Montenegrin Journal of Economics

Volume 12 Number 2 July 2016

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Montenegrin Journal of Economics, Vol. 12, No. 2 (July 2016)

Editor in Chief Veselin Draskovic, University of Montenegro, Maritime Faculty of Kotor, Montenegro

Co-Editors Yuriy Bilan, University of Szczecin, Faculty of Economics Science and Management, Poland Yochanan Shachmurove The City College of the City University of New York, Department of Economics and Business, USA Radislav Jovovic University Mediterranean, Faculty of Business Studies, Montenegro

Advisory Board Harry M. Markowitz, Nobel Laureate Rady School of Management at the University of California, USA Oliver E. Williamson, Nobel Laureate University of California, Berkeley, USA Lloyd Blenman University of North Carolina-Charlotte, President at Midwest Finance Education Foundation, USA Victor Polterovich Central Economics and Mathematics Institute, Russian Academy of Science and Moscow School of Economics / Lomonosov's Moskow State University, Russia Yochanan Shachmurove The City College of the City University of New York, Department of Economics and Business, USA

Associate Editor and Journal Administrator Oleksandr Dorokhov, Kharkiv National University of Economics, Faculty of Economic Informatics, Ukraine

Technical editor Milojko Pusica, B. Sc. ing. electrotecnics, „Tangenta“ Niksic, Montenegro

International Editorial Board

Serguei Aivazian, Central Economics and Mathematics Institute of the Russian Academy of Sciences / Lomonosov's Moscow State University, Russia Jaroslav Belás, Tomas Bata University in Zlín, Fakulty of management and economics, Department of Enterprise Economics, Czech Republic István Benczes, Corvinus University of Budapest, Faculty of Economics, Hungary Bolesław Borkowski, SGGW Warsaw, Faculty of Applied Informatics and Mathematics, Department of Econometrics and Statistics, Poland Laszlo Csaba, Central European University, Department of International Relations and European Studies, Budapest / Budapest University of Eco- nomic Sciences and Public Administration, Hungary Fan Gang, Graduate School of Chinese Academy of Social Sciences (CASS) / China's National Economic Research Institute (NERI), China Yuriy Gavrilec, Central Economics and Mathematics Institute of the Russian Academy of Sciences, Russia Wei Ge, Bucknell University, Department of Economics, Lewisburg, USA Balazs Hamori, Corvinus University of Budapest, Hungary Boris Popesko, Tomas Bata University in Zlín, Fakulty of Management and Economics, Czech Republic Yu Hsing, Southeastern Louisiana University, College of Business, Hammond, LA, USA Wen-jen Hsieh, University Road, Tainan / Art Center National Cheng Kung University, Taiwan Svetlana Kirdina, Institute of Economics Russian Academy of Sciences, Russia George Kleiner, Central Economics and Mathematics Institute of the Russian Academy of Sciences, Russia Siu Lee Jasmine Lam, Nanyang Technological University, Singapore Valeriy Makarov, Central Economics and Mathematics Institute of the Russian Academy of Sciences/ Lomonosov's Moscow State University / New Economic School, Russia Vladimir Matveenko, National Research University Higher School of Economics, St. Petersburg, Russia Alojzy Nowak, University of Warsaw, Faculty of Management, Poland Yuriy Osipov, Lomonosov's Moscow State University, Faculty of Economics, Russia Jiancai Pi, School of Business, Nanjing University, China Evgeniy Popov, Institute of Economics, Urals Branch of Russian Academy of Sciences, Ekaterinburg, Russia Uriel Spiegel, Bar-Ilan University, Faculty of Social Sciences, Ramat-Gan, Israel Aleksandr Tatarkin, Institute of Economics, The Ural Branch of Russian Academy of Sciences, Ekaterinburg, Russia Merih Uctum, The Graduate Center City University of New York, USA João Paulo Vieito, Polytechnic Institute of Viana do Castelo, Portugal Milos Vulanovic, City University of Hong Kong Eric Wdoviak, Farmingdale State College, New York, USA Bagrat Yerznkyan, Central Economics and Mathematics Institute, Russian Academy of Science / State University of Management Moscow, Russia

Regional Editorial Board Sanja Bauk, University of Montenegro, Faculty of Maritime Studies Kotor, Montenegro Mimo Draskovic - Secretary of Editorial Boards, University of Montenegro, Maritime Faculty of Kotor, Montenegro Gordan Druzic, Croatian Academy of Sciences and Arts, Zagreb, Croatia Miomir Jaksic, University of Belgrade, Faculty of Economics, Serbia Borut Jereb, University of Maribor, Faculty of Logistics Celje, Slovenia Slobodan Lakic, University of Montenegro, Faculty of Economics Podgorica, Montenegro Milan Lakicevic, University of Montenegro, Faculty of Economics Podgorica, Montenegro Andjelko Lojpur, University of Montenegro, Faculty of Economics Podgorica, Montenegro Ljubomir Madzar, Institute of strategic studies and development „Petar Karić“ of the Alfa University in Novi Beograd, Serbia Joze Mencinger, University of Ljubljana, Law School, Slovenia Janez Prašnikar, University of Ljubljana, Faculty of Economics, Institute for South-East Europe, Slovenia Milivoje Radovic, University of Montenegro, Faculty of Economics Podgorica, Montenegro Ivan Ribnikar, University of Ljubljana, Faculty of Economics, Slovenia Guste Santini, University of Zagreb, Croatia Ivo Speranda, University of Dubrovnik , Department of Economics and Business Economics, CroatiaUniversity of Rijeka, Faculty of Econo- mics, Croatia

Montenegrin Journal of Economics, Vol. 12, No. 2 (July 2016)

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E.V. Popov, I.S. Katz, A.Y. Veretennikova / Montenegrin Journal of Economics, Vol. 11, No. 2 (2015), 5-17

Montenegrin Journal of Economics

Vol. 12, No. 2 (2016) ‘

C O N T E N T S

The Size of Innovation Space as a Factor of Innovation Activity in Regions Sergey Ayvazyan, and Mikhail Afanasyev ...... 7

Relationships Between Investment Effectiveness Controlling and Business Performance Rastislav Rajnoha, Petr Novák, and Martina Merková ...... 29

Trade Liberalisation and Export Performance of the Western Balkans Łukasz Klimczak ...... 45

Central and Eastern European Share Markets and the Halloween Effect Peter Arendas, and Bozena Chovancova ...... 61

A Mid-Term Forecast of Maximum Demand for Electricity in Poland Jacek Brożyna, Grzegorz Mentel, and Beata Szetela …..………………………………...... 73

The Strategy for Russia’s Breakthrough to the Future: Lvov’s Legacy Bagrat Haykovich Yerznkyan ...... 89

Budget Constraint Fulfilment in Some EU Candidate Countries Miomir Jaksic, and Milutin Jesic ………...... 101

Different Values Forms in Organization: is the Congruence Possible? Jolita Vveinhardt, Evelina Gulbovaitė, and Dalia Streimikiene ...... 117

Institutions for Decreasing of Employee Opportunism Evgeny V. Popov, and Evgenia V. Ersh ...... 131

Hypothetical Matrix for Institutional Modeling of the Basis for Economic Development in the Countries of Southeast Europe Milica Delibasic ...... 147

GDP and Net Migration in Some Eastern and South-Eastern Countries of Europe. A Panel Data and Bayesian Approach Mihaela Simionescu, Daniel Ciuiu, Yuriy Bilan, and Wadim Strielkowski 161

Author Guidelines ...... 177

Sergey Ayvazyan, and Mikhail Afanasyev / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 7-27

Montenegrin Journal of Economics

Vol. 12, No. 2 (2016), 7-27

‘

The Size of Innovation Space as a Factor of Innovation Activity in Regions

Sergey Ayvazyan 1, and Mikhail Afanasyev 2

1 Professor, Deputy Director of CEMI RAS, Moscow, e-mail: [email protected] 2 Professor of Department of Mathematical Economics of SAUHS, Head of the Laboratory of CEMI RAS, e-mail: [email protected]

ARTICLE INFO ABSTRACT Received March 20, 2016 The research objective is to obtain and ground the quantitative Received in revised form - characteristics of the impact of science and business on the results Accepted May 28, 2016 of innovation activity of the Russian Federation subjects. Under Available online June 15, 2016 such results the number of patents issued and new production technologies developed are considered. Hypotheses testing is con- JEL classification: ducted enabling to establish the relationship between the innovation activity of a region and the number of potential links between C12, C51, R15 the organizations creating new knowledge and innovation active businesses. The totality of these relations is characterized as an DOI: innovation space of a region. The results obtained through econo- 10.14254/1800-5845.2016/12-2/11 metric modelling using the official data from the Rosstat and U. S. Census Bureau, Patent and Trademark Office, National Center for Keywords: Education Statistics for the period 2009-2013 allow to justify some regional economy, properties of estimates of the regional innovation space technical econometric modelling, efficiency and the estimates of innovation activity results elasticity hypothesis testing, by the innovation space size for the subjects of the Russian Federa- stochastic frontier, tion and the states of the USA. An emphasis is made on the role of efficiency estimation public authorities in creating a favourable environment for innovation activity enhancement for the Russian Federation subjects through facilitating new research organizations emergence and higher education institutions start-ups.

1. INTRODUCTION The current understanding of the innovation system functioning at the national and regional levels is related to the overall efforts of government, business and academia, aimed at creation, dissemination and use of new ideas, knowledge, technologies and products (Itskovits, 2010). In international practice, an important criterion of effectiveness of the innovation system is the R&D (Research and Development) performance. However, the process of emergence of an innovative idea and its further transformation into innovation has been little explored through computer simulation methods and, partly for that reason, we do not have convincing explanations for the effectiveness or failure of a particular innovation system as a whole. The result of the innovation process is largely determined by the ability of regional innovation system subjects to communicate and interact (Butler, Gibson, 2013; Golinchenko, Balycheva, 2012;

Sergey Ayvazyan, and Mikhail Afanasyev / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 7-27

Ivanov et al., 2012; Larina, 2012; Makoveyeva, 2012; Rumyantsev, 2013; Simachev, 2012). Apart from the direct outcomes, created by such interaction, we might gain positive externalities and synergistic effects (Polterovich, 2010). Obtaining quantitative characteristics of such relationships and interactions is one of the most difficult tasks in the analysis of innovation processes. The key objective of this paper is to obtain and substantiate the quantitative characteristics of the influence of science and business on the results of innovation activity of the Russian Federation subjects. Under such results the number of patents issued and new production technologies are considered, viewed by K. Freeman as the primary outcome of the innovative development of the economy (Freeman, 1987). The research grounds the expediency of estimating the number of potential relationships between the subjects of the Russian regional innovation systems, i.e. organizations, creating new knowledge and innovative ideas, and innovation active businesses using this knowledge to produce innovations. A hypothesis that these relationships is the core driver of production technologies and patents development has been tested. The paper consists of four sections. The first section presents the hypothesis testing, which confirms the determining impact of a region’s scientific and production potential on its innovation activity enhancement. The second section grounds the relationship between the results of innovation activity in the region and the number of potential links between knowledge creating organizations and innovation active enterprises. The totality of these relations is characterized further as innovation space of the region. The third section demonstrates that the parameters of the relationship between the number of patents issued and the size of the innovation space for the Russian Federation subjects are negligibly different from the ones present in the United States federal structure. The fourth, concluding section, describes the elasticity properties of the result of innovation activity in the region by the size of its innovation space and proves the possibility of estimating the region’s share in the innovation space used. The role of the state and regional governments in the development of innovation space to support sustainable innovative performance is emphasized.

2. THE IMPACT OF SCIENCE AND BUSINESS DEVELOPMENT ON INNOVTION ACTIVITY IN REGIONS Hypothesis 1. The number of organizations, creating new knowledge, and the number of innovation active businesses are the factors determining the result of innovation activity of the Russian Federation subjects.

Testing of the hypothesis is conducted using the methods of econometric modelling based on the official statistics data that characterize the potential of science and business at the regional level. In (Makarov et al., 2014) the three-factor models of production potential of the Russian Federation regions have been constructed, defining the dependence of GRP on the main production factors: labour, physical and intellectual capitals for the period of 2009-2013. As the characteristics of intellectual capital such indicators as "the number of personnel engaged in research and development" and "the number of higher education institutions" were considered. “The number of personnel engaged in research and development" as the intellectual capital indicator proved to be significant in the models based on the data of 2009 and 2010. In models constructed for 2011-2013 its impact on GRP is being lost, while the importance of “the number of higher education institutions” indicator increases. The research findings allow us to consider the above indicators as characteristics of the scientific potential of regions in assessing the results of their innovation activity.

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As an alternative to characterize the number of higher education institutions the indicator of the number of organizations engaged in R&D is applied. The latter to a greater extent takes into account the specific features of scientific research arrangement in the Russian Federation, since it includes the Russian Academy of Sciences institutes, project institutes and design bu- reaus. The number of higher education institutions is a characteristic of intellectual capital in most developed countries, thus making it convenient for comparative analysis. However, the estimates obtained for the subjects of the Russian Federation on the basis of this indicator, currently can be classified as hypothetical, being valid under the condition that only universities are involved in innovation activities as organizations that create new knowledge, ignoring the participation of other research organizations. Hence, hereinafter the indicator of "the number of organizations engaged in R&D" will be employed as the fundamental characteristics of the scientific potential of the Russian Federation subjects. As a conditional estimate, for comparison purposes, the indicator of “the number of higher education institutions” will be considered. In (Makarov et al., 2014) it is argued that the significant factor of efficiency in regions production potential models based on 2009-2013 statistical data is the number of innovation active businesses. Further, this indicator is used as the characteristics of business potential at the regional level. For the same purpose fixed assets value is considered. To test Hypothesis 1 the production functions that determine the dependence of the result of innovation activity in the region on the totality of the above characteristics of science and business for each year in the period 2009-2012 are constructed. Further, we explore power-law production functions1, in logarithmic form presented as

lnQi  0  K lnKi  L lnLi  S lnSi  B lnBi  vi ui . (1)

Here Qi is the result of innovation activity in the region i (two indicators are considered:

Qi  pati - the number of patents issued in the region i , Qi  techi - the number of new production technologies developed in the region i in a year t ); Ki - the fixed assets value;

Li - the number of personnel engaged in R&D; Si - the number of organizations creating new knowledge (two indicators are considered: Si  heii - the number of higher education institutions, Si  rori - the number of organizations engaged in R&D); Bi - the number of businesses (two indicators are considered: Bi  busi - the total number of businesses in a region,

Bi  inni - the number of innovation active businesses); 0 ,  K ,  L ,  S ,  B - parameters.

The random component vi  ui reflects the impact of uncertainty and efficiency factors on the process of innovation activity in the region. To simulate effects of uncertainty a normally distrib- 2 uted random variable vi with zero mathematical expectation vi  N(0, v ) is used. For the simulation of the effects of efficiency factors a non-dependent on vi non-negative random variable ui , having zero-truncated normal distribution with zero mathematical expectation  2 ui  N (0, u ) is applied. This approach to the modelling of residues is consistent with the concept of stochastic frontier (Kumbhakar, Lovell, 2004) and allows to obtain the correct estimates of technical efficiency of production factors.

1 The rationale for this specification of the production function is given in (Aivazyan, Afanasyev, 2014) 9

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Table 1. Given data for testing Hypothesis 1.

Notation Indicator Title Time period Source the number of patents issued 2008-2013 (Inflow…, 2013 ) pati the number of new production tech- 2008-2013 (new technologies tech i nologies developed in a region developed, 2013) fixed assets cost 2009-2012 (fixed assets cost …, 2012) Ki the number of personnel engaged in 2009-2012 (the number of Li R&D personnel …, 2013) the number of higher education 2008-2013 (higher education institu- heii institutions in a region tions, 2013) the number of organizations en- 2008-2013 (organizations …, 2013) ror i gaged in R&D the number of businesses 2008-2013 (the number of businesses bus i in a region, 2013) I the share of innovation active busi- 2008-2013 (organizations’ innovation i nesses in total number of enter- activity..., 2013) prises in a region

In the adopted notations the number of innovation active businesses in the region is expressed by the value inni  Ii  busi . To test Hypothesis 1 production functions that determine the dependence of the number new production technologies developed (patents issued) on the set of science and business potential characteristics at the regional level are constructed. The factor of results of innovation activity is estimated by the science or business characteristic significant in production functions models constructed for the given period of 1 time. The method of testing Hypothesis 1 H0 : S  0;B  0 is being reduced to the verifica- 1 tion of statistical hypothesis. The Hypothesis 1 is accepted if the statistical hypothesis H0 is not rejected for 90% of the total number of estimated models of the form (1), built for different 1 characteristics Qi and Si for the period 2009-2012. If the hypothesis H0 is rejected for more than 10% of the constructed models, the Hypothesis 1 is rejected.

Table 2. Parameter estimates of model (1) for patents issued.

2009 2009 2010 2010 2011 2011 2012 2012 K .130 .139 .086 .127 .273 .313 .192 .148 L .208 -.078 .137 -.112 .124 -.051 -.016 -.038 Ror .823*** .759*** .697*** .851*** inn .540*** .481*** .798*** .657*** .540*** .427*** .448*** .430*** hei .425** .343* .406** .868*** cons -2.151 -1.954 -3.279 -3.050 -3.829* -3.964* -2.201 -2.191 log likeli -99.16 -97.64 -94.61 -92.85 -98.01 -96.76 -90.12 -96.84 sigma v .442 .444 .447 .471 .441 .482 .508 .460 sigma u 1.243 1.204 1.127 1.049 1.212 1.122 .930 1.160

* 10% significance level; ** 5% significance level; *** 1% significance level

Sergey Ayvazyan, and Mikhail Afanasyev / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 7-27

For each year within the period from 2009 to 2012 stochastic production functions (1) are constructed. Their parameters are estimated by maximum likelihood on the basis of information data on 80 subjects of the Russian Federation. The list of regions is presented in column 2 of Table A1 of the Annex. Overall, for this period 16 models (8 for the patents and 8 for production technologies) have been built. Parameter estimates of these models are presented in Tables 2 and 3. The results obtained do not contradict the Hypothesis 1. In all models the characteristics of a region’s scientific potential – "the number of organizations engaged in R&D" (the alternative is "the number of higher education institutions") and business capacity – "the number of innovation active businesses" significantly influence both the number of patents granted (Table 2) and the number of production technologies developed (Table 3).

Table 3. Parameter estimates of model (1) for production technologies

2009 2009 2010 2010 2011 2011 2012 2012 K .115 .019 -.086 -.146 -.041 -.094 .168 .071 L .297 -.007 -.039 .091 .286 .158 .249 -.054 ror .813*** .363* .623*** .452*** inn .236*** .150* .314*** .544*** .469*** .299** .538** .538*** hei .224*** .261* .242* .357** cons -4.261 -2.697 -4.062 -1.665 -2.736 -1.675 -2.031 -3.031 log likeli -100.08 -96.16 -99.59 -98.62 -106.77 -104.85 -111.15 -113.57 sigma v .845 .804 .751 .408 .482 .623 .299 .494 sigma u .357 .211 .722 1.261 1.359 1.093 1.730 1.520

The number of organizations creating new knowledge as a characteristic of the scientific potential in a region and the number of innovation active businesses as a characteristic of business affect the result of innovation activity of the Russian Federation subjects. Through testing results for the period 2009-2012 the Hypothesis 1 is accepted. The characteristics of the scientific potential – the number of personnel engaged in R&D" and of business capacity – "the fixed assets value" are insignificant in all models. Model (1) can be transformed to the form

lnQi  0  S lnSi  B lnBi  vi ui . (2)

3. THE SIZE OF INNOVATION SPACE AS A FACTOR OF INNOVATION ACTIVITY OUTCOME

Hypothesis 2. The outcomes of innovation activity in the Russian Federation regions depend on the size of innovation space, which is determined by the number of potential pairwise relationships between organizations, creating new knowledge, and innovation active businesses.

The results of this hypothesis validation allows to prove the possibility of using quantitative estimates of potential pairwise relationships between organizations engaged in R&D (the alternative is higher education institutions) and businesses that use new knowledge for creating innovations, as a factor determining the results of innovation activity at the regional level. The totality of potential links between such organizations and businesses will be referred to as innovation space, and their number as the size of innovation space.

Sergey Ayvazyan, and Mikhail Afanasyev / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 7-27

Introduce the notations  S  1,  B  1  , where 1  0 ,  can be both positive and negative. Then after the transformation of function (2) we get:

lnQi  0  1 ln(Si *Bi ) Bi  vi ui . (3)

Under the notations  B  1,  S  1  , after the transformation we obtain:

lnQi  0  1 ln(Si *Bi ) Si  vi ui . (4)

Testing of Hypothesis 2 is being reduced to the verification of statistical hypothesis 2 H 0 : 1  0,  0 for each estimated model of the form (3) or (4). The Hypothesis 2 is accepted for the period in question, when a statistical hypothesis is not rejected for 90% of the 2 total number of the estimated models. If the hypothesis H0 is rejected for more than 10% of the models, the Hypothesis 2 is rejected for the period in question. Parameter estimates for the eight models of the forms (3) and (4) based on the data of 80 regions of the Russian Federation within the period 2009-2012 for the patents issued are 2 presented in Table 3. For all models the hypothesis H0 is not rejected. Parameter estimates for the eight models of the forms (3) and (4) for production technologies are presented in Table 4. 2 For 7 out of the 8 models the hypothesis H0 is not rejected. For one of the models built on 2 2 2009 data the hypothesis H0 is rejected. Thus, the hypothesis H0 is not rejected for 15 out of the 16 constructed models that allows for accepting the Hypothesis 2.

Table 4. Parameter estimates of models (3) and (4) for the patents issued

2009 2009 2010 2010 2011 2011 2012 2012 ror*inn .532*** .559*** .788*** .692*** hei*inn .624*** .645*** .874*** .794*** ror .162 .172 -.268 inn .127 .007 -.364 -.337 -.235 cons -.252 -.740 -.880 -1.057 -.266 -1.006 -.163 -.019 log likeli -102.21 -94.36 -82.60 -90.80 -91.57 -98.03 -93.04 -99.62 sigma v .4250 .437 .378 .409 .471 .450 .539 .460 sigma u 1.338 .746 .982 1.100 1.024 1.200 .944 1.229

Table 5. Parameter estimates of models (3) and (4) for production technologies

2009 2009 2010 2010 2011 2011 2012 2012 ror*inn .813*** .492*** .795*** .239** hei*inn .496*** .283*** .346*** .432 ror .109 inn -.173 -.658** -.545 .375 hei .342 .379 -.070 cons -2.266 -2.524* -1.975 -2.087 -1.83 -2.212* -1.453 - 2.657** * log likely -105.01 -96.17 -108.63 -102.60 -112.06 -105.61 -121.97 -115.61 sigma v .898 .804 .931 .807 .737 .653 .830 .484 sigma u .027 .025 .217 .549 1.091 1.061 1.243 1.587

Sergey Ayvazyan, and Mikhail Afanasyev / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 7-27

The production function of the form (2) can be transformed to the form (5):

М1: lnQi  c  lnVi  vi ui , (5) where Vi  Si *Bi - is the number of potential pairwise relationships between organizations engaged in R&D (the alternative is higher education institutions) and innovation active businesses. Further value Vi will be called the size of innovation space in the region. Thus, model (5) describes the dependence of the result of innovation activity in the region on the size of innovation space. Thereafter, as one of the characteristics of the innovation system of the Rus- sian Federation at the regional level, the  parameter estimate is considered, characterizing the elasticity of innovation activity in the region by the size of innovation space.

Figure 1a. Statistical characteristics Figure 1b. Statistical characteristics

Vi = hei i * inni , logarithmic scale Vi = ror i * inni , logarithmic scale

Figure 1a shows the dynamics of statistical characteristics of the size of innovation space

V i  hei i * inn i for 80 regions of the Russian Federation, being estimated by the number of higher education institutions and innovation active businesses in logarithmic form for each year of the period from 2008 to 2013. Figure 1b presents the statistical characteristics of innovation space size Vi  rori * inn i , estimated by the number of organizations engaged in R&D and innovation active businesses. The mean values demonstrate their stability over time for each evaluation method. The maximum values corresponding to the region of Moscow are also stable for the given period of time. It should be noted that the size of innovation space, calculated by the number of higher education institutions indicator, is significantly below the level estimated on the basis of more relevant to the research objectives indicator of the number of organizations engaged in R&D. Accordingly, the use of characteristics

V i  hei * inn i when evaluating the impact of science and business on the results of innovation activity of the Russian Federation subjects may lead to inflated estimates of the technical efficiency of innovation space. Table 6 presents the parameter estimates of the six models of the form (5) for the patents issued with the size of innovation space estimated by the number of organizations engaged in R&D and innovation active businesses for each year of the period from 2008 to 2013.

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Table 6. Parameter estimates of models (5) with Vi  rori * inn i for the patents issued

2008 2009 2010 2011 2012 2013  0.615*** 0.586*** 0.618*** 0.630*** 0.581*** 0.571*** C -1.105*** -0.805*** -1.151*** -1.374*** -0.699*** -0.591*** log likely -102.598 -94.715 -91.131 -98.484 -99.941 -98.281 sigma v 0.569 0.428 0.398 0.448 0.499 0.484 sigma u 1.134 0.762 1.122 1.213 1.179 1.162 W 0.165 0.253 0.155 0.112 0.301 0.355

Table 7 provides parameter estimates of the 6 models of the form (5) for the patents issued with the size of innovation space, estimated by the number of higher education institutions and innovation active businesses for each year between 2008 and 2013.

Table 7. Parameter estimates of models (5) с V i  hei i * inn i for the patents issues

2008 2009 2010 2011 2012 2013  0.626*** 0.620*** 0.649*** 0.661*** 0.623*** 0.599*** C -0.535*** -0.344*** -0.853*** -0.994*** -0.581*** -0.275*** log likely -96.202 -91.601 -82.606 -92.729 -94.105 -92.921 sigma v 0.520 0.400 0.378 0.453 0.550 0.500 sigma u 1.053 1.133 0.982 1.078 0.950 1.011

Table 8 offers the parameter estimates of five models of the form (5) for new production technologies with the size of innovation space, estimated by the number of organizations engaged in R&D and innovation active enterprises for each year of the period 2008-2012.

Table 8. Parameter estimates of models (5) с Vi  rori * inn i for production technologies 2008 2009 2010 2011 2012

 0.513*** 0.587*** 0.565*** 0.655*** 0.572***

c -2.859*** -4.139*** -3.684*** -4.558*** -3.156***

log likely -126.410 -135.704 -138.374 -136.169 -141.695

sigma v 1.39E-07 0.3682 0.330 0.362 0.377

sigma u 2.349 2.330 2.454 2.350 2.532

Table 9 demonstrates parameter estimates of five models of the form (5) for the production technologies with the innovation space size, estimated by the number of higher education institutions and innovation active businesses for each year of the period 2008-2012.

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Table 9. Parameters estimates of models (5) с Vi  heii * inni for production technologies

2008 2009 2010 2011 2012

 0.494*** 0.568*** 0.544*** 0.585*** 0.519***

C -2.194*** -3.237*** -2.778*** -2.965*** -1.913***

Log likely -136.319 -143.577 -146.084 -145.531 -149.159

sigma v 0.471 0.587 0.545 0.583 0.597

sigma u 2.252 2.374 2.515 2.456 2.586

Parameter estimates are significant in all 22 models of the form (5). The size of innovation space can be considered as a factor of the patents issued and production technologies at the regional level.

4. COMPARATIVE ANALYSIS OF INNOVATION SPACE IMPACT ON THE NUMBER OF PATENTS ISSUED TO THE SUBJECTS OF THE RUSSIAN FEDERATION AND THE USA Hypothesis 3: The parameters of the function (5) describing the dependence of the number of patents issued on the size of innovation space of the Russian Federation subjects, estimated by the number of organizations engaged in R&D and innovation active businesses do not differ significantly from the parameters of the function (5) representing the dependence of the number of patents issued on the size of innovation space across the US states, estimated by the number of higher education institutions and high-tech companies.

While testing Hypothesis 3 for the subjects of the Russian Federation, the data presented in Table 1 were used, for the US states - the data described in Table 10, respectively.

Table 10. Given data for testing Hypothesis 3 by US states Notation Indicator Title Time period Source the number of patents is- pat 2006-2013 (Number of Patents, 2014) i sued the number of higher educa- hei 2006-2010 (Number of institutions, 2010) i tion institutions in a region

total number of companies 2006-2012 (All business establishments, 2014) comi the number of high-tech htcom 2006-2010 (High-technology establishments, 2014) i companies

Table 11 provides the parameters estimates for five models of form (5) for the patents issued with the size of innovation space, estimated for the US states as

V i  hei i * htcom i for each year in the period 2006-2010.

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Table 11. Parameter estimates of models (5) с V i  hei i * htcom i for the patents issued

2006 2007 2008 2009 2010  0.663*** 0.662*** 0.679*** 0.668*** 0.679*** c -1.939*** -2.027*** -2.293*** -2.108 -2.011*** log likely -53.607 -53.859 -54.120 -53.463 -52.528 sigma_v 0.692 0.695 0.699 0.690 0.677 sigma_u 0.008 0.010 0.009 0.015 0.014 w 0.053 0.046 0.034 0.042 0.051

Fig. 2 (series 1) shows the dynamics of estimates of the elasticity of the number of patents issued by the size of innovation space across the US states, calculated with consideration of the number of higher education institutions and high-tech companies according to 2006-2010 data (see the  parameter estimates in Table 11). Series 2 in Fig. 2 reflects the dynamics of the elasticity values by the size of innovation space of the Russian Federation subjects, calculated subject to the number of organizations engaged in R&D and innovation active businesses (see the  parameter estimates in Table 6). The difference in values of the elasticity coefficient estimates for the subjects of the Russian Federation and of US states for the period 2008-2010 does not exceed 0.08.

Figure 2. Estimates of the elasticity of the number of patents issued by the size of innovation space for the US states (Series 1) and the Russian Federation subjects (Series 2).

0.7 0.68 0.66 0.64 0.62 0.6 0.58 0.56 0.54 0.52 0.5 2006 2007 2008 2009 2010 2011 2012 2013

Series 1 Series 2

Figure 3a demonstrates the dependence of the number of patents issued on the size of innovation space, in logarithmic scale, for the Russian Federation subjects based on 2010 data; Figure 3b - for the US states and Figure 3c – for the totality of the Russian Federation subjects and the states of the USA.

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Figure 3a. Subjects of the Russian Federation Figure 3b. USA states

10 12 9 8 10 7 8 6 5 6 4 4 3 2 2 1 0 0 0 5 10 15 20 0 5 10 15 20

Figure 3a. Subjects of the RF, Figure 3b. USA states,

Vi  rori * inn i V i  hei i * htcom i

Figure 3c. Regions of the Russian Federation and the US states

0 0 5 10 15 20

Figure 3c. Regions of the RF and the US states

To test Hypothesis 3 models have been built in the form

М2: lnQi  c cd di ( d dvi )lnVi vi ui , (6)

where di  dvi  0, if the index i refers to the subject of the Russian Federation and di  dvi 1, if the index i refers to a US state. For the subjects of the Russian Federation the innovation space size is calculated on the basis of the number of organizations engaged in R&D and the number of innovation active businesses Vi  rori * inn i . For the US states – with respect to the number of higher education institutions and high-tech companies

V i  hei i * htcom i . Test of Hypothesis 3 is reduced to verification of the statistical hypothesis 3 H 0 : cd   d  0 for models of the form (6) constructed for 2008-2010. The Hypothesis 3 is 3 accepted if the statistical hypothesis H 0 is not rejected for each of the three models.

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Estimation of parameters of model M2 by maximum likelihood is performed for each year of the period 2008-2010 within the data on 131 regions: 80 subjects of the Russian Federation and 51 state of the USA. Parameter estimates of model M2 given in Table 12 under the control 3 variables di and dvi proved insignificant. The hypothesis H 0 is not rejected for each of the three models. Hypothesis 3 is accepted. Thus, to describe the dependence of the number of patents issued on the size of innovation space across the subjects of the Russian Federation and the US states a generic model of the form M1can be constructed. Parameter estimates of this model for 2008-2010 period are given in Table 12.

Table 12. Parameter estimates of models M1 and M2 for the totality of 131 regions.

2008 2008 2009 2009 2010 2010 M2 М1 M2 М1 M2 М1 V .623*** .669*** .616*** .663*** .637*** .723*** dv .027 -.002 -.0001 d .113 .460 .743 cons -1.318*** -1.689*** -.995** -1.426*** -1.467* -2.335*** log likeli -159.90 -163.82 -155.68 -159.08 -146.33 -156.96 sigma v .601 .648 .453 .530 .482 .656 sigma u .948 .915 1.133 1.064 .958 .771

Control variables are not significant in each of the three models (M2). To compare the technical efficiency of the subjects of the Russian Federation and the US states, models of the form M1, built for the totality of 131 regions, can be used.

5. SOME ESTIMATES PROPERTIES OF INNOVATION ACTIVITY RESULTS ELASTICITY BY THE SIZE AND THE EFFICIENCY OF REGIONAL INNOVATION SPACE Property 1. A method of estimating the size of innovation space (based on the number of higher education institutions or the number of organizations engaged in R&D for the subjects of the Russian Federation; for the states of the US – considering the number of high-tech companies in the total number of firms) has no significant effect on the estimates of the elasticity of innovation activity results by the size of innovation space and their dynamics.

Figure 4 provides the estimates of the elasticity of the number of patents issued by the innovation space size V i  hei i * inn i calculated for the period 2008-2013 based on the number of higher education institutions (series 1) and the size of innovation space

V i  ror i * inn i , given the number of organizations engaged in R&D (series 2). The maximum difference in elasticity coefficients obtained under model (5) for the two methods of estimating the size of innovation space does not exceed 0.05. The correlation coefficient of 0.906 indicates the dependence of the estimates of elasticity for different methods of estimating the size of innovation space. The choice of method for estimating the size of innovation space (based on the number of higher education institutions or organizations engaged in R&D) has no significant effect on the dynamics of the elasticity coefficients of the number of patents issued.

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Fig.ure 4. Elasticity estimates on the number of patents issued by the size of innovation space for the subjects of the Russian Federation under model (5) for the period 2008-2013: series 1

Vi  hei i * inn i (data from Table 7), Series 2 - for V i  ror i * inn i (data from Table 6)

series 1 series 2

Figure 5 shows the estimates of the elasticity of the number of production technologies developed within the size of innovation space V i  ror i * inn i calculated for the period 2008-2012 taking into account the number of organizations engaged in R&D (series 1) and the size of innovation space V i  hei i * inn i , calculated with regard to the number of higher education institutions (series 2). The maximum difference between the elasticity coefficients for each year does not exceed 0.07. A high correlation coefficient of 0.903 indicates the strength of relationship between these estimates. The choice of estimation method to measure the size of innovation space has no significant effect on the dynamics of the elasticity coefficients of the number of production technologies.

Figure 5. The estimates of elasticity of production technologies developed within the size of the Russian Federation subjects innovation space according to model (5) for the period 2008-

2012: series 1 for V i  ror i * inn i (data from Table 8), series 2 - for

V i  hei i * inn i (data from Table 9)

Sergey Ayvazyan, and Mikhail Afanasyev / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 7-27

series 1 series 2

Table 13 provides the parameter estimates of model (5) for patents issued according to the data on 51 states of the USA. For comparison with the results presented in Table 14, the size of innovation space is calculated as V i  hei i * com i taking into account both the number of high-tech companies and the total number of businesses.

Table 13. Parameter estimates of model (5) with V i  hei i * com i for patents issued.

2006 2007 2008 2009 2010 2011 2012 δ 0.669*** 0.669*** 0.685*** 0.672*** 0.683*** 0.684*** 0.672*** c -3.729*** -3.812*** -4.102*** -3.850*** -3.773*** -3.739*** -3.505*** log likely -56.801 -56.858 -57.342 -56.383 -55.593 -57.071 -54.150 sigma v 0.736 0.737 0.744 0.730 0.719 0.740 0.699 sigma u 0.011 0.016 0.011 0.010 0.013 0.011 0.018 w 0.0038 0.0033 0.0025 0.0032 0.0039 0.0042 0.0054

Figure 6 displays the estimates of elasticity of the number of patents issued within the size of innovation space V i  hei i * com i calculated for the period 2006-2012 subject to the total number of businesses in US states (series 1) and the size of innovation space

V i  hei i * htcom i with regard to the number of high-tech companies for the period 2006-2010 (series 2). The maximum difference between the elasticity coefficients for each year of the 2006-2010 period does not exceed 0.01. The correlation coefficient of 0.991 indicates that the choice of estimation method for measuring the size of innovation space has no significant effect on the dynamics of the elasticity coefficients for patents issued.

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Figure 6. The estimates of elasticity of the number of patents issued within the size of the US states according to model (5) for the period 2008-2012: series 1 for

V i  hei i * com i (data from Table 13), series 2 - for V i  hei i * htcom i (data from Table 11)

series 1 series 2

Thus, the elasticity estimates demonstrate weak dependence on the method of innovation space evaluation. Their dynamics is consistent with different estimation methods. It should be noted that the method of evaluating the innovation space affects the constant of the model, which scales the x-axis.

Property 2. For most regions of the Russian Federation the technical efficiency in the use of innovation space estimated by the number of organizations engaged in R&D and innovation active businesses is close to technical efficiency in the use of innovation space of the US states, estimated by the number of higher education institutions and high- tech companies. 2 2 The estimated parameters  v , u enable to estimate mathematical expectation ~ u ( /  ) 1 TE E(e i v u ) i * * exp{ 2 ~ } i   i  i  ~  *  i (Battese, Coelli, 1988), where (i / * ) 2 ~ 2 2 2 2 2 2 2 2 2 it  (vi  ui ) u / ,  *   u  v /  ,    u   v .

According to the stochastic frontier concept (Kumbhakar, Lovell, 2004), the value TEi characterizes the technical efficiency of innovation space use in the region. Technical efficiency estimatesTEi are relative characteristics of regional efficiency. Their values can vary from year to year. However, the regions ranks determined by the technical efficiency estimates, are the sustainable characteristics of their innovation activity. Table 14 provides the values of Spear- man's rank correlation coefficients of efficiency estimates obtained by model M1 (see Table 15) for 2008, 2009 and 2010 for the totality of 131 subjects of the Russian Federation and the US states that demonstrate their high dependence over time.

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Table 14. Spearman's rank correlation coefficients of efficiency estimates TEi by model М1 _2008 2009 2010 2008 1.000 2009 0.933 1.000 2010 0.897 0.933 1.000

c / In (Aivazyan, Afanasyev, 2015) it has been argued that the value w  e assumes being interpreted as the expected share of the size of innovation space used by the region, effectively 2 ~ creating discrete results of innovation activity. As an estimate wi of the share of innovation space used by the region when creating the innovations of a specific type the value  1/  ~ ~ (w TEi ) can be taken. Then the value Vi  wiVi , calculated for the relevant year, can be considered as an estimate of the innovation space size used by the region to generate a specific outcome of innovation activity. Dynamics of regions’ innovation activity results is determined by the dynamics parameter w . The growth of parameter w is associated with an increase in the expected number of results generated by the innovation efficient regions. The estimates of the value w of patents issued to the subjects of the Russian Federation are provided in the last row of Table 6. In the last row of table 11 these estimates are presented for the US states. The estimates vary by an order of magnitude due to differences in the size of innovation space used by the subjects of the Russian Federation and the US states. For the same reason the values w vary by the same order of magnitude in tables 11 and 13 for the US states obtained with the different methods of evaluating the innovation space. The dynamics w is determined by the ratio of the parameters c and  : since c  0 and   0 , and with increase of the value w grows, too; an increase in c drives the growth of w . The simultaneous increase of these two parameters indicates an increase in the share of effectively used innovation space and the overall innovation activity growth. With a multi- directional change of c and  , the dynamics w is determined by the dynamics of the relationship c / . An important advantage of using the of stochastic frontier concept under model (5) parameters c and  estimation is their stability in relation to the characteristics of innovation passive regions. The value of the parameter c of the model (5) depends on the method of evaluating the size of innovation space and may be considered as a scaling option with regard to the size of ~ innovation space. An estimate wi of innovation space share used by a region is relative, as it depends on parameter c and technical efficiency estimate TEi which is also a relative charac- ~ teristic of a region. However, the dynamics of estimates wi reflects a change in both innovation ~ activity and the size of innovation space. The estimates wi of the innovation space share used by regions of the Russian Federation under the creation of new production technologies for the period 2009-2013 and the analysis of the factors affecting their dynamics are presented in the research paper by Aivazian, Afanasiev (2015). The verification of Hypothesis 3 testing evidences that the dependence of the innovation activity results on the size of the innovation space for the subjects of the Russian Federation

2 Estimate TEi for a region, whose technical efficiency in the use of innovation space equals one 22

Sergey Ayvazyan, and Mikhail Afanasyev / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 7-27 and the US states is described by a generic model M1 (see Table 12). In Fig. 7a across the x- axis to the vertical line 80 subjects of the Russian Federation are distributed according to the classification adopted by the Rosstat (see, for example, Razrabotannyye..., 2013). After the vertical lines 51 states of the USA in alphabetical order are displayed (see, for example, Number of Patents..., 2014). The axis of ordinates on a logarithmic scale shows the values of the innovation space size in these regions. Among the 6 regions with the largest size of the innovation space from the total number of subjects of the Russian Federation and states of the USA by the 2010 data are the two subjects of the Russian Federation, i.e. Moscow and Saint Petersburg. At that, the innovation space size of Moscow exceeds the size of the innovation space of any of the US state. In Fig. 7b across the x-axis the subjects of the Russian Federation (before the vertical line) and the US states (after the vertical line) are arrayed in the same way as in Fig. 7a. Y-axis for each region displays the number of patents issued using a logarithmic scale. The maximum number of patents issued is in the state of California. The second biggest region in the number of patents issued is Moscow. Among the 15 regions the next highest in the number of patents issued is Saint Petersburg.

Figure 7a. The size of innovation space Figure 7b. The number of patents issued on a logarithmic scale on a logarithmic scale 20 12 18 16 10 14 8 12 10 6 8 6 4 4 2 2 0 0 0 20406080100120140 0 20 40 60 80 100 120 140

Figure 7c. The estimates of technical efficiency of innovation space on a logarithmic scale 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0.0 0 20406080100120140

The size of the innovation space of the US states on the average significantly exceeds the one of the RF subjects (Fig. 7a). The number of patents issued in the United States significantly exceeds the number of patents granted to the RF subjects (Fig. 7b). However, the estimates of technical efficiency in the use of innovation space by the majority of the Russian Federation subjects are comparable to respective estimates of the US states. In Fig. 7b across the x-axis the subjects of the Russian Federation (before the vertical line) and the US states (after the

Sergey Ayvazyan, and Mikhail Afanasyev / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 7-27 vertical line) are arrayed in the same way as in Fig. 7a. Y-axis for each region displays the technical efficiency estimate TEi . Among the 13 most efficient regions there are 3 subjects of the Russian Federation (Ivanovo, Kursk and Ulyanovsk oblasts) and 10 US states (Idaho, Vermont, Washington, Connecticut, Rhode Island, Oregon, Delaware, New Hampshire, New Jersey and Massachusetts). Among the 25 most efficient regions there are 12 regions of Russia and 13 states of the USA. For the majority of subjects of the Russian Federation the results of INNOVA- TION ACTIVITY to the same degree correlate to the innovation space size as for the US states. If under evaluation of the parameters of model (5) for the totality of 131 regions we use the underestimation of the size of innovation space V i  hei i * inn i of Russian Federation subjects, among the 13 most efficient regions are the 7 subjects of the Russian Federation (Ivanovo, Kursk, Ulyanovsk, Penza, Kaluga, Saratov and Tomsk oblasts) and 6 US states (Idaho, Vermont, Washington, Connecticut, Rhode Island and Oregon). However, when comparing the technical efficiency estimates we should take into account that patent regulations of the Rus- sian Federation and the United States are different. Moreover, patenting activity in the US exhib- its a wider range of participants, apart from high-tech companies. Therefore, the estimates of the size of innovation space of the US states are too low, and the estimates of innovation space technical efficiency are inflated, respectively. Yet, these estimates were obtained using the official statistics information, and thus can serve as a basis for identifying the factors of innovation space technical efficiency.

Property 3. The elasticity of innovation activity result by the size of innovation space reflects the possibility of enhancement of innovation system at the regional and national levels through extensive development of business, education and science.

Under the elasticity  the change in the number of innovation active businesses in a region i at gi % and in the number of organizations engaged in R&D (higher education institutions) at qi % drives a  (gi  qi )% variance in the innovation activity result. For such innovation activity outcomes as the number of patents issued and the number of new production technologies the elasticity estimates exceed 0.5 and range from 0.5 to 0.65. Therefore, the increase in the number of research organizations in a region by 1% and the number of innovation active businesses by 1% should be accompanied by the regional innovation activity growth by more than 1%.

6. CONCLUSIONS The number of organizations creating new knowledge, as a characteristic of the region’s research potential and the number of innovation active enterprises as a characteristic of business success affect the overall result of innovation activity of the Russian Federation subjects, i.e. the number of production technologies developed and the number of patents issued. The results of innovation activity in the regions of the Russian Federation depend on the size of the innovation space, which is determined by the number of potential pairwise relationships between organizations, creating new knowledge, and innovation active businesses. The parameters of the function describing the dependence of the number of patents issued on the size of innovation space used by the Russian Federation subjects, estimated by the number of organizations engaged in R&D and innovation active businesses do not differ significantly from the parameters of the function governing the relationships between the number of patents issued and the size of innovation space of the US states, measured by the number of higher education institutions and high-tech companies.

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For the majority of the Russian Federation subjects the results of innovation activity to the same extent correlate to the size of innovation space as of for the US states. For such subjects of the Russian Federation the estimates of innovation space technical efficiency are close to the respective technical efficiency estimates of the US states. A method of estimating the size of the innovation space for the subjects of the Russian Federation (subject to the number of higher education institutions, or the number of organizations engaged in R&D) and for the US states (with regard to the number of high-tech companies, or the total number of firms) has no significant effect on the estimates of the elasticity of innovation activity results by the size of innovation space and their dynamics. The elasticity of innovation activity result by the size of innovation space reflects the possibility of enhancement of innovation system at the regional level through extensive development of business, education and science. The current reform of the education system of the Russian Federation is aimed at consoli- dation of higher education institutions and is carried out through universities mergers. The reform of the Russian Academy of Sciences also suggests incorporation or alliance of academic institutions. In conditions of economic crisis it is hardly likely this reduction would be offset by an increase in the number of innovation active businesses. Therefore, one can expect a reduction in the size of innovation space at the regional level and, as a consequence, a decline in innovation activity results. The limitation of this research is that the above models do not account for specific features and the intensity of interaction between individual research organizations and businesses. Un- der the innovation space reduction the results of innovation activity can still show a growth trend by enhancing the intensity of interaction between particular actors. However, such variant of innovation system development can be defined as optimistic. Given the above research findings a more realistic option is the one when the reduction in innovation space would apparently affect the decline in innovation activity of the Russian Federation subjects. Implementation of the strategy of development against the background of reduction of the innovation space might challenge targeted investments that exceed the cost of maintenance of the achieved size of innovation space if the current number of research organizations and higher education institutions is retained. Based on the results obtained it can be concluded that the increase in innovation activity of the Russian Federation subjects assumes that state and regional governments would create the environment facilitating the expansion of regional innovation space through new research organizations and higher education institutions start-ups, increase of overall innovation activity of businesses.

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„All business establishments: Census Bureau, the Business Information Tracking Series“ (2014), Science and Engineering Indicators 2014, Table 8-53, High-technology establishments as a percentage of all business establishments, by state: 2003-2010 URL: http:// www.nsf.gov/statistics/seind14/index.cfm/state-data/download.htm (accessed January 2016). Battese, Coelli (1988), „Prediction of Firm-level Technical Efficiencies with a Generalized Fron- tier Production Function and Panel Data“, Journal of Econometrics, Vol. 38, 387-399. Freeman, C. (1987), Technology Policy and Economic Performance: lessons from Japan, Pinter, London. „High-technology establishments“ (2014), Census Bureau, the Business Information Tracking Series (various years), Science and Engineering Indicators 2014, Table 8-53, High- technology establishments as a percentage of all business establishments, by state: 2003- 2010, URL: http://www.nsf.gov/statistics/seind14/index.cfm/state-data/download.htm (accessed January 2016). Kumbhakar, S., Lovell, K. (2004), Stochastic Frontier Analysis, Cambridge U.P. „Number of Patents Granted as Distributed by Year of Patent Grant: U.S. U.S. Patent and Trademark Office“ (2014), A Patent Technology Monitoring Team Report, (December, 2014) URL: http://www.uspto.gov/web/offices/ac/ido/oeip/taf/cst_all.htm (accessed January 2016). Number of institutions (2010), „U.S. National Center for Education Statistics, Digest of Educa- tion Statistics“, annual. URL: http://www.nces.ed.gov/programs/digest (accessed January 2016).

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Montenegrin Journal of Economics

Vol. 12, No. 2 (2016), 29-44

‘

Relationships Between Investment Effectiveness Controlling and Business Performance

Rastislav Rajnoha1, Petr Novák2, and Martina Merková3

1 Assoc. prof. Rastislav Rajnoha, PhD., Tomas Bata University in Zlín, Faculty of Management and Economics, T. G. Masaryka 5555, 760 01 Zlín, Czech Republic, E-mail: [email protected] 2 Ing. Petr Novák, PhD., Tomas Bata University in Zlín, Faculty of Management and Economics, T. G. Masaryka 5555, 760 01 Zlín, Czech Republic, E-mail:[email protected] 3 Ing. Martina Merková, PhD., Technical University in Zvolen, Faculty of Wood Sciences and Technology, T. G. Ma- saryka 24, 960 53 Zvolen, Slovak Republic E-mail: [email protected]

ARTICLE INFO ABSTRACT Received March 22, 2016 We focused on business performance in companies and in scope of Received in revised form - investment measurement and management we analyse using of Accepted May 30, 2016 investment effectiveness evaluation methods. Goal of our research Available online June 15, 2016 at first was to detect what investment valuation methods apply companies in Slovakia in their management and what determinants JEL classification: cause it. Consequently, the aim was to find out if using of certain investment valuation method or some valuation approach consisted M21, F21, G30 from several methods, has the positive impact into business performance. Analysed data were collected trough questionnaire. We DOI: defined several hypotheses and decided to apply two kinds of statis- 10.14254/1800-5845.2016/12-1/1 tical methods appropriate for tested variables. Results of the research confirmed some assumptions and we state that use of in- Keywords: vestment valuation methods is limited by foreign ownership of company and certain methods caused better business performance. Investment Controlling, Investment Effectiveness, Foreing Capital, Business Performance, Break-Even Analysis, Cost Analysis

1. INTRODUCTION For qualified and correct answer how to achieve the higher efficiency and economic effectiveness of business, it is firstly necessary to determine what is the current and real business performance, and which appropriate and objective indicators use to measure this performance. The collected information, obtained values of the indicators are important factors for decision making about future investment in companies. Insufficient domestic capital has been shown in the process of transformation in post-communist countries and a possible solution of this problem appeared the foreign direct investment. Therefore it is necessary to additionally increase efficiency of the investment activity in order to achieve set economic goals, especially reducing of unemployment (Piplica & Speranda, 2015).

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FDI brings for the country and its businesses more significant effects. Innovation activities play an important role in economic growth and can be considered as the engine of economies. It is argued that a dependency between innovation activities and economy performance exists and the relationship of these two indicators is considered (Juřičková & Novák, 2015). Based on the scientific conclusions and previous research results, in which we have shown the positive effects of the FDI at the level of macro environment, we then hypothesized certain influence of foreign firms in microeconomics. We tested if companies with foreign capital are per- forming better and what is typical for them against local firms. We interested in investment effectiveness controlling and investment valuation methods used in companies. Aim was to analyze determinants what cause the use of the investment effectiveness valuation methods and to find out certain methods with possitive effect in better business performance. Significant results of our research we publish in this paper.

2. LITERATURE REVIEW In scope of measuring the businesses performance it can be concluded that the economic experience quite often realizes the financial management based on the accounting profit and common indicators such as profitability or activity ratios. These indicators are presently considered as insufficient, which is also one of the reasons for the significantly poor competitiveness of enterprises. Traditional methods of measuring business performance (for example in Kislin- gerová, 2010 and others) are based primarily to maximize profits (which is also in line with the objectives of business activity). To measuring the performance are used absolute and relative indicators (Brealey & Myers, 2002; Kislingerová, 2010 or others). However, in recent years can be seen objections to the traditional performance measurement indicators such as profitability. INFA performance indicator diagnostic system (Neumaier & Neumaierová, 2002), used at the Ministry of Industry and Trade of the Czech Republic, works with the managerial face of economic profit, which compares the ROE and the alternative cost of equity (Neumaier & Neu- maierová, 2014). Recent research at the microeconomic level aimed at businesses in various industries in Slovakia (Rajnoha et al., 2013) was focused on both - traditional key indicators such as accounting profit, value added, wages and labor productivity as well as non-traditional way of performance measuring. Business performance in mentioned research was expressed by the ROE indicator. Company managers utilize a number of concepts for the management of performance including Balanced Scorecard (BSC), Economic Value Added, benchmarking and many others (Knápková, Pavelková & Jirčiková, 2010). Petera, Wagner & Menšík (2012) deal with performance measurement and management systems with focus on BSC and they found statistically significant difference between BSC adopters and BSC non-adopters as for utilization of Activity Based Management. One of the conditions to maintain the competitiveness and performance of the company is the ability to work properly and timely with information not only about past and present but also especially about the future (Rajnoha et al., 2014). Business activities are significantly determined by the environment of the company, which forces firm to use a particular method of behavior, as well as to use the choice of particular business goals and ways of achieving them. In this context, a very important role is played by social environment and political and legal environment that is created by the state authorities. It is assumable that a positive perception of these companies by their environment could stimulate their financial performance and accelerate the positive influences of these companies on the whole society (Belás, Bilan, Demjan & Sipko, 2015). Other similar research based on a questionnaire survey obtained from the 91 companies from Czech Republic. This is one of the few studies which investigate the relationship between management tools and techniques and organizational performance. The study indicates that there is a positive significant relationship between management tools and techniques utilization and organizational performance (Afonina, 2015). On the other hand, some studies analyse using of tools without positive impact into business per-

Rastislav Rajnoha, Petr Novák, and Martina Merková / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 29-44 formance. Research in Romania, where sample consisted of 73 multinational companies, investigated lingage between corporate social performance and financial performance. Authors according statistical analysis results state, that improving of CSR does not necessarily lead to better financial performance (Miron & Petrache, 2012). Next research in Germany interprets, that due to some significant correlations between innovations and financial and quality performance it is not possible to provide a clear statement about the impact of innovations on the performance (Heurich & Vignali, 2015). The importance of these problems has significantly increased during the economic crisis, because many enterprises in the world reduced their performance. According to Belás et al. (2014) average performance of small and medium enterprises de- creased by 15.80% in the Czech Republic and 18.78% in Slovakia at this time. Several studies and analyses dealing with FDI issues worldwide generally finds a significantly positive relation between FDI and economic growth. FDI by multinational corporations plays an important role in the transformation of former centrally planned economies into vibrant market systems, since it provides an inflow of capital, management skills, and jobs, alongside increasing exports and transfer of technology (Chidlow, Salciuviene & Young, 2009). Consider- ing given localization of our research and existing literature from this region, authors Pavlínek and Smith (1998) in their research deal with FDI in the Czech and Slovak Republics. Pavlínek (2008) discussed about advantages of foreign ownership for Czech enterprises, such as access to investment capital, access to sale and distribution networks of parent companies and technology transfer. Positive impact of FDI in Slovakia demonstrated authors Merková, Drábek & Jelačić, 2012). Another research realized in Slovakia has statistically confirmed that better business performance is significantly dependent on financing from foreign capital (Merková, Rajnoha & Dobrovič, 2015). Rugraff (2007) focused on the efficiency of the Central European countries' FDI policies by evaluating the spillover effects of FDI. His comparison demonstrated that for the creation of competitive indigenous firms has been more efficient the model built on strong state intervention in the industrial structure and in industrial guidance of FDI than the model totally banned policies constraining FDI. Companies with higher level of implementation of corporate governance principles have higher net profit margin and earnings per share (To- dorovič, 2013). There are several approaches how to valuate economic effectiveness of investment and which methods or indicators are used in companies. The most frequently mentioned methods in theory are Net Present Value and Internal Rate of Return (e.g. Levy & Sarnat, 1986; Khan, 1993; Brealey & Myers, 2002; Drábek & Polách, 2008 etc.) considering the discount rate. Dis- counted cash flow valuation is based on expected future cash flows and discount rates. While discounted cash flow valuation is only one of the three ways of approaching valuation, it is the foundation on which all other valuation approaches are built (Damodaran, 2012). Brealey & Myers (2002) also deal with often used indicators Return on Investment or Return on Equity, but these methods do not take into account the time factor. Cost criteria (discounted cost method) commonly used in manufacture industries (Popesko, 2010) compare different technical and production alternatives of investments, and their goal is not maximizing the benefits, but estimating the parameters, which the investment has to fulfill (Tuček, Tučková & Zámečník, 2009). Cost management is one of the most important issue of company performance and company financial management. Also the issue of the costing systems, methods and techniques is one of the important features of cost management and management accounting (Novák & Popesko, 2014). Knowing how costs change as activity output changes is an essential part of planning, controlling, and decision making (Hansen, 2009). How underline Banker and Chen (2006) understanding cost behaviour is one of the most important aspects of profit analysis for managers. The experience of a corporate practice, analys is of variable and fixed costs and their solution is dealt with in most companies by the controlling department. Some of companies notices the causes of the cost remanence but it is not them able to predict. In the context of the emergence of cost behavior and cost remanence are growing much faster, these costs are not analyzed and are allocated without a difference to individual groups performances 31

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(Novák & Popesko, 2014). Each company usually sets its own methods, criteria, which are the most acceptable and which enable right investment decision making, according to their own point of view considering investment effectiveness and suitability.

3. OBJECTIVES AND METHODOLOGY

3.1 Research objective and hypotheses The aim of the research in the first step was to analyze relevant determinants for using of the investment effectiveness valuation methods. We think that in different companies, whether domestic or foreign, different sizes, operating in different business and so on there are significant differences in the management and evaluation of investment effectiveness. Used methods of investment valuation can then affect the actual effectiveness of investments and thus also the overall performance of the company. Our primary research goal is therefore to analyze in statistically significant sample of businesses using of certain investment evaluation methods and also identify the key methods that have a positive impact on the overall business performance. Subsequently, based on statistical analysis, we tried to find out a method or group of methods for evaluation of investments, the use of which significantly affects better business performance based on the Return on Equity indicator (ROE). The essence of the research was to analyze the performance categories that companies achieved with using of certain methods. In relation to the research objective we set the following hypotheses: H 1: Annual indicators for ivestment effectiveness valuation, due to the expected highest frequencies of use of these methods, statistically influence the business performance. However, we expect to be typical for the moderate level of performance. H 2: Use of discounted cash-flow indicators has a significant impact on business performance and we expressed the assumption that these methods are applied in companies that achieve a moderate or higher ROE. H 3: Methods based on investment controlling evaluation significantly influence business performance and they are typical in companies achieving the highest performance with ROE of over 7%. H 4: Additional method of break-even analysis is used in companies with better business performance.

In order to test the statistical hypotheses, the basic (null) hypothesis H0, an alternative hypothesis H1 with a significance level α we formulated. The aim was to challenge the validity of the hypothesis H0. The alternative hypothesis H1 represented the opposite to the basic hypothesis.  Null hypothesis: There is no relationship between tested method and business performance.  Alternative hypothesis: There is a contingency between tested method and business performance.

The decision to accept or eventually to reject the H0 was carried out as follows:

α < p, H0 cannot be rejected, α ≥ p, H0 is rejected in favour of H1. The level of significance was set as α = 0.05.

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3.2 Research questionnaire and sample There was created on-line questionnaire through internet application to build data collection of companies in Slovakia. In total 1.457 chosen businesses were asked to participate in the survey, representing selected industry segments in Slovakia. Data about the primary database of 1.457 enterprises from selected industries of the Slo- vak Republic we received from information of various industrial associations and those we have subsequently supplemented by other companies on the basis of extensive online survey. The questionnaire was distributed in two consecutive rounds. First via e-mail (time for completion was two months, low latency – there were completed only 45 research questionnaires), subsequently we are therefore used in the second round the form of telephone and the most common form of face-to-face interview (time for completion was next two months, there were filled other 119 research questionnaires). After these two consecutive rounds the questionnaires were correctly completed by 164 enterprises in the end. Relatively low return stemmed mainly from the reluctance of businesses, their negative mood and scepticism from economic development, lack of time, lack of interest and so on. Nevertheless, we consider the size of the research sample – 164 enterprises as being sufficiently representative and this is 11.26% share of the total number of companies surveyed. The initial data set consisted of all the surveyed firms (164 enterprises), out of which we created sets specifically aimed at firms from the industries of wood processing, engineering and automotive industry. A separate set containing all the enterprises from the three industries was also studied. The final two sets are defined by their core business (focus) – manufacturing, the last set also includes enterprises of trade and services. Table 1 presents the data from the research sets. In terms of size of company across the whole survey sample, the medium-sized (51-250 employees) and large enterprises (over 250 employees) formed 40.3% share. Small businesses (11-50 employees) accounted for 29.8% share. Micro sized to 10 employees accounted for 29.9% share of the survey sample. From that perspective the research sample was balanced and contained uniform representation of all size categories. Regarding the parameter origin of foreign capital in companies in Slovakia, whole research sample consisted from 17 various answers. We used optimal binning of classes in this variable and we created 4 classes. Countries were sorted according most counts: 120 firms of domestic origin, 27 firms in group of other foreign origin (21 firms of 15 concrete foreign countries and 6 firms from unnamed foreign country), 10 firms from Germany and 7 from Czech Republic.

Table 1. Basic data on the data sets analysed

Set The industry focus Totals Set 1 All industries 164 firms Set 2 Wood Processing Industry 34 firms Set 3 Mechanical engineering 30 firms Set 4 Automotive industry 16 firms Selected industries (Wood processing industry, Engineering, Automo- Set 5 80 firms tive) Set 6 Production companies 106 firms Set 7 Trade and Services 58 firms

Data source: own

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3.3 Statistical methods used in the research We have used mathematical and statistical methods focusing on two-dimensional inductive statistics in the research of interdependencies and impacts of individual factors on achieved performance of companies. The research consisted from qualitative – nominal variables the association between variables we examined with contingency. We applied chi-squared test, which is commonly used for testing the independence between two categorical variables (Pearson, 1904; Everitt, 1977; Pánik, 2005 and others). Results of chi-squared tests describe selected statistics: Pearson’s chi-square and significance p-value „p“, Pearson’s contingency coefficient (CC) and Adjusted contingency coefficient (Adj. CC).

Pearson’s Chi-square: ; while (1) Pearson’s contingency coefficient CC: (2)

Maximum contingency coefficient CCmax: (3) Adjusted contingency coefficient Adj. CC: ; while (4)

Where: – observed frequency in an field of the table, – expected (theoretical) frequency in an field of the table, k – number of cells in the table N – sample size q – number of rows or columns (in square tables)

Table 2. Maximum values of contingency coefficient for square tables

Number of rows or columns 2 3 4 5 6 7 8 CCmax 0.707 0.816 0.866 0.894 0.913 0.926 0.935

Data source: Clauss & Ebner (1988)

Pearson's contingency coefficient may occur in different maximum values depending on the number of categories for the studied variables. Clauss & Ebner (1988) report the maximum values for square tables, CCmax for rectangular tables can be roughly estimated by averaging the maximum values for square tables. In our paper we publish only the results of tables 2x2 and 3x2. From Table 2 we use CCmax for 2x2 tables, which is 0.707, CCmax for combination of 3 columns and 2 rows we calculated (see Formula 3) value CCmax 0.762. For clear interpretation and relevant comparisons of the contingency coefficients of several analyzes we calculated adjusted contingency coefficient (Adj. CC), which takes into account the calculated CC and the corresponding CCmax (see Formula 4). That ranges from 0 to 1, values close to 1 mean a stronger dependence of two variables. The only assumption underlying the use of the Chi-square (other than random selection of the sample) is that the expected frequencies are not very small. The 2x2 tables would be the value of the expected frequency for each cell being in a table greater than 5. When the expected cell frequencies fall below 5, those probabilities cannot be estimated with sufficient precision. For larger tables, compliance of this condition is often problematic. The result is inac- curate approximation of the test characteristics of the chi-square probability distribution. How- ever, according to Finkelstein & Levin (2001), for tables larger than 2x2 it is recommended to 34

Rastislav Rajnoha, Petr Novák, and Martina Merková / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 29-44 have at least 80% of the expected frequency of greater than 5 or not the expected frequency of less than 1 in more than 10 % of cases. We also applied analysis of variance (ANOVA) in the research. The purpose of ANOVA (Shapiro & Wilk, 1965; Iversen & Norpoth, 1976 and others) is to test differences in means (for groups or variables) for statistical significance. Assumptions of ANOVA are:  Normality - the normal probability distribution with mean equal to zero.  Homogeneity of variances - the variances are equal for all values.  The individuals are independent - observations in groups are different objects. For testing of homogeneity of variances we used Levene´s test. Levene's test (Levene et al., 1960) is an inferential statistic used to assess the equality of variances for a variable calculated for two or more groups. If the resulting p-value of Levene's test is less than significance level (0.05), the null hypothesis of equal variances is rejected and it is concluded that there is a difference between the variances in the sample. For statistical analysis, numeric and graphical presentation of the research results, we used the program MS Office Excel and Statistic software from StatSoft, Inc.

4. RESULTS

4.1 Determinants of use of investment effectiveness valuation methods Research of determinants whose influence using of investment valuation methods analyzed following factors (basic selecting questions no. 1-10 in the questionnaire): Industry, Re- gion of country, Legal form, Age of company, Ownership (domestic or foreign), Origin of foreign capital, Size of company (number of employees), Type of activity, Type of production (if), Value of turnover. Finally, from all tested factors only foreign ownership as a determinant of use of investment valuation methods proved several statistically significant dependences. Relationship between variables foreign ownership and use of concrete method or group of indicators we present in Table 3.

Table 3. Contingency: Foreign ownership vs. Use of investment valuation methods – Statistics

Foreign ownership x Counts Pearson’s df p Contingency Adjusted Use of investment valuation methods chi- coefficient CC (Adj. square (CC) CC) Use of annual indicators 164 2.524 1 0.112 0.12 0.17 - profit comparison (profit maximization) 164 4.186 1 0.041 0.16 0.22 - cost comparison (cost minimization) 164 1.264 1 0.261 0.09 0.12 - earnings 164 0.010 1 0.919 0.01 0.01 - payback period 164 2.060 1 0.151 0.11 0.16 - return on investment (ROI) 164 5.823 1 0.016 0.19 0.26 - approximation of earnings 164 1.523 1 0.217 0.10 0.14 Use of discounted cash flow valuation 164 9.508 1 0.002 0.23 0.33 - Net present value (NPV) 164 1.051 1 0.305 0.08 0.11 - Profitability index (PI) 164 3.186 1 0.074 0.14 0.20 - Internal rate of return (IRR) 164 1.459 1 0.227 0.09 0.13

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Foreign ownership x Counts Pearson’s df p Contingency Adjusted Use of investment valuation methods chi- coefficient CC (Adj. square (CC) CC) - Payback period (PP) 164 4.141 1 0.420 0.16 0.22 Use of investment controlling methods 164 7.698 1 0.006 0.21 0.30 Use of additional methods: 164 1.607 1 0.205 0.10 0.14 - break-even analysis 164 0.486 1 0.486 0.05 0.08 - project commercial life cycle 164 1.198 1 0.274 0.09 0.12

Data Source: authors

We asked about four types of methods in questionnaire section aimed in investment valuation indicators and we can say main results in four groups of methods. Annual indicators without time value of money (profit, cash flow, cost, earnings, payback period and return on investment) was the first group. The research demonstrated the statistically significant relationship between foreign firms and use of the ROI indicator. In the second group were long-term indicators considering time value and cost of capital, it means methods based on discounted values (net present value, internal rate of return, profitability index and discounted payback period). In analysis of individual methods does not exist any association, but generally, use of discounted cash flow methods is statistically significant and typical for foreign firms. The third group covered methods used in investment controlling (modified internal rate of return and net final value) and the results are similar like in the second group, for individual method no one relationship (low counts), but use of controlling methods and foreign companies means significant contingency. The last group contained additional indicators for support decision-making (break- even point and others). There was not found out any significance. Considering the separate types of methods we can summarize, that the research demonstrated the statistically significant relationship between foreign owned firms and:  Use of the profit comparison (profit maximization)  Use of the ROI indicator  Use of discounted cash flow methods  Use of investment controlling methods Presented results of dependence between foreign owned firms and use of investment effectiveness valuation methods suggest comprehensive approach of foreign firms in investment measurement and management.

4.2 Influence of investment evaluation methods in business performance In analysis of investment effectiveness evaluation methods companies could choose op- tional number of responses and identify one or more methods or group of methods for investment evaluation (defined in theoretical part of this paper). Each method were surveyed as a binary variable, but we also analyzed certain group of methods to determine if their use has an impact on business performance. Business performance in this analysis was categorized into three groups. Obtained results are presented in

Table 4.

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Table 4. Contingency: Use of investment valuation methods vs. Business Performance – Statis- tics

Investment valuation methods x Counts Pearson’s df p Contingency Adjusted Business Performance chi-square coefficient CC (Adj. (CC) CC) Use of annual indicators: 164 3.816 2 0.148 0.15 0.20 - profit 164 1.067 2 0.587 0.08 0.11 - cost 164 1.608 2 0.448 0.10 0.13 - earnings 164 1.323 2 0.516 0.09 0.12 - payback period 164 4.797 2 0.091 0.17 0.22 - return on investment (ROI) 164 0.480 2 0.786 0.05 0.07 - approximation of earnings 164 2.831 2 0.243 0.13 0.17 Use of discounted cash flow evaluation: 164 4.530 2 0.104 0.16 0.22 - Net present value (NPV) 164 1.323 2 0.516 0.09 0.12 - Profitability index (PI) 164 6.470 2 0.039 0.19 0.26 - Internal rate of return (IRR) 164 6.349 2 0.042 0.19 0.25 - Payback period (PP) 164 1.054 2 0.590 0.08 0.10 Use of investment controlling evaluation 164 4.244 2 0.120 0.16 0.21 Use of additional methods: 164 0.776 2 0.678 0.07 0.09 - break-even analysis 164 1.980 2 0.372 0.11 0.14 - project commercial life cycle 164 2.229 2 0.328 0.12 0.15

Data source: authors

In the research of the first group of methods between business performance and annual indicators (individual method or whole group of methods), the use of annual indicators has not statistically significant effect on the business performance, so we did not confirmed the general purpose of the first hypothesis H1. When we analysed the second group of methods, in the research of discounted cash-flow indicators, we demonstrated statistically significant relationships between performance and two indicators: Profitability Index and Internal Rate of Return. Both pursued relationships show moderate dependence with similar Adj. CC at 0.26 (and 0.25 respectively). The analysis of observed frequencies presented in histograms (Figure 1 and Figure 2), but especially residuals show that if companies do not use specified evaluation method, they obtain poor performance with negative or very low positive ROE to 2%. When they use the mentioned methods, the differences between observed and expected frequencies are significant for the second and third group of performance (positive ROE above 2%), residuals are slightly higher for the second performance group (ROE 2-7%). So, we cannot say, that with application of these methods companies have extremely high performance; probability to result with the ROE indicator at the level of 2% or 10% is the same. But it is sure that without analyzed methods companies are very weak with the ROE under 2%.

Rastislav Rajnoha, Petr Novák, and Martina Merková / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 29-44

Figure 1. Use of PI method vs. Business Performance

Without use of PI method Use of PI method Histogram of Performance 70 Histogram of Performance 66; 48% 14 13; 48% 60 12 50 48; 35% 10 40 8; 30% 8 30 6; 22% 23; 17% 6 20

Use of PI method PI of Use 4 10 2 Without use of PI method PI of use Without 0 Group 1: Low Performance Group 2: Middle Performance Group 3: High Performance 0 Group 1: Low Performance Group 3: High Performance Performance Group 2: Middle Performance Performance Data source: authors

Figure 2. Use of IRR method vs. Business Performance

Without use of IRR method Use of IRR method Histogram of Performance Histogram of Performance 80 10 70; 47% 9; 60% 70 8 60 52; 35% 50 6

40 4; 27% No ofobs

No ofobs No 4 30 27; 18%

20 2; 13% 2 10

0 0 Group 1: Low Performance Group 3: High Performance Group 1: Low Performance Group 3: High Performance Group 2: Middle Performance Group 2: Middle Performance Performance Performance Data source: authors

Use of discounted cash flow methods thus resulted in higher performance than without the use of methods, but does not guarantee placement in the highest categories of ROE, on which are likely to have significant impact controlling methods. However, it is possible to confirm the hypothesis H2. In the third group of investment effectiveness valuation indicators we focused on methods based on investment controlling approach. We specified two controlling methods in questionnaire and it would be suitable to analyse each one separately, but there were very low observed frequencies insufficient for statistical testing by using any statistical method. We decided to analyse not each method, but two controlling methods together as variable “use of investment controlling”, while it was not important which method the company uses. In this variable we selected two categories: without use and use of investment controlling approach. In variable business performance according the ROE indicator we started with 6 groups (categories). However, the statistical analysis did not record p-value p<0.05 for this distribution. We were forced to join the groups of performance, that of the original six groups were created two, with limit ROE was 4%. Analysis of dependence between investment controlling methods and performance of businesses recorded in this case p-value of p<0.05. Detailed statistical results of chi-square test presents Table 5.

Rastislav Rajnoha, Petr Novák, and Martina Merková / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 29-44

Table 5. Contingency: Use of investment controlling evaluation vs. Business Performance – Sta- tistics

Investment controlling valuation x Counts Pearson’s df p Contingency co- Adjusted CC Business Performance chi-square efficient (CC) (Adj. CC) Use of investment controlling 164 4.276149 1 0.038 0.159 0.22 evaluation

Data source: authors

Due to the unfulfilled assumptions of expected frequencies was not appropriate to interpret the values of contingency coefficients or residual frequencies in contingency tables. However, the results of the p-value have led us to the decision to examine further the use of investment controlling evaluation methods and performance by statistical analysis, which would offer sufficient evidence of a statistically significant dependence of variables. We used analysis of variance. Statistical characteristics of the use of investment controlling evaluation presents Table 6, demonstrated impact on performance we display in Figure 3.

Figure 3. Use of investment controlling evaluation vs. Business Performance

Categ. Box & Whisker Plot 5

3 Performance groups (ROE) groups Performance 2

1 Mean NO YES Mean±SE Use of investment controlling evaluation Mean±1,96*SE

Data source: authors

Rastislav Rajnoha, Petr Novák, and Martina Merková / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 29-44

Table 6. Analysis of variance: Use of investment controlling evaluation vs. Business Perform- ance

Levene´s test of homogeneity of variances Use of investment SS - df - df - controlling evalua- MS- Effect SS - Error MS- Error F p Effect Effect Error tion Performance 0.34595 133.377 0.82331 1 0.345959 162 0.4202 0.5177 (ROE) 9 6 9 Analysis of variance (ANOVA) Use of investment df - df - controlling evalua- SS - Effect MS- Effect SS - Error MS- Error F p Effect Error tion Performance 0.036 10.50136 1 10.50136 380.8889 162 2.351166 4.4664 (ROE) 0 Statistics: Performance (ROE) Use of investment Performance Confidence Confidence Performance Performance (ROE) controlling evalua- (ROE) - Means -95.000% +95.000% (ROE) - N – Std.Dev. tion No 2.000000 1.755382 2.244618 155 1.541630 Yes 3.111111 2.062475 4.159748 9 1.364225 All categories 2.060976 1.822044 2.299907 164 1.549570

Data Source: authors

The analysis of the use of investment controlling methods reveals that Levene´s test determined the p-value p>0.05, whereby we did not reject the null hypothesis of equal variances; assumption for ANOVA test was fulfilled. In the ANOVA test, p-value was p<0.05 (0.036), we can reject null hypothesis H3 in favour of alternative hypothesis and thus demonstrate the statistically significant dependence of performance in relation to analysed methodology. Use of investment controlling evaluation methods as a tool of investment measurement we consider as significant factor with the impact into better business performance.

4.3 Relations in tested research areas Based on the results of statistical analysis we had constructed a model of relations between the research parameters, we visualized our statement to the results of testing hypotheses. This model, shown in three general steps, presents impact of foreign owned firms in use of investment valuation methods together with influence to better performance (see Figure 4). Based on statistical results we have made the decision on the hypothesis formulated at the beginning of the study:

H 1: We do not reject null hypothesis H0. We did not confirmed the statistically significant relationship between the use of annual indicators for ivestment effectiveness valuation and business performance. H 2: We reject null hypothesis H0 in favour of alternative H1. Use of discounted cash-flow indicators has statistically significant impact on business performance. We proved that these methods are applied in companies that achieve moderate or higher performance. H 3: We reject null hypothesis H0 in favour of alternative H1. Dependence of business performance on using of investment controlling valuation was statistically proven. However, companies applying this tool of investment measurement and management reach the ROE indicator more than 4%, not more than 7% as we expected. H 4: We do not reject null hypothesis H0. We did not confirme that use of additional method of break-even analysis has a significant effect into better business performance.

Rastislav Rajnoha, Petr Novák, and Martina Merková / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 29-44

Figure 4. Confirmation of research hypotheses

Determinants of use of investment evaluation methods

Confirmed: Not confirmed: ‐ Industry, Foreign ownership ‐ Region of country, ‐ Legal form, ‐ Age of company, ‐ Origin of foreign capital, ‐ Size of company (number of employees), ‐ Type of activity, ‐ Type of production (if), ‐ Value of turnover. Investment effectiveness evaluation methods Annual indicators Discounted cash flow valuation Controlling methods Additional methods (e.g., turnover, cost, (e.g. NPV, PI, IRR, PP) (e.g. final value method, (e.g. break‐even analysis) Profit, ROI) modified IRR) 1st hypothesis: 2nd hypothesis: 3rd hypothesis: 4th hypothesis: not confirmed confirmed confirmed not confirmed

Business performance (ROE)

Data source: authors

5. DISCUSSION Almost a third of businesses do not use any method of evaluating the efficiency of investment (Rajnoha et al., 2013). It is possible to assume, that if a company which still does not use any method for assessing the effectiveness of investment, chooses some concept of evaluation of investment plans, it will be more applying annual indicators, only very limited use of discounted cash flow methods, certainly not once more dificult approach based on investment controlling. Results of our research can improve businesses in Slovakia and increase their performance, regarding the application of investment effectiveness controlling. Recommendations are primarily directed to domestic firms that use concepts and tools of investment management and measurement in minimum level. Just companies with using of some basic and simple investment valuation approach would be interested in useful findings in this article. Most businesses apply annual indicator Return on investments (ROI) or methods based on discounted cash-flow. According to research results (Rajnoha et al., 2013), 38% of companies in our research sample use methods based on discounted cash-flow, but using of these methods only leads to a moderate business performance and . Precisely for this reason it is necessary to look for something that will bring greater efficiency and therefore enterprises should to their investment measurement and management also implement investment controlling. Furthermore, it was proven (Merková, Rajnoha & Dobrovič, 2015), the investment controlling apply entities with partial or full foreign ownership. The research also confirmed that companies with foreign ownership obtain better performance, according ROE indicator more than 4%. We can therefore assume that the use of investment controlling approach is still associated with the entry of foreign investors to the company in Slovakia and with bringing of certain elements of knowledge base. Domestic firms do not use the method of investment controlling for several reasons. At first, they have no interest to implement new conceptions in management,

Rastislav Rajnoha, Petr Novák, and Martina Merková / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 29-44 because they do not see the sure effects. Second, they do not understand and trust the methods of investment controlling. Third, they have lack of capital; if they invest, it is tangible investments - technology, machinery - investment in direct connection in production, not in management. The hypothesis set at the beginning of the research assumed that the use of investment controlling cause business performance, more than 7% in ROE indicator. ANOVA test showed that companies achieved 4th and higher performance group, which means border of performance over 4% ROE. It is questionable whether such performance for businesses is enough. Rather, we purpose that if a company incurs finances to implementation of an investment controlling, they expect more. We realise that our results have limitations and future research requires some gudlines and recommendations. The first, valuation of the overall business performance according the ROE indicator can be distorting; and also due to the results achieved, we will in our further research consider using the indicator Earnings before interests, taxes and depreciation and amor- tization (EBITDA). Second, it would be more appropriate to realize the study in the longer term, since it is generally known that investments bringing higher profitability after certain time. So, in our research, they did not have yet to fully reflect in business performance measured by ROE indicator. Eventually, it would be suitable to extend the research sample, primarily of the other companies with foreign capital and MNEs, to conclude the statistically more relevant research findings.

6. CONCLUSIONS Presented research results based on statistical testing as well as from discussion show that some tools of investment measurement and management and applying of certain investment effectiveness valuation methods is typical for foreign owned firms. Furthermore, some of these methods has positive impact into business performance. Comprehensive approach of investment effectiveness valuation in foreign firms, influencing better business performance, covers the ROI indicator, long-term indicators based on discounted cash flows and methods used in investment controlling. Findings from our research based on the statistical testing can benefit businesses in the Slovak economy, in terms of the investment controlling application. Inadequate concepts in investment management and controlling may be the reason of insufficient performance of domestic companies. We can therefore assume that the use of investment controlling approach is still associated with the entry of foreign investors to the company in Slovakia and with bringing of certain elements of knowledge base.

Acknowledgment This paper is the partial result of the Ministry of Education of Slovak Republic grant project VEGA Nr. 1/0537/16 - Methods and models of Strategic Business Performance Management and their comparison in companies and multinational corporations. This paper is one of the research outputs of the project GA 14-21654P/P403 “Variability of Cost Groups and Its Projection in the Costing Systems of Manufacturing Enterprises” registered at the Czech Science Foundation.

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Łukasz Klimczak / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 45-60

Montenegrin Journal of Economics

Vol. 12, No. 2 (2016), 45-60 ‘

Trade Liberalisation and Export Performance of the Western Balkans1

Łukasz Klimczak2

1 The research project was financed by means of the National Science Centre of Poland (Narodowe Centrum Nauki) granted upon decision number DEC-2013/11/N/HS4/03642. Author would like to thank Mr. Sławomir Śmiech (PhD) from the Cracow University of Economics and an anonymous Reviewer for helpful comments. 2 Cracow University of Economics, ul. Rakowicka 27, Kraków, [email protected]

ARTICLE INFO ABSTRACT Received February 25, 2016 Despite the seeming obviousness of an impact of trade liberalisa- Received in revised – June 06, 2016 tion on trade values, there are substantial differences in results of Accepted May 29, 2016 empirical studies in that field. Thus, the aim of this research was to Available online June 10, 2016 measure the influence of trade liberalisation processes on export performance of the Western Balkan countries (Albania, Bosnia and JEL classification: Herzegovina, Croatia, FYR Macedonia, Montenegro and Serbia) in years 2001 - 2014. For this purpose, an imperfect substitutes mod- F12, F14, C23 el of trade was employed. It explained the value of export with the DOI: World GDP, real effective exchange rate, weighted average tariff rate and stock of FDI. This demand model was further extended by 10.14254/1800-5845.2016/12-1/3 adding different supply-type variables in order to capture differences in production capacities of the analysed countries. It was Keywords: estimated twofold: as pooled data with OLS and as fixed effects trade liberalisation, model. The results were contrary to expectations. Trade liberalisa- export, tion influenced export values to a very small extent. Expectedly, imperfect substitutes model, external demand played a crucial role, as well as additional, supply- Western Balkans, type variables. Foreign direct investments also influenced export weighted average tariff rate positively. Finally, big internal market, if proxied by population, not GDP, seemed to restrain local producers from selling abroad.

1. INTRODUCTION An impact of trade liberalisation on trade values seems obvious and intuitive. Removing barriers to trade is supposed to result in its growth. However, empirical works in this field bring diverse findings. Thus, the main purpose of this paper is to investigate if and to what extent trade liberalisation processes, that have been taking place in the Western Balkan countries in the new millennium, influenced their export performance. Review of literature doesn’t give an unique opinion on what to expect. Most of the pre-liberalisation studies anticipated trade growth

Łukasz Klimczak / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 45-60 that was supposed to emerge as a result of regional economic integration processes (see for instance Busier et al., 2005; Herderschee and Qiao, 2007). However, others claimed that regional trade was close to potential, thus lowering barriers wasn’t supposed to cause its significant increase (Damijan et al., 2006). Ex-post analysis of liberalisation show its strong (Peterski 2013; Pllaha, 2012) or relatively strong (Klimczak, 2014; Trivić and Klimczak, 2015) positive influence on trade. The region of the Western Balkans3 was chosen as a research object, because of the processes of trade liberalisation and economic integration that have been taking place in extraordi- nary economic and political circumstances. They were preceded by a highly unstable period of the 1990s, in which the peoples of the region suffered not only from warfare, but also from a significant decrease in industry output. On the other hand, negative effects of barriers to trade appeared in parallel with emergence of borders between countries that previously formed one country – Yugoslavia. Unlike the above cited papers, in this study the imperfect substitutes model of trade was employed. This theory-based approach underlines the importance of the demand-driven factors, which have their strongest impact in short and medium term analysis4. Trade liberalisation was proxied by weighted average tariff rate. As a proxy for product quality level, foreign direct investments stock was added to the model (see Penkova-Pearson, 2011 for similar approach). The study was extended by adding three different supply-type variables to this demand model of trade, in order to capture differences in production capacities of the analysed countries. Con- trolling for changes in supply in the imperfect substitutes models seems to be especially important in the case of studies that encompass relatively long periods (thirteen years in our case), because adjustments in supply take place only in a long run (see Barteczko, Przystupa, 2006). The remainder of this paper is structured as follows. After Introduction, in part two the main trade liberalisation processes in the Western Balkans were outlined. In part three, methodological aspects were highlighted and values of the main variables presented. In part four, results were displayed and discussed. The fifth part brought additional supply-type variables to the model. Its standard version was than tested for robustness in part six, which was followed by the main conclusions5.

2. TRADE LIBERALISATION IN THE WESTERN BALKANS Since the breakdown of the Socialist Federal Republic of Yugoslavia (SFRY) the newly evolved countries experienced profound changes of economic, political and sociological type. Among them, trade liberalisation processes seemed to play a significant role. They have been carried out in four main directions:  Stabilisation and Association Process (SAP),  bilateral free trade agreements,  CEFTA-2006 and  World Trade Organisation (WTO).

3 The Western Balkan region geographically covers Albania and majority of the countries that emerged after the breakdown of the SFR Yugoslavia: Bosnia and Herzegovina, Croatia, Montenegro, Serbia and FYR of Macedonia. Due to lack of comparable data Kosovo was not taken into account in this analysis. 4 Although according to Bobić (2010), the model serves well also in the long run. 5 This article is an extended and up-dated version of the paper presented during the IV REDETE Conference, Graz, Austria, October 2015 46

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As the conflict in Kosovo ended, in 1999 the European Union (EU) has begun the so- called Stabilisation and Association Process, which encompassed five countries of the South- Eastern Europe (SEE)6. The participants committed themselves to adjust their institutions and procedures to the standards of the EU and to gradually decrease barriers to trade. In return, the European Union offered apart from financial support, also free access to the common market and perspective of a membership (Kaminski, de le Rocha 2003). The SAP required from the participating countries an engagement in a regional co-operation, among others in an economic field (Pjerotić, 2008, p. 498). For this reason, the Western Balkan countries as well as Romania, Bulgaria and Moldova, signed on June 27th, 2001 an EU-supported document called Memorandum of Understanding on Trade Liberalization and Facilitation (MoU). The document obliged them to sign until the end of 2002 bilateral free trade agreements with one another and to follow the World Trade Organi- sation rules in this respect. For the countries of the former Yugoslavia the bilateral agreements were an important step towards liberalisation of trade, which used to be completely free, before the collapse of TFR Yugoslavia. However, the bilateral agreements constituted a complicated network, often referred to as “spaghetti bowl”. Partly for the sake of simplicity, in December 2006 the WB countries together with Moldova signed the Central European Free Trade Agree- ment, which since then was re-called CEFTA-2006 (see Gressani, Mitra, 2002, pp. 14-15)7. The aims of the Agreement reached beyond typical goals of FTAs, as defined in the GATT article XXIV, because they encompassed (Miklaszewski, 2005, p.6; Molendowski, 2007, p. 95; Molen- dowski, 2012, p. 98):  facilitating development of economic relations by promotion of trade;  ensuring fair trade practices among the signatories;  contributing to the harmonious development of the World trade. However, it is important to notice, that at the beginning there was no consensus about a full trade liberalisation. Thus, the pace of the agreed trade liberalisation was relatively slow, taking into account an eight-year period of reaching fully liberalised trade. On the other hand, non-discriminatory trade liberalisation has taken the form of joining the World Trade Organisation. All countries of the region took an effort to negotiate the conditions of becoming members of this organisation, with all consequences of liberalising trade outside of the FTAs. Apart from Bosnia and Herzegovina and Serbia, who are “in progress toward membership”, all other Western Balkan countries are currently members of the WTO8. All these liberalisation processes resulted in a significant decrease in tariff barriers, as presented in Table A1 and in Graph 1. The values of weighted average tariff rate in 2001 varied from less than 5% to almost 12%. Thirteen years later, the values ranged just from ca. 1% to 2%. The most significant drop of tariff barriers was reported by Albania, which changed its position from the most closed, to the most open economy among the WB countries (if measured by an average tariff rate). In a contrary, the smallest changes were reported by Bosnia and Herze- govina (data for Croatia and Serbia awere not available for 2014 at the time when the analysis was done).

6 Albania, Bosnia and Herzegovina, Croatia, FYR Macedonia and Serbia and Montenegro 7 The initial CEFTA agreement was signed in Dec. 21st, 1992, by Poland, Hungary, Czech Rep. and Slovakia. 8 The article was submitted in February 2016. Kosovo wasn’t at that time taking part in the WTO-accession process. 47

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Graph 1. Weighted average tariff rates in the Western Balkan countries in period 2001-2014.

Note: A part of the missing data were linearly interpolated. Source: http://unctadstat.unctad.org/EN/, accessed: 01.10.2015.

This significant drop in weighted average tariff rates can be associated with trade liberalisation processes that were taking place in the region of the Western Balkans.

3. METHODOLOGY & DATA A question arose, how did those trade liberalisation processes influence export performance of the Western Balkan economies? The choice of the proper econometric model should result from an analysis of types of goods being traded (Mroczek, Rubaszek 2003). As countries of the Western Balkan region specialise in export of differentiated more than homogeneous products9, the appropriate model describing their export seems to be the imperfect substitutes model. The models of perfect and imperfect substitutes presented by M. Goldstein and M. Khan (1985) account for a complementary concept. The value of a country’s export is explained especially with the World demand for exported goods. The possibility of substitution between domestic and imported good is in this case a discriminant enabling to choose between both models. In the case of the perfect substitutes, simultaneous export and import of the same type of goods does not take place. One country can be either an exporter or an importer of a certain good. This can be associated with trade with homogenous products, which implies limited practical application, as majority of products are differentiated. In reality, substitution of products is usually limited, which means that a country can be simultaneously exporter and importer of the same type of goods. The ground for such a case is the consumers’ preference for product variation as a means of utility enhancement. In this event, the imperfect substitutes model is in use10 (see Mroczek, Rubaszek 2003).

9 Even though in 2013 SITC section [333] “Petroleum oils, oils from bitumin. materials, crude” constituted as much as 28.1 % of Albania’s exports, and section [334] “Petroleum oils or bituminous minerals > 70 % oil” constituted 10.2 % of Croatia’s export. 10 The imperfect substitutes model is used as an empirical approach i.a. by the Croatian National Bank (see Bobić 2010), National Bank of Albania (see Hoda 2011), National Bank of Poland (see Mroczek, Rubaszek 2003), Bulgar- 48

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Assumptions of the imperfect substitutes model imply, that the value of export is in general a function of:

 external demand, which is usually proxied by the World GDP, and  competitiveness of domestic goods abroad, which is proxied by real effective exchange rate (REER). The latter one is calculated by correcting nominal exchange rate courses with the difference in levels of inflation and it takes into account shares of certain partners in the total export value of the reporting country. REER shows changes in purchasing power of the local currency and reflects competitiveness of domestic goods on the international market. In the utilised model, external demand and competitiveness were modified by:  quality of exported goods, which was proxied by the stock of the foreign direct invest- ment11, and  effects of trade liberalisation, which was proxied by the weighted average tariff rate. The model was constructed as a power function which enabled to interpret estimated values of coefficients as elasticities.

(1) where: - export of country i in year t - World GDP in year t - real effective exchange rate of country i in year t - stock of foreign direct investment in country i in year t - weighted average tariff rate in country i in year t a, b, c, d - coefficients - error term.

The model was first log-linearized. The shape of the graph of the dependent variable suggested testing for stationarity (see Graph 2). Indeed, Levin-Lin-Chu test proved non-stationary character of the data. In order to deal with this problem, two alternative approaches were tested: - a time trend was added to the log-linearized model; - the initial log-linearized model was converted to first-differences12. In both cases, the dependent variable showed stationary character. The log-linearized model with a time trend was then estimated twofold:  as pooled data with OLS,  as a fixed-effects model.

The research encompassed five (or six, after the year 2006) Western Balkan countries: Al- bania, Bosnia and Herzegovina, Croatia, TFYR Macedonia and Serbia and Montenegro, in years 2001-201413. Kosovo was not taken into account due to lack of comparable data.

ian National Bank (see Penkova-Pearson 2011) and The Foreign Trade Research Institute of Poland (see Barteczko, Przystupa, 2006). 11 This approach was taken by Penkova-Pearson (2011). 12 This approach is presented in the “Robustness check” part of the paper. 49

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In the period 2001-2014 the value of export (the dependent variable) showed a similar trend in almost all of the analysed countries (Graph 2)14. After its significant increase in years 2001-2008, a one-year sharp drop occurred in 2009, which was probably caused by the World economic crisis. This short downturn was followed by five years of a recovery. In a consequence, in all of the countries except Croatia and Montenegro the value of export in 2014 was higher than before the crisis, in 2008.

Graph 2. Export (million USD)

Source: http://unctadstat.unctad.org/EN/, accessed: 01.12.2015.

Graph 3. World GDP (billion USD, constant prices)

Source: http://unctadstat.unctad.org/EN/, accessed: 01.12.2015.

13 For econometric purposes, Serbia and Montenegro after 2006 were in this model still treated as a one country. Values of export and FDI stock of Montenegro after 2006 were added to the corresponding values of Serbia. The values of the two other variables (REER and WATR) after 2006 were taken just of Serbia. 14 Values of all variables apart from WATR, were presented in Table A3. 50

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Similarly to the export variable, also the World GDP (Graph 3), which represented external demand, underwent an upward trend until 2008. Then, after a one-year drop, the growth continued until the end of the examined period. Expectedly, similarity of trends resulted in a relatively high positive correlation of 0.56 between export and the World GDP (see Table A2).

Changes of the real effective exchange rate shown on Graph 4. were not easy to interpret. Very high short-term changes of the REER were recorded in the case of the FYR Macedonia and Croatia, but they were both anticipated and followed by relative stabilisation of the level of this variable. A lack of data occurred in case of:  Serbia (and Montenegro) in years 2001 – 2003 and 2006 – 2007, and  Bosnia and Hercegovina in years 2001 – 2004.

Real effective exchange rate, reflecting price competitiveness of domestic goods abroad, showed positive correlation with export (0.15), but the coefficient of variation was relatively small (0.056).

Graph 4. Real effective exchange rate

Source: http://unctadstat.unctad.org/EN/, accessed: 01.12.2015.

The stock of foreign direct investment, which was the last of the explanatory variables (Graph 5), was characterised by an upward trend in almost all countries and in almost all periods. The main exception was Croatia, which recorded a sharp decrease in 2008. In the following years the level of the FDI stock was stable. Although this variable was highly correlated with export (0.96), causality cannot be assumed due to various ways of possible interactions between FDI and export. The relation depends on the type of the FDI, as horizontal investments may restrain trade, whereas vertical ones may facilitate it, especially with the investing country (Camarero and Tamarit, 2003). Regarding the region of the South-Eastern Europe, Mehić and Babić-Hodović (2011) found positive and statistically important influence of the FDI on exports of the SEEs, which was in a contrary to results of Estrin and Uvalic (2013).

Łukasz Klimczak / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 45-60

Graph 5. Stock of the FDI (million USD, at current prices and current exchange rates)

Source: http://unctadstat.unctad.org/EN/, accessed: 01.12.2015.

4. ESTIMATION RESULTS At the beginning the panel data model was estimated twofold: as pooled data with OLS and as a fixed-effects model, in both cases with a time trend variable. In case of each of the estimation types, a very high explanatory power was attained – the values of the adjusted R-squared amounted to 0.92 and 0.99 respectively. In case of the majority of coefficients they appeared to have expected signs (see Table 1). External demand, proxied by the World GDP, only in the pooled model had a negative sign (-0.92), the coefficient was statistically not significant, though. In the fixed effects model the sign was positive (5.15) and the coefficient was statistically significant. This goes in line with findings of V. Bobić (2010) and confirms the assumption of the imperfect substitutes theory, that external demand plays an important role in countries’ export. Similarly, the signs of the REER coefficients, proxying competitiveness of domestic products abroad, were positive. The values, which ranged just from 0.13 to 0.25, were not high, and in both models they were statistically insignificant. When commenting these results it must be noticed, that according to Đozović and Pripužić (2013), REER as a measure of price competitiveness produces more exact results when data are disaggregated into industry levels. The stock of the FDI, which was the third explanatory variable, appeared to have a positive and relatively strong influence on export. The values of its coefficients ranged from 0.33 to 0.79 and in both types of the model they were statistically significant, which confirmed findings of Mehić and Babić-Hodović (2011). However, they were in a contrary to the results of Estrin and Uvalic (2013) who argue that inflow of the FDI to the SEEs didn’t stimulate their export growth. Finally, the values of the coefficients standing by the WATR variable took expectedly negative, but very low values (from -0.05 to -0.01). In both models they were statistically insignificant. The fact that the influence of the lowered tariff barriers on export was so limited was a surprising outcome of this research. Taking into account findings of Klimczak (2014) and Trivić and Klimczak (2015), who argued that trade liberalisation had relatively strong influence on trade within the region of the Western Balkans, one can conclude that those intra-regional ef-

Łukasz Klimczak / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 45-60 fects of trade liberalisation were higher than the effects for trade with further-located coun- tries15.

Table 1. Estimation results POOLED – OLS FIXED EFFECTS Estimation type (time trend) (time trend) 10.13 -50.43*** const (21.91) (11.44) -0.92 5.15*** GDP (2.07) (1.10) 0.25 0.13 REER (0.16) (0.08) 0.79*** 0.33*** FDI (0.04) (0.05) -0.01 -0.05 WATR (0.05) (0.03) 0.01 -0.07** time (0.05) 0.03

No. of observations: 70 70 R-squared: 0.922352 0.985521 Adjusted R-squared: 0.916287 0.983350

Notice: ***, ** and * indicate significance 1, 5 and 10 per cent levels accordingly. Source: Own calculations

A test for differing group intercepts suggested that the model with fixed effects was more appropriate. On the other hand, a model with random effects could not be estimated due to insufficient degrees of freedom for regression.

5. SUPPLY FACTORS IN A DEMAND MODEL There is a big difference between a standard imperfect substitutes models for one country and for more countries. In the latter case, the standard panel data model doesn’t anyhow capture differences in production outputs or potential of the reporting countries. This shortcoming is partly addressed by including country-fixed effects. Just partly, because these effects encompass all country-specific factors, not only production potential. For this reason they can be treated as the so-called multilateral resistance of a country.

In order to control for production potential of each of the analysed countries, additional supply-type variables were added to the model:

- GDP, proxying supply potential of an economy, - GDP per capita, proxying quality level of exported goods and - population, proxying supply of labour factor.

15 For effects of trade liberalisation in the Western Balkans seen from the different stakeholders’ perspective (consumer, producer, government), see Holzner 2004. 53

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Introducing them should inform about importance of trade determinants when supply side is controlled for.

Table 3. Estimaton results with additional supply-type variables

FIXED EFFECTS FIXED EFFECTS FIXED EFFECTS Estimation type (time trend) (time trend) (time trend) -54.94*** -56.44*** -46.29*** const (8.75) (8.40) (13.40) 4.07*** 4.29*** 5.35*** GDP_WORLD (0.86) (0.81) (1.16) 0.05 0.04 0.12 REER (0.06) (0.06) (0.08) 0.14*** 0.08 0.32*** FDI (0.05) (0.05) (0.05) 0.01 0.01 -0.04 WATR (0.03) (0.03) (0.03) -0.05** -0.06*** -0.07*** time (0.02) (0.02) (0.03) 1.86*** - - GDP (0.28) - 2.15*** - GDP pc (0.29) - - -0.75 POP (1.24)

No. of observations: 70 70 70 R-squared: 0.991716 0.992391 0,985610 Adjusted R-squared: 0.990312 0.991101 0,983171

Notice: ***, ** and * indicate significance 1, 5 and 10 per cent levels accordingly. Source: Own calculations

The relatively high values of coefficients standing by GDP (1.86) and GDP per capita (2.15) confirmed the suspicion, that differences in supply potential among countries can influence export values strongly. Especially that countries of the Western Balkans differ significantly not only by size of their economies, but also and especially by richness of their nations. On the other hand, a negative role of population in an absence of any variable controlling for its economic condition, could suggest that in the case of relatively low-income countries (as the WB ones), bigger internal market discourages a part of local producers from seeking their opportunities abroad. The significance of the GDP and GDP per capita variables also confirms the long-run character of changes in supply and an importance of including supply-type variables in the models with a wide time-frame.

6. ROBUSTNESS CHECK The non-stationary character of the initial data was the reason for verifying if the estimation results were robust. Firstly, an alternative approach towards non-stationarity problem was tested. Instead of adding a time trend to the log-linearized data, they were first differentiated. The 54

Łukasz Klimczak / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 45-60 results of the estimation (see Table 4) were not significantly different from the ones of the model with a time-trend. The sign of the REER variable became negative (as expected from theory) and on the other hand, the coefficient standing by the FDI variable lost its significance.

Table 4. Estimation results of the alternative model No.1. (with first differences)

Estimation type POOLED - OLS -0.11*** const (0.03) 8.37*** diff GDP (0.83) -0.04 diff REER (0.06) 0.08 diff FDI (0.06) -0.03 diff WATR (0.02)

No. of observations: 65 R-squared: 0.671935 Adjusted R-squared: 0.650064

Notice: ***, ** and * indicate significance 1, 5 and 10 per cent levels accordingly. Source: Own calculations

In order to verify robustness of the results the model was also tested for presence of influential observations. No outliers were recorded. Another subject worth checking was the reason for big differences in the REER values over time. Untypical shape of the REER curve suggested possibility of existence of leverage points. Indeed, two observations with a leverage point were recorder. After excluding them from the model, estimation of the REER coefficients didn’t show any bigger changes comparing to the standard model in the pooled OLS specification (see Table 5). However, in the fixed-effects model the value of the coefficient was higher and significant.

Table 5. Estimation results of the alternative model No.2 (without leverage points)

POOLED – OLS FIXED EFFECTS Estimation type (time trend) (time trend)

8.30 -58.40*** const (24.95) (11.77) -0.76 5.81*** GDP (2.33) (1.12) 0.28 0.26** REER (0.22) (0.11) 0.79*** 0.33*** FDI (0.05) (0.05) 55

Łukasz Klimczak / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 45-60

-0.01 -0.05** WATR (0.05) (0.03) 0.00 -0.08*** time (0.06) (0.03)

No. of observations: 68 68 R-squared: 0.922347 0.986741 Adjusted R-squared: 0.916085 0.984683

Notice: ***, ** and * indicate significance 1, 5 and 10 per cent levels accordingly. Source: Own calculations

As the missing data problem was encountered in the case of weighted average tariff rates, a number of observations were interpolated or extrapolated. To insure that the model including these interpolated and extrapolated data was robust, an alternative one was tested, in which the missing data were simply omitted. The estimation results are presented in Table 6.

Table 6. Estimation results of the alternative model No.3 (without missing data)

POOLED – OLS FIXED EFFECTS Estimation type (time trend) (time trend) 16.55 -42.55*** const (24.92) (11.95) -1.54 4.41*** GDP (2.36) (1.15) 0.28 0.15* REER (0.19) (0.08) 0.80*** 0.32*** FDI (0.05) (0.05) 0.00 -0.06* WATR (0.06) (0.03) 0.03 -0.05* time (0.06) 0.03

No. of observations: 59 59 R-squared: 0.912872 0.987002 Adjusted R-squared: 0.904653 0.984615

Notice: ***, ** and * indicate significance 1, 5 and 10 per cent levels accordingly. Source: Own calculations

Estimation results of the model with omitted missing observations were quite similar to the one with interpolated and extrapolated data. The main difference was statistical significance of the coefficients standing by REER and WATR variables in the fixed-effects model. Very slightly higher values of (adjusted) R-square statistics in the alternative model suggest that the interpolation wasn’t necessary.

Łukasz Klimczak / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 45-60

7. CONCLUSIONS Although the influence of trade liberalisation on the value of trade seems obvious and intuitive, empirical works help to recognise the real impact. It much depends on the circumstances, especially on pre-liberalisation level of protection measures. In the case of the Western Balkan countries, liberalisation processes that took place in years 2001 – 2014 brought a significant drop in weighed average tariff rates (from 4.6 – 11.5 in 2001, to 0.7 – 2.1 in 2014). Surpris- ingly, it’s influence on trade values appeared to be rather small. One of possible explanations could be that the imperfect substitutes model describes mostly short- and medium-term relations. And this 13-year analysis could well have been affected by changes in supply potential. However, including proxies of supply potential in the model didn’t change the value of the WATR coefficient significantly. The demand from abroad turned out to be the main factor influencing export sales, far outpacing not only trade liberalisation, but also stock of the foreign direct investments. A number of data limitations was faced in the research. A lack of data occurred for weighted average tariff rate and (to small extent) for real effective exchange rate. Interpolation and ex- trapolation of the missing observations of WATR turned out to be an almost meaningless step, though, as the estimated values were very similar to the ones of the model in which missing observations were omitted. Another limitation was the necessity to deal with the split of Serbia and Montenegro in 2006. For econometric purposes they were treated as a one entity in the entire research period. Finally, Kosovo was not taken into account at all, due to a lack of comparable data. The study did not close the subject of an impact of trade liberalisation on trade values in the region of the Western Balkans. Further research should especially broaden the scope of potential trade determinants. Regarding approximation of the notion of “trade liberalisation”, it would be worth exploring, how non-tariff barriers contributed to the observed trends in trade values. On the other hand, a breakdown of data into industry level would produce more precise results. The research brought relatively clear policy implications. It suggested, that trade liberalisation, although positively seen from a political perspective, doesn’t facilitate the overall export performance to a significant extent in a long term. One can suspect, that far more important job should be done in the institutional field. A favourable macro environment should be created in order to enable producers to develop modern and internationally competitive technologies, thus building and extending production capacities of the countries of the Western Balkans.

REFERENCES Barteczko, K., Przystupa, J. (2006), Czynniki określające zmiany strumieni handlu zagranicznego Polski i ekonometryczna prognoza obrotów na lata 2007 – 2009, Instytut Koniunktur i Cen Handlu Zagranicznego, Warszawa. Bobić, V. (2010), “Income and Price Elasticities of Croatian Trade – A Panel Data Approach”, Croatian National Bank, Working Papers W-25, Zagreb, April. Bussière M., Fidrmuc J., Schnatz B. (2005), “Trade Integration of Central and Eastern European Countries: a Lesson from a Gravity Model”, European Central Bank Working Paper Series, No 545. Camarero, M., Tamarit, C. (2003), “Estimating exports and imports demand for manufactured goods: the role of FDI”, European Economy Group, Working Paper, No. 22. Damijan, J., Sousa, J., Lamotte, O. (2006), “The Effect of Trade Liberalization in South-Eastern European Countries”, The Vienna Institute for International Economic Studies Working Pa- per, No 070. 57

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Đozović, D. Pripužić, D.I. (2013), “Industry Specific Real Effective Exchange Rates in Central and Eastern European Countries”, The 8th Young Economists' Seminar to 19th Dubrovnik Economic Conference, June 12. Estrin, S., Uvalic M. (2013), “Foreign direct investment into transition economies: Are the Bal- kans different?”, LSE ‘Europe in Question’ Discussion Paper Series, LEQS Paper No. 64/2013. Goldstein, M., Khan, M. (1985), “Income and price effects in foreign trade”, in Jones, R. and Kenen, P. (Ed.), Handbook of International Economics, chapter XX, Elsevier Science Pub- lishers B.V. Gressani, D., Mitra, S. (2002), “Structural Reforms in Southeastern Europe since the Kosovo Conflict”, World Bank Technical Paper, No. 526, Europe and Central Asia Poverty Reduction and Economic Management Series, The World Bank, Washington. Herderschee J., Qiao Z. (2007), “Impact of Intra-European Trade Agreements, 1990–2005: Policy Implications for the Western Balkans and Ukraine”, International Monetary Fund Working Paper, 07/126. Hoda, B. (2013), “The Role of Exchange Rates inInternational Trade Models: Does the Marshall- Lerner Condition Hold in Albania?”, National Bank of Albania, Working Paper, (13)52. Holzner, M. (2004), “GSIM Measurement of the Costs of Protection in Southeast Europe”, The Vienna Institute for International Economic Studies, June. Kaminski, B., de le Rocha, M. (2003), “Stabilization and Association Process in the Balkans: Integration Opinions and their Assessment”, World Bank Policy Working Paper, No. 3108. Klimczak, Ł. (2014), “The gravity model as a tool for the international trade analysis – a case study of the Western Balkans”, in Proceedings of the 8th Professor Aleksander Zelias Inter- national Conference on Modelling and Forecasting of Socio-Economic Phenomena, May 6– 9, Zakopane, Poland, 67–76. Mehić, E., Babić-Hodović, V. (2011), “Izravna strana ulaganja i trgovina u zemljama Jugoistočne Evrope”, in Trgovina kao pokretač razvoja Srednje i Jugoistočne Europe, 16th November Ekonomski fakultet, Zagreb, 139-155. Miklaszewski, S. (2005), “Próba bilansu dokonań i przyszłość CEFTA w świetle rozszerzenia Unii Europejskiej”, Zeszyty Naukowe Akademii Ekonomicznej w Krakowie, nr 695, Kraków, 5-21. Molendowski, E. (2007), Liberalizacja wymiany handlowej krajów Europy Środkowowschodniej w okresie transformacji ze szczególnym uwzględnieniem doświadczeń krajów CEFTA, Difin, Warszawa. Molendowski, E. (2012), Integracja handlowa nowych państw członkowskich (UE-10), Difin, Warszawa. Mroczek, W., Rubaszek, M. (2003), “Determinanty polskiego handlu zagranicznego”, Materiały i Studia, Narodowy Bank Polski, Nr 161, lipiec, Warszawa. Penkova-Pearson, E. (2011), “Trade, Convergence and Exchange Rate Regime: Evidence from Bulgaria and Romania”, Bulgarian National Bank Discussion Papers, DP/85/2011. Peterski, M. (2013), “Southeastern European Trade Analysis: A Role for Endogenous CEFTA- 2006?”, Emerging Markets Finance and Trade, Vol. 49, Issue 5, 26-44. Pjerotić, L. (2008), “Trade Liberalization in the South East Europe – Effects and Controversial Issues”, Panoeconomicus, Vol. 55, Issue 4, 497-522. Pllaha, A. (2012), “Free Trade Agreements and trade integration among South Eastern Euro- pean countries; Gravity model estimations”, Bank of Albania Working Paper. No 05 (36). Trivić, J., Klimczak, Ł. (2015), “The Determinants of Intra-Regional Trade in the Western Bal- kans”, Zbornik radova Ekonomskog fakulteta u Rijeci, časopis za ekonomsku teoriju i praksu - Proceedings of Rijeka Faculty of Economics, Vol. 33, No. 1, 37-66.

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Appendix 1

Table A1. Weighted average tariff rates in the Western Balkan countries in period 2001-2014.

Country 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Albania 11.5 8.6 8.4 7.5 7.2 6.5 5.8 1.4 4.6 4.6 0.9 0.7 0.7 0.7 Bosnia and Herzegovina 4.9 5.4 5.9 6.4 6.9 7.3 6.1 6.0 2.4 2.2 1.9 1.9 1.9 2.1 Croatia 4.6 4.5 2.0 0.7 0.7 0.7 0.8 0.8 0.9 1.0 1.0 1.0 0.4 0.4 Montenegro ------2.62.7 2.6 2.9 2.4 1.7 1.6 Serbia (and Montene- 5.7 7.8 7.4 6.9 6.4 6.4 6.3 6.3 4.0 3.2 2.6 4.1 5.6 3.5 gro) TFYR of Macedonia 8.3 6.4 6.7 7.1 1.6 3.3 5.2 2.4 2.3 1.5 1.1 1.2 5.6 1.2

Note: Data in italics were interpolated or extrapolated. “-“ denotes not applicable data. Source: http://unctadstat.unctad.org/EN/, accessed: 01.10.2015.

Table A2. Correlation Coefficients

EXP GDP REER FDI WATR 1,0000 0,5627 0,1549 0,9553 -0,5140 EXP . 1,0000 -0,3499 0,6536 -0,5783 GDP . . 1,0000 0,0801 0,1122 REER . . . 1,0000 -0,5654 FDI . . . . 1,0000 WATR

Source: Own calculation

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Table A3. Values of the variables used in the model

Country 2001 20022003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Export (million USD) Albania 305 330447 603 658 793 1078 1355 1088 1550 1948 1968 2332 2431 Bosnia and Herzegovina 1031 1015 1400 1912 2388 3428 4152 5021 3954 4803 5850 5162 5687 5892 Croatia 4666 49046187 8024 8773 10377 12360 14124 10492 11811 13364 12369 12742 13814 Montenegro 617 388 437 628 469 494 446 Serbia (and Montenegro) 1903 2275 2575 3801 5065 7212 9648 10972 8345 9795 11779 11229 14611 14843 TFYR of Macedonia 1155 1116 1363 1673 2041 2401 3356 3953 2692 3351 4455 4015 4267 4934 GDP (billion USD, at constant prices (2005) and constant exchange rates (2005)) World 41660 4254943769 45562 47203 49154 51104 51864 50820 52900 54381 55569 56837 58245 Real Effective Exchange Rate (year 2005 = 100) Albania 94 9591 99 100 115 115 101 96 93 92 92 92 94 Bosnia and Herzegovina 100 88 87 89 88 88 89 88 87 86 Croatia 192 193192 195 100 119 120 108 109 107 105 104 105 104 Serbia (and Montenegro) 231 100 126 119 111 121 113 122 121 TFYR of Macedonia 111 113 115 114 100 265 265 100 100 99 99 100 101 101 FDI stock (million USD, at current prices and current exchange rates) Albania 327 360483 837 1020 1392 2693 2869 3258 3255 4399 4304 3936 4466 Bosnia and Herzegovina 544 942 1561 2286 2302 3203 5397 6103 6936 6709 7099 7440 7787 7383 Croatia 3406 53097402 11133 13332 25943 43584 28415 33537 32273 28398 29333 29911 29761 Montenegro 0 0 4231 4209 4707 5143 4983 Serbia (and Montenegro) 1194 1685 3152 4110 5687 9943 15710 21130 23149 24919 27684 29344 35375 33142 TFYR of Macedonia 916 1217 1632 2193 2087 2764 3747 4132 4525 4351 4678 4863 5489 5140

Source: http://unctadstat.unctad.org/EN/, accessed: 01.12.2015.

Peter Arendas, and Bozena Chovancova / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 61-71

Montenegrin Journal of Economics

Vol. 12, No. 2 (2016), 61-71 ‘

Central and Eastern European Share Markets and the Halloween Effect

Peter Arendas1, and Bozena Chovancova2

1 Ing. Peter Arendas, PhD, Department of Banking and International Finance, Faculty of National Economics University of Economics in Bratislava, Dolnozemska cesta 1, 852 35 Bratislava, E-mail: [email protected] 2 Prof. Ing. Bozena Chovancova, PhD, Department of Banking and International Finance, Faculty of National Eco- nomics, University of Economics in Bratislava, Bratislava, E-mail: [email protected]

ARTICLE INFO ABSTRACT The Halloween effect is one of the best known share market calen- Received February 21, 2016 dar anomalies. It is based on the phenomenon when the summer Received in revised March 10, 2016 period (May – October) returns tend to be lower compared to the Accepted June 13, 2016 winter period (November – April) returns. This paper investigates the Available online June 15, 2016 presence of the Halloween effect on share markets of 12 CEE countries. The results show that although the Halloween effect pattern JEL classification: can be found in the majority of the CEE share markets, it is statisti- G01, G14, G15 cally significant only in the case of Poland and Ukraine. The data also show that the Halloween effect tends to be stronger on mature DOI: share markets of Germany and the USA than on the CEE share markets as a group, however there can be found some exceptions, 10.14254/1800-5845.2016/12-1/4 such as the Ukrainian, Russian and Estonian share markets. In Keywords: most of the cases, the Halloween effect grew stronger after the Central and Eastern Europe (CEE), global financial crisis of 2008 although there are some exceptions such as the Lithuanian and Russian share markets. financial crisis, Halloween effect, seasonal anomaly, stock market

1. INTRODUCTION It is a known fact that various seasonal anomalies occur on the financial markets. Although their existence is in a direct contradiction to the efficient markets theory (Fama, 1965), some of the seasonal anomalies can be tracked several centuries back. One of the best known seasonal anomalies is the Halloween effect. The Halloween effect is based on the phenomenon when winter period returns (November to April) are higher than summer period returns (May – Octo- ber). The Halloween effect is also known as “Sell in May and go away” or “Sell in May and come back after Halloween”. Various researchers came to conclusion that a Halloween effect based investment strategy may generate abnormal returns (see Literature Review).

Peter Arendas, and Bozena Chovancova / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 61-71 Although the Central and Eastern Europe (CEE) region share markets keep on developing, they are still relatively young. Some of the CEE countries are members of the European Union or even members of the European Monetary Union but they are still perceived as emerging markets. A lot of attention has been paid to the development of the CEE financial markets but only relatively small attention has been paid to the CEE share markets regarding seasonal anomalies. This paper is focused on the investigation of the CEE share markets for the presence of the Halloween effect. It also compares the strength of the Halloween effect in the CEE region to the strength of the Halloween effect on mature share markets of Germany and the USA and it analyses the impacts of the 2008 global financial crisis on the Halloween effect pattern in these countries.

2. LITERATURE REVIEW The Halloween effect is one of the best known calendar anomalies, along with the January effect or the Monday effect. A lot of attention has been paid to the calendar anomalies on financial markets, as these anomalies can be used to generate abnormal returns. For example Lakonishok and Smidt (1988) analysed 90 years of Dow Jones Industrial Average data and they discovered persistently anomalous returns around the turn of the week, turn of the month, turn of the year and around holidays. Zhang and Jacobsen (2013) investigated more than 300 years of data from the UK share market and they concluded that various seasonal anomalies can be found over particular time periods, however the strength of the anomalies varies significantly. Dzhabarov and Ziemba (2010) investigated the presence of the January effect, the Halloween effect, the Holiday effect, and the Turn-of-the-month effect, focusing on the small-cap share index Russell 2000 and large-cap share index S&P 500 over the 1993 – 2009 time period. They concluded that the seasonal patterns were stronger in small-cap shares. Gebka, Hudson and Atanasova (2015) came to conclusion that seasonal anomalies in combination with technical analysis are able to generate significant returns with low risk. Some of the authors focused directly on the Halloween effect. For example Bouman and Jacobsen (2002) concluded that the Halloween effect is present on share markets of 36 countries. The results of Bouman and Jacobsen were later confirmed by Andrade, Chcaochharia and Fuerst (2013) who claimed that share returns tend to be about 10 percentage points higher during the November – April than during the May – October period. On the other hand Maberly and Pierce (2004) concluded that the results of Bouman and Jacobsen were driven by the Oc- tober 1987 crash and by the collapse of the Long-Term Capital Management hedge fund and that after adjusting data for these two events, the anomaly is not statistically significant for the U.S. markets. Lean (2011) confirmed the presence of the Halloween effect on share markets in Malaysia, China, India, Japan and Singapore. On the other hand it is important to note also the research of Dichtl and Drobetz (2014) who concluded that a trading strategy based on the Hal- loween effect is unable to outperform significantly. Although most of the authors agree that the Halloween effect does exist or at least did exist at a certain historical period, it is still unknown what is causing its existence. Lucey and Zhao (2008) suppose that the existence of the Halloween effect is related to the existence of the January effect. Hong and Yu (2008) assume that the Halloween effect is caused by the summer vacation period. The investors go for a Holiday and the trading activity falls down. According to Cao and Wei (2005), the Halloween effect is weather related, as investors tend to be more ag- gressive when the weather is colder and more apathetic when the weather is hot. But in the opinion of Jacobsen and Marquering (2008), it is premature to link the Halloween effect to the weather induced mood changes of investors. Another factor that may have an impact on the Halloween effect pattern is the amount of daylight. Kamstra, Kramer and Levi (2003) came to conclusion that the seasonal affective disorder (SAD) has an important impact on share market

Peter Arendas, and Bozena Chovancova / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 61-71 returns, as the share markets tend to perform better during the periods of lower amount of daylight (autumn and winter). Relatively lot of attention has been paid to economies and share markets of the CEE countries lately. For example Tzeng and Tay (2014) analysed the mechanism of transmission of the U.S. subprime crisis and the European sovereign debt crisis to emerging markets, some of the CEE countries included. Tendera-Wlaszczuk and Szymanski (2015) analysed the economic policies of the Visegrad Group countries. Silaghi and Alexa (2015) investigated the sources of economic growth of selected CEE countries over the 1993 – 2008 time period. Belas et al. (2014, 2015, 2015), Sobekova-Majkova et al. (2014), Abrham et al. (2015) and Ekes and Koloszar (2014) studied the environment in the SME segment of selected CEE countries. Also Harumova and Janisova (2014) focused on the healthiness of some of the CEE region companies. Wang, Jiang, Chang and Su (2015) investigated whether the Taylor rule is valid for the CEE countries. Alexy, Ochotnicky and Kacer (2014) analysed the sovereign credit ratings of Slovakia, Czech Republic, Poland and Hungary. Palankai (2015) analysed the perspectives of adoption of the Euro currency in Central Europe. Reboredo, Tiwari and Albulescu (2015) examined the dependence structure between Czech, Hungarian, Polish and Romanian share markets. Galloppo, Pai- manova and Aliano (2015) focused on the transparency and efficiency of the Eastern European share markets. Fedorova and Saleem (2010) analysed the relations between Polish, Hungarian, Russian and Czech share and currency markets. Bota and Ormos (2014) analysed the weak- form efficiency of the CEE share markets. On the other hand only a limited attention has been paid to seasonal anomalies on CEE share markets. Norvaisiene, Stankeviciene and Lakstutiene (2015) investigated the presence of seasonal anomalies on Estonian, Latvian and Lithuanian share markets. Sander and Veider- pass (2013) focused on share markets of the Baltic countries as well and they discovered a strong turn-of-the-year effect. Oprea (2014) analysed four Romanian share indices over the 1998 – 2014 time period and he found no evidence of the Halloween effect. The authors inves- tigating the presence of seasonal anomalies in the CEE region tend to focus on a relatively low number of countries. The aim of this paper is to fill this gap.

3. DATA AND METHODOLOGY As mentioned above, the aim of this paper is to investigate the presence of the Halloween effect on share markets of 12 countries from the CEE region. Although not all of the CEE region countries are included, due to the lack of relevant data, countries covered by this paper generate the vast majority of the CEE region GDP as well as the vast majority of the CEE region share market trading volume. The share markets are represented by the benchmark share indices: BET (Romania), BUX (Hungary), CROBEX (Croatia), OMX Riga (Latvia), OMX Tallinn (Estonia), OMX Vilnius (Lithuania), PX (Czech Republic), RTS (Russia), SAX (Slovakia), SOFIX (Bulgaria), UX (Ukraine), WIG 20 (Poland). The time periods analysed vary significantly (table 1), as the age of the indices differ. The index values were gained from Quandl and Stooq databases.

Table 1: Basic statistics

country share index period analysed number of years Romania BET V. 1998 - IV. 2015 17 Hungary BUX V. 1991 - IV. 2015 24 Croatia CROBEX V. 1998 - IV. 2015 17 Latvia OMX Riga V. 2000 - IV. 2015 15

Peter Arendas, and Bozena Chovancova / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 61-71

Estonia OMX Tallinn V. 2000 - IV. 2015 15 Lithuania OMX Vilnius V. 2000 - IV. 2015 15 Czech Republic PX V. 1994 - IV. 2015 21 Russia RTS V. 1996 - IV. 2015 19 Slovakia SAX V. 1996 - IV. 2015 19 Bulgaria SOFIX V. 2002 - IV. 2015 13 Ukraine UX V. 1998 - IV. 2015 17 Poland WIG 20 V. 1994 - IV. 2015 21

Source: Own processing

As the Halloween effect is based on the assumption that the summer period returns are lower than the winter period returns, every year (12 consecutive months) is divided into two halves. The summer period lasts from May 1 of year x to October 31 of year x. The winter period lasts from November 1 of year x to April 30 of year x+1. As a result, returns for particular time periods are calculated using following formulas:

(1)

(2)

Where: rs is return for the summer period, rw is return for the winter period, x represents the calendar year, POX is October closing price in year x and PAX is April closing price in year x. If there is a Halloween effect present on a particular share market, the average winter period returns must be higher than the average summer period returns. To evaluate whether the differences between summer period and winter period returns are statistically significant, the Two-sample t-tests and Wilcoxon rank sum tests are performed. The Shapiro-Wilk test is used to determine whether the returns come from a normally distributed population. It means whether the parametric Two-sample t-test or the non-parametric Wilcoxon rank sum test is more appropriate for the given dataset. The F-test is used to determine whether the summer and winter period returns have equal variances and whether the Two-sample t-test for equal variances or the Two-sample t-test for unequal variances should be used. This paper investigates whether there is a statistically significant Halloween effect on the CEE share markets and how it compares to the Halloween effect pattern on the mature share markets of Germany (DAX) and the USA (Dow Jones Industrial Average – DJIA). It also investigates whether the Halloween effect pattern has changed after the global financial crisis of 2008 and whether the impact of the crisis has been similar to the mature markets. For this purpose, two 6-year long time periods are analysed. The pre-crisis period lasts from May 2002 to April 2008 and the post-crisis period lasts from May 2009 to April 2015. The pre-crisis and post-crisis percentage of Halloween effect years and the pre-crisis and post-crisis differences between average summer period and winter period returns are compared to evaluate whether the pattern has changed.

Peter Arendas, and Bozena Chovancova / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 61-71 4. RESULTS AND DISCUSSION The data show that there are huge differences between particular CEE share markets. All of the share indices except of BET, OMX Riga and SAX recorded higher winter period returns during more than 50% of years over the investigated time period. At the same time, all of the share indices except of OMX Riga and SOFIX recorded higher average winter than summer period returns. On the other hand in most of the cases, the differences between summer and winter period results are not statistically significant. Table 2 shows results of the parametric Two-sample t-tests and non-parametric Wilcoxon rank sum tests. Result of the more appropriate test for each dataset, based on the results of the Shapiro-Wilk tests, is written in bold. The Halloween effect is statistically significant only in the case of Ukraine (UX) and Poland (WIG 20), at the 5% level of significance. On the other hand it is important to note that in the case of some other countries, e.g. Estonia (OMX Tallinn) or Croatia (CROBEX), the percentage of Halloween effect years as well as the differences between average summer period and winter period returns are high and it is able to assume that the tests were unable to confirm the statistical significance only due to the relatively short time periods and low volumes of data.

Table 2: Halloween effect in the CEE region

Wilcoxon rank average sum- % of Hallow- Two-sample t- average winter sum test (two- mer period een effect test (two-tailed period returns tailed p- returns years p-values) values) BET 9.29% 13.38% 47.06% 0.682530 0.876825 BUX 4.23% 14.13% 58.33% 0.179422 0.148915 CROBEX -2.18% 10.68% 76.47% 0.089467 0.094818 OMX Riga 7.18% 4.59% 46.67% 0.692047 0.851934 OMX Tallinn 1.37% 15.48% 73.33% 0.102072 0.092984 OMX Vilnius 7.32% 9.68% 66.67% 0.810181 0.633364 PX -2.09% 6.16% 66.67% 0.124195 0.115896 RTS 3.08% 25.93% 68.42% 0.083091 0.156792 SAX 1.57% 2.67% 47.37% 0.869976 0.693486 SOFIX 12.85% 7.42% 61.54% 0.660404 0.590258 UX -2.82% 35.31% 82.35% 0.012384 0.021993 WIG 20 -2.69% 10.70% 71.43% 0.033496 0.037954

Source: Own calculations

Data captured by Table 3 show the comparison between the Halloween effect in the CEE region and Halloween effect on mature share markets of Germany and the USA. The presence of the Halloween effect on the German and U.S. share market is investigated over various time periods, so that it can be directly compared to the results from the particular CEE share markets over the same time periods. The results confirm the findings of Swagerman and Novakovic (2010) that the Halloween effect is stronger in developed than in emerging markets. For DAX and DJIA, the Halloween effect was statistically significant over the 1991 – 2015, 1994 – 2015 and 1996 – 2015 time periods. For DAX, the Halloween effect was statistically significant also

Peter Arendas, and Bozena Chovancova / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 61-71 during the 1998 – 2015 time period. Regarding the CEE region, the Halloween effect was statistically significant only in the case of UX and WIG 20, as mentioned above. Over the shorter time periods, the Halloween effect didn’t prove to be statistically significant.

Table 3: Halloween effect in the CEE region – comparison with Germany and the USA

average average % of Hallow- summer statistically winter pe- een effect period re- significant riod returns years turns

BUX 4.23% 14.13% 58.33% no DAX 1991 - 2015 -0.05% 10.83% 75.00% yes DJIA 1.23% 7.49% 75.00% yes PX -2.09% 6.16% 66.67% no WIG 20 -2.69% 10.70% 71.43% yes 1994 - 2015 DAX -0.62% 11.08% 76.19% yes DJIA 0.94% 7.81% 76.19% yes RTS 3.08% 25.93% 68.42% no SAX 1.57% 2.67% 47.37% no 1996 - 2015 DAX -0.67% 11.57% 73.68% yes DJIA 0.19% 7.18% 73.68% yes BET 9.29% 13.38% 47.06% no CROBEX -2.18% 10.68% 76.47% no UX 1998 - 2015 -2.82% 35.31% 82.35% yes DAX -1.65% 9.09% 70.59% yes DJIA -0.64% 5.78% 70.59% no OMX Riga 7.18% 4.59% 46.67% no OMX Tallinn 1.37% 15.48% 73.33% no OMX Vilnius 2000 - 2015 7.32% 9.68% 66.67% no DAX -1.46% 6.99% 66.67% no DJIA -0.34% 4.85% 66.67% no SOFIX 12.85% 7.42% 61.54% no DAX 2002 - 2015 0.75% 8.13% 69.23% no DJIA 0.63% 5.02% 69.23% no

Source: Own calculations

The global financial crisis was a major milestone in the development of global financial markets. Vast fiscal and monetary measures were adopted by governments and central banks around the World to cope with the crisis. The measures have had a major impact on the post- crisis development of financial markets, share markets included. Therefore it is able to assume that also the seasonal anomalies have been affected. Table 4 shows the average summer and 66

Peter Arendas, and Bozena Chovancova / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 61-71 winter period returns and percentage of Halloween effect years during a 6-year pre-crisis period (May 2002 – April 2008) and a 6-year post-crisis period (May 2009 – April 2015). First of all, it is important to note that the statistical tests haven’t proven the statistical significance of the Halloween effect in any one of the cases. But this fact can be attributed to the very short time periods and low number of data points.

Table 4: Halloween effect before and after the global financial crisis of 2008

% of Halloween effect average returns years 2002 - 2007 2009 - 2014 2002 - 2009 - 2007 2014 summer winter summer winter BET 16.67% 50.00% 24.57% 11.14% 5.42% 13.10% BUX 50.00% 50.00% 7.68% 10.93% 5.64% 7.78% CROBEX 66.67% 66.67% 11.38% 11.36% -0.27% 3.64% OMX Riga 50.00% 66.67% 8.04% 10.27% 6.74% 6.22% OMX Tallinn 66.67% 66.67% 7.56% 16.51% 6.84% 16.51% OMX Vilnius 66.67% 50.00% 14.27% 18.55% 16.58% 6.07% PX 66.67% 50.00% 9.99% 13.98% -0.10% 4.26% RTS 66.67% 50.00% 11.60% 22.69% 4.80% 2.99% SAX 33.33% 66.67% 12.17% 17.34% -5.22% 0.83% SOFIX 33.33% 83.33% 37.31% 11.64% -0.01% 8.99% UX 83.33% 50.00% 14.27% 48.00% -4.49% 23.43% WIG 20 50.00% 50.00% 11.05% 5.82% 4.24% 2.49% CEE average 54.17% 58.33% 14.16% 16.52% 3.35% 8.03% DAX 66.67% 66.67% 2.75% 5.79% 3.59% 12.56% DJIA 66.67% 66.67% 2.23% 2.67% 3.66% 10.27%

Source: Own calculations

Data in Table 4 also show that the impacts of the 2008 crisis were different country to country. For example the percentage of Halloween effect years increased rapidly in Romania (BET), Slovakia (SAX) and Bulgaria (SOFIX) after the crisis. A meaningful decline could be seen in the case of Ukraine (UX). Overall, the percentage of Halloween effect years increased in 4 cases, it declined in 4 cases and in 4 cases it remained unchanged. The average percentage of Halloween effect years for the CEE countries increased from 54.17% to 58.33%. In the case of DAX and DJIA it remained unchanged at 66.67%. The average summer period and winter period returns for the pre-crisis and post-crisis periods are captured by Table 4 as well. Figure 1 shows the pre-crisis and post-crisis differences (in percentage points) between average summer period and winter period returns. A negative number means that winter period returns were higher than summer period returns and vice versa. It is able to see again that the development is very different country to country. For example in Romania (BET), the average summer period returns were higher than average winter period returns by 13.43 percentage points during the pre-crisis period and they were by 7.67 percentage points lower during the post-crisis period. On the other hand in Russia (RTS) a 67

Peter Arendas, and Bozena Chovancova / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 61-71 strong Halloween effect (-11.1 percentage points) reversed completely (to 1.8 percentage points). During the pre-crisis period, average summer period returns beaten the average winter period returns in the case of Romania (BET), Croatia (CROBEX), Bulgaria (SOFIX) and Poland (WIG 20). The same claim is valid also for the 2009 – 2015 period but this time for Latvia (OMX Riga), Lithuania (OMX Vilnius), Russia (RTS) and Poland (WIG 20). Overall, the average difference between summer and winter period returns increased from -2.36 to -4.68 percentage points for the 12 CEE share markets. Regarding DAX and DJIA, the Halloween effect strengthened as well, given the growth of the difference between average summer and winter period returns from -3.04 to -8.97 and from -0.43 to -6.61 percentage points respectively.

Figure 1. Pre-crisis and after-crisis differences between average summer and winter period returns (in percentage points)

Source: Own processing

Based on the abovementioned data, it is able to conclude that the Halloween effect pattern strengthened after the global financial crisis. It is in a partial contradiction with Dichtl and Drobetz (2015) who claimed that the Halloween effect weakened or completely disappeared in recent years. Although the Halloween effect was weaker during the 2002 – 2008 period than during the whole longer-term period in most of the cases, its strength increased again during the 2009 – 2015 period. This finding is in line with findings of Zhang and Jacobsen (2013) who investigated more than 300 years of the UK share market data concluding that the strength of the seasonal anomalies changes over time significantly.

5. CONCLUSION The emerging share markets of the CEE region have come a long way since their inception in the 90’s. This paper focused on the investigation of presence of the Halloween effect on CEE share markets. It is able to conclude that the Halloween effect pattern could be seen on various CEE share markets since their inception during the 90’s, however the statistical tests show that only in the case of Poland and Ukraine we can talk about a statistically significant Halloween effect. The comparison of the Halloween effect on the emerging CEE share markets and on the

Peter Arendas, and Bozena Chovancova / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 61-71 mature German and U.S. share markets shows that it is possible to come to a generalised conclusion that the Halloween effect is stronger on the mature markets. However it is important to note that there are huge differences between particular CEE share markets and in the case of countries such as Ukraine, Russia or Estonia, the differences between average summer period and winter period returns are far bigger compared to Germany or the USA. The analysis also shows that the global financial crisis of 2008 had a mixed impact on the Halloween effect pattern in the CEE region. In general, it can be said that the Halloween effect was stronger during the 6-year post-crisis period than during the 6-year pre-crisis period. But once again, huge differences between particular countries can be observed. The biggest ex- tremes can be seen in the case of Romania where the Halloween effect appeared after the crisis and in Russia where a strong pre-crisis Halloween effect disappeared after the crisis. Com- paring the impacts of the crisis on the whole CEE group to the impacts of the crisis on the Ger- man and U.S. share markets it can be said that the crisis resulted into a stronger Halloween effect in all of the three cases, although the Halloween effect pattern was more positively affected in the case Germany and the USA. This paper shows that the Halloween effect can be found also on share markets of the CEE region. It also confirms findings of Zhang and Jacobsen (2013) that the strength of seasonal anomalies changes over time. Also the finding of Swagerman and Novakovic (2010), that the Halloween effect is stronger in developed than in emerging markets, is valid for most of the CEE region share markets.

Acknowledgement This contribution is the result of the project implementation VEGA (1/0124/14) ”The role of financial institutions and capital market in solving problems of the debt crisis in Europe”.

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Vol. 12, No. 2 (2016), 73-88 ‘

A Mid-Term Forecast of Maximum Demand for Electricity in Poland

Jacek Brożyna1, Grzegorz Mentel2, and Beata Szetela3 1 Department of Quantitative Methods, Faculty of Management, Rzeszow University of Technology, Rzeszow, Poland Al. Powstańców Warszawy 8, 35-959 Rzeszów, Poland. Tel: +48-792-395-486, E-mail: [email protected] 2 Department of Quantitative Methods, Faculty of Management, Rzeszow University of Technology, Al. Powstańców Warszawy 8, 35-959 Rzeszów, Poland. Tel: +48-608-59-13-30. E-mail: [email protected] 3 Department of Quantitative Methods, Faculty of Management, Rzeszow University of Technology, Al. Powstańców Warszawy 8, 35-959 Rzeszów, Poland. Tel: +48-502-140-249. E-mail: [email protected]

ARTICLE INFO ABSTRACT Received February 21, 2015 Forecasting of demand for electricity plays an important role in Received in revised March 10 28, 2016 planning of seasonal operations and expansion of power facilities. Accepted Jun2 13, 2016 Power plants must ensure the continuity of supply of energy, without Available online June 15, 2016 producing the excess due to problems associated with its storage, and at the same time they must be prepared for increased demand JEL classification: e.g. during the periods of cold weather. These factors make that energy companies need accurate forecasts, which in the best way G01, G14, G15 will help plan all the processes associated with this activity. In the DOI: article, based on data from the years 2002-2015, the medium-term forecast of electricity demand in Poland until the end of 2017 has 10.14254/1800-5845.2016/12-1/5 been presented. Forecasts have been determined using the exponential smoothing Winters and SARIMA models, and their Keywords: results have been compared with each other and the months, when electricity demand, a rise and a fall for energy demand is predicted, have been quoted. forecasting, seasonality, exponential smoothing, Winters, SARIMA

1. INTRODUCTION Demand for electricity is the amount of energy that must be generated and distributed. Power distribution is not only to provide it to electrical equipment, but also to ensure its continuity, which directly translates into customer satisfaction. Ensuring continuity of energy demand cannot be solved by its excessive overproduction since electricity storage is problematic and expensive. Therefore, its proper forecasting is very important, and thanks to this the outages of electricity and its overproduction will be reduced. From the point of view of electricity producers, the correct forecast of the demand for electricity also allows to plan fuel supplies such as coal or gas. Problems of this type apply to energy systems in every country and region of the world, 73

Jacek Brożyna, Grzegorz Mentel, and Beata Szetela / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 73-88 and is still valid due to the continual development of equipment, of which a significant part requires electrical power. In addition, the update of forecasts forces their nature - the most accurate, i.e. short and mid- term must be based on the most current data. In this publication the energy demand forecasts have been based on the data from the Polish National Energy System (NES) from the years 2002 to 2015, and their horizon covers the period till the end of 2017. The forecasts have been determined on the basis of two models: the exponential smoothing of Winters and SARIMA, which provides greater certainty regarding their relevancy.

2. A REVIEW OF RESEARCH The invention of electricity in the nineteenth century was the revolution that shaped the modern world and the economy (Yergin, 2012) and contributed to the development of many sciences, which had not existed before. Along with the electricity the issues concerning forecasting the demand for it appeared. Scientific approach to forecast the demand for electricity has been conducted for many years (Wilson, 1971; Halvorsen, 1975; Taylor, 1975), and it became particularly important in the 60s of last century, when a very fast growth in electricity consumption started (Smil, 2010). This theme is still up-to-date and it is the object of interest of both practitioners (Piekut, et al., 2012), as well as scientists who use a wide range of forecasting models (Armstrong, 2001; Zhou et al., 2006; Dongxiao, et al., 2010; Balitskiy et al., 2016. Research related to energy requirements apply to each region and country, regardless of its degree of economic development. In case of Poland an article by Maciejewski can be quoted as an example, in which the author in 2007 forecasts of the demand for national electricity until 2012 (Maciejewski, 2007). Ringwood et al., using three different scale (annual, weekly and hourly), forecast domestic demand for electricity in the Republic of Ireland (Ringwood, et al., 2001). Küçükdeniz in his article in 2010, using the SVM model, predicts long-term demand for electricity in Turkey (Küçükdeniz, 2010). An example of forecasts using data from the fastest growing economies in the world, the Chinese economy, is the work by Zhout et al., in which the authors present a trigonometric gray prediction approach by combining the traditional gray model GM (1,1) with the trigonometric residual modification technique (Zhou et al., 2006). Taylor et al., using several different models, compared them with data from Rio de Janeiro, and England and Wales (Taylor et al., 2006). One should not forget about the most developed US economy and cite the works including both forecast ofonly some regions, for example. California (Nowicka-Zagrajek and Weron, 2002); (Wang et al., 2012), New England (Daneshi et al., 2008), as well as the whole country (Pielow et al., 2012). Forecasts can be divided into short (Smith, 2000), medium (Pedregal and Trapero, 2010); (De Gooijer & Hyndman, 2006) and long-term ones, but regardless of the forecast period, they must be considered as guidelines to make certain decisions, not a ready-made solution (Zeliaś, 1997). Forecast horizon does not only mean the period where the values will be forecast, but also, depending on the test object, it has additional meaning and purpose. In the case of medium-term forecasts in the energy sector, this aim is planning of fuel purchase in order to ensure continuity of supply and optimize costs that are associated with the turn of the final price of energy (Nogales et al., 2002); (Karakatsani and Bunn, 2003). In the literature one can find a large number of items describing and comparing different methods of forecasting for energy demand. Cottet & Smith (Cottet and Smith, 2003) have used for this purpose the procedures by Bayes; Blum & Riedmiller (Blum and Riedmiller, 2013) predict energy demand using Gaussian processes, and Dongxiao et al. (Dongxiao et al., 2010) use a support vector machine and ant colony optimization. However, the most popular models used to forecast electricity demand are ARMA / ARIMA / SARIMA models and exponential smoothing, which have been used, among others, in the works (Pappas et al., 2008; Taylor, 2003; Chen, et al., 1995; Lee and Ko, 2011; De Andrade &and da Silva, 2009; Bratu, 2012; Kasperowicz, 2014a,b) and they have been selected in this article to calculate forecasts for the Polish energy system.

Jacek Brożyna, Grzegorz Mentel, and Beata Szetela / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 73-88 3. DISCUSSION OF DATA FROM THE NATIONAL ENERGY SYSTEM IN POLAND Data on the demand for electricity in the National Energy System (NES) in Poland have been downloaded from the website of Polish Power Grid1, where they are given from January 2002 in megawatts [MW] every fifteen minutes. The forecasts in this article will be carried out for two years on a monthly basis and they relate to maximum demand for energy. These factors make that the retrieved data, before making the forecasts, must be appropriately converted into the same form as the forecast data. Thus, the most appropriate cycle in this case is a period of one month for which \ the maximum energy demand needs to be found. Since the collected data refer to the period of January 2002 - December 2015, then by converting the data in this way, it is possible to obtain a sample containing 168 monthly data (Table 1). In addition, to increase the readability, the data has been presented in gigawatts [GW].

Table 1. Energy demand in the National Energy System in Poland [GW]

Month Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2002 22.02 20.24 20.22 18.72 16.55 16.17 15.96 16.96 19.22 20.49 21.22 23.21 2003 23.29 21.71 20.96 20.01 17.06 16.81 16.72 17.23 18.74 21.47 21.77 22.45 2004 22.98 21.91 21.55 20.36 18.05 17.36 17.29 18.32 19.85 21.11 22.46 23.11 2005 22.50 22.29 22.08 19.56 18.48 17.56 17.64 19.00 19.87 21.47 22.95 23.48 2006 24.64 23.12 22.34 20.85 18.76 19.01 19.02 19.59 20.59 21.95 22.89 23.66 2007 23.48 23.31 22.42 21.62 19.66 19.60 19.84 20.28 21.77 23.13 24.44 24.61 2008 25.12 23.19 23.29 21.65 20.18 19.77 19.67 20.43 22.20 22.84 23.77 23.59

Year 2009 24.42 22.93 22.11 20.81 19.03 19.29 19.46 19.78 20.98 22.68 22.96 24.59 2010 25.45 23.76 23.11 21.00 20.62 20.39 20.62 20.34 22.03 22.96 24.60 25.16 2011 24.11 24.66 23.77 21.91 20.86 20.98 20.67 21.14 22.17 23.36 24.48 24.78 2012 25.14 25.84 23.51 22.43 20.66 20.95 21.18 21.07 22.23 23.55 23.87 25.12 2013 24.74 23.69 23.71 22.72 20.69 21.60 21.24 21.33 22.44 23.18 24.58 24.76 2014 25.53 23.93 23.27 22.26 21.16 21.63 21.80 21.25 22.55 23.72 24.69 25.49 2015 25.10 24.31 23.55 23.24 21.39 21.44 22.18 22.30 22.95 23.83 24.87 24.79

Source: Own study

By supporting the graph of so prepared data (Figure 1) the annual seasonality (s = 12) can be observed, the smallest energy demand in summer and the largest in winter. Greater demand for energy in winter can be explained by the shorter day, which results in longer duration of any kind of lighting and lower temperatures which, in turn, affects the need to use heating devices.

1 Polskie Sieci Elektroenergetyczne, http://www.pse.pl/index.php?dzid=77 (04.01.2016r.) 75

Jacek Brożyna, Grzegorz Mentel, and Beata Szetela / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 73-88 Figure 1. Monthly energy demand in the National Energy System in Poland

Power requirements in Poland January 2002 - December 2015 [GW] 16 18 20 22 24 26

2002 2004 2006 2008 2010 2012 2014 2016 Time

Source: Own study

Descriptive statistics of the presented data have been included in Table 2. On their basis one can see significant, reaching 10 GW, differences between the minimum and the maximum energy demand. Considering that the data include fairly short, because only 14-year period, the differences are significant and they indicate a rapid increase in energy demand.

Table 2. Descriptive statistics of the monthly energy demand in the National Energy System in Poland [GW]

N Min. 1stQu. MedianMean 3rdQu. Max. 168 15.96 20.38 21.98 21.76 23.39 25.84

Source: Own study

Jacek Brożyna, Grzegorz Mentel, and Beata Szetela / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 73-88 Figure 2. Boxplot of power requirements in Poland Power requirements in Poland [GW]

16 18 20 22 24 26 Source: Own study

3.1 Models and forecasts A series shown in Figure 1, is of additive nature, which is also confirmed by the graph after the classical decomposition in Figure 3. In this graph seasonal fluctuations with an amplitude of about 2.3 GW are visible, small values of the random component and a clear upward trend with the value of 19.3 GW at the beginning of the year 2002, and 23.4 GW at the end of 2015. The decomposition graph will allow in the next points to adjust better the models of exponential smoothing and ARIMA.

Figure 3. Decomposition of time series of power demand of NES. Decomposition of additive time series observed 16 20 24 trend 20 22 seasonal -2 012 random -1.0 0.0 1.0

2002 2004 2006 2008 2010 2012 2014 2016 Time Source: Own study.

Jacek Brożyna, Grzegorz Mentel, and Beata Szetela / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 73-88 The most commonly used in the literature means to assess the quality of the forecasts are MAE (Mean Absolute Error), RMSE (Root Mean Squared Error), MAPE (Mean Absolute Percentage Error) (Brother, 2012). In this study other measures will be used: ME (Mean Error), MPE (Mean Percentage Error) and MASE (Scaled Mean Absolute Error) (Gardner, 1985).

3.2 Forecast using Winters exponential smoothing model The first model that will be used to forecast the maximum demand for electricity in Poland is a model of exponential smoothing (Hyndman, et al., 2008). The most appropriate model for the series tested will be additive model of Winters ETS (AAA) (Errors = Additive, Trend = Additive, seasonality = Additive) (Winters, 1960) in the form:

(1) (2) (3) where: – the equivalent of the smoothed value obtained from a simple model of exponential smoothing (the average rating) –assessment of the trend growth for the moment or period t-1 –assessment of an indicator of seasonality for the date or the period t-1 r –length of the seasonal cycle - number of phases α, γ, δ –model parameters accepting the values from the range [0 to1] α – parameter characterizing the degree of smoothing is required for all models, δ – parameter of seasonal smoothing and determined only in the case of seasonal choice of models, γ – smoothing parameter of linear and exponential trend.

The equation of the forecast for a moment or period t> n (n - is the number of terms of the series of variable forecast) for the additive alternative of the model:

(4)

The exponential smoothing of such a selected model can be: alpha = 0.5627 beta = 0.0001 gamma = 0.0001

The correctness of the model adjustment to the data has been verified by analyzing the histogram and the graph of quantile residuals (Figure 4), and carrying out further test of normality Shapiro,

Jacek Brożyna, Grzegorz Mentel, and Beata Szetela / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 73-88 Figure 4. The distribution of residuals in Winters ETS(AAA) model Histogram of Residuals Quantile residuals Density Quantile of the test -1.0 -0.5 0.0 0.5 1.0 1.5 0.0 0.2 0.4 0.6

-1.5 -1.0 -0.5 0.0 0.5 1.0 1.5 2.0 -2 -1 0 1 2 Theoretical quantiles

Source: Own study

The p-value of the Shapiro test residuals is 0.2195, so it can be assumed that the distribution of residuals is normal, which allows to determine the point and interval forecast for the confidence levels 0.80 and 0.95. The point and interval forecast for the confidence levels 0.80 and 0.95 for a period of 24 months has been presented in Table 3 and Figure 5.

Table 3. The forecast for energy demand in the National Energy System in Poland for the years 2016-2017 using the exponential smoothing model.

Date Forecast Lo 80 Hi 80 Lo 95 Hi 95 [GW] [GW] [GW] [GW] [GW] Jan 2016 25.39 24.74 26.04 24.40 26.38 Feb 2016 24.42 23.68 25.17 23.28 25.56 Mar 2016 23.77 22.95 24.60 22.51 25.04 Apr 2016 22.44 21.54 23.35 21.06 23.83 May 2016 20.72 19.75 21.70 19.23 22.21 Jun 2016 20.74 19.70 21.78 19.14 22.33 Jul 2016 20.80 19.70 21.91 19.11 22.49 Aug 2016 21.21 20.04 22.37 19.43 22.99 Sep 2016 22.47 21.26 23.69 20.61 24.34 Oct 2016 23.76 22.49 25.03 21.81 25.71 Nov 2016 24.78 23.46 26.11 22.76 26.81 79

Jacek Brożyna, Grzegorz Mentel, and Beata Szetela / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 73-88

Dec 2016 25.44 24.06 26.81 23.34 27.54 Jan 2017 25.66 24.24 27.08 23.49 27.84 Feb 2017 24.70 23.23 26.16 22.45 26.94 Mar 2017 24.05 22.54 25.56 21.74 26.36 Apr 2017 22.72 21.16 24.27 20.34 25.10 May 2017 21.00 19.40 22.59 18.55 23.44 Jun 2017 21.01 19.37 22.65 18.50 23.52 Jul 2017 21.08 19.40 22.76 18.51 23.65 Aug 2017 21.48 19.76 23.20 18.85 24.11 Sep 2017 22.75 20.99 24.51 20.06 25.44 Oct 2017 24.03 22.24 25.83 21.29 26.78 Nov 2017 25.06 23.22 26.89 22.25 27.86 Dec 2017 25.71 23.84 27.58 22.85 28.57

Source: Own study

Figure 5. The forecast for energy demand in the National Energy System in Poland for the years 2016-2017 using the Winters exponential smoothing model

Forecasts from ETS(A,A,A) [GW] 16 18 20 22 24 26 28

2005 2010 2015 Source: Own study

The results of the obtained forecasts have the tendency and fluctuations of the observed series. The errors of such forecasts are: ME -0.0006212085 RMSE 0.5057831000 MAE 0.3947103000 MPE -0.0480970300 MAPE 1.8322730000 MASE 0.6493178000

Jacek Brożyna, Grzegorz Mentel, and Beata Szetela / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 73-88 3.3 Forecast using ARIMA model The second model, which has been used to forecast is the ARIMA model (Asteriou & Hall, 2011) in the seasonal version SARIMA. Models of this type can be applied to stationary series, that is, those in which there are only random fluctuations around the average, or non-stationary brought to stationary ones. As autocorrelation graphs (Figure 6) and partial autocorrelation (Figure 7) show, a series is not stationary and requires additional treatments to meet the requirements of the ARIMA model.

Figure 6. Autocorrelation ACF -0.4 0.0 0.2 0.4 0.6 0.8 1.0 0.0 0.5 1.0 1.5

Lag Source: Own study

Figure 7. Partial autocorrelation Partial ACF Partial -0.4 0.0 0.2 0.4 0.6 0.8

0.5 1.0 1.5

Lag Source: Own study

After adjusting the series to stationarity (Figure 8) by a single seasonal differentiation (D = 1) and a single differentiation due to the trend of (d = 1) and taking into account one parameter of the moving average of the trend (q = 1), and seasonality (Q = 1), the best-fitting model is the seasonal ARIMA model (0,1,1), (0,1,1) [12].

Jacek Brożyna, Grzegorz Mentel, and Beata Szetela / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 73-88 Figure 8. Time series of energy demand reduced to stationarity

Stationarity of time series (d=1, D=1) -0.05 0.05

2004 2006 2008 2010 2012 2014 2016

ACF PACF -0.4 0.0 -0.4 0.0

0 5 10 15 20 25 30 35 0 5 10 15 20 25 30 35

Lag Lag

Source: Own study

As in the Winters exponential smoothing model, checking the adjustment of ARIMA model to the data has been made by analyzing the histogram and the graph of quantile residuals (Figure 9) and using the test of normality Shapiro.

Figure 9. The distribution of residuals in SARIMA(1,1,0)(1,1,0)[12] model Histogram of Residuals Quantile residuals Density Quantile of the test -1.5 -1.0 -0.5 0.0 0.5 1.0 1.5 0.0 0.2 0.4 0.6

-2.0 -1.5 -1.0 -0.5 0.0 0.5 1.0 1.5 -2 -1 0 1 2 Theoretical quantiles Source: Own study

The residuals test of Shapiro has shown that the residuals are normally distributed (p-value = 0.6869), so it is possible to make forecasts with the use of the selected model. The resulting forecasts for the years 2016-2017 have been presented in Table 4 and Figure 10.

Jacek Brożyna, Grzegorz Mentel, and Beata Szetela / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 73-88 Table 4. The forecast for energy demand in the National Energy System in Poland for the years 2016-2017 using the ARIMA model

Date Forecast Lo 80 Hi 80 Lo 95 Hi 95 [GW] [GW] [GW] [GW] [GW] Jan 2016 25.37 24.70 26.04 24.35 26.39 Feb 2016 24.50 23.80 25.21 23.42 25.58 Mar 2016 23.75 23.00 24.49 22.61 24.88 Apr 2016 22.89 22.11 23.67 21.70 24.08 May 2016 21.30 20.49 22.11 20.06 22.54 Jun 2016 21.58 20.74 22.42 20.29 22.87 Jul 2016 21.86 20.99 22.74 20.53 23.20 Aug 2016 21.83 20.93 22.73 20.45 23.21 Sep 2016 22.85 21.92 23.78 21.42 24.27 Oct 2016 23.86 22.90 24.82 22.40 25.33 Nov 2016 24.88 23.90 25.87 23.37 26.39 Dec 2016 25.27 24.25 26.28 23.72 26.82 Jan 2017 25.49 24.37 26.61 23.78 27.21 Feb 2017 24.62 23.46 25.79 22.84 26.41 Mar 2017 23.87 22.66 25.08 22.02 25.72 Apr 2017 23.01 21.76 24.26 21.10 24.92 May 2017 21.42 20.13 22.71 19.45 23.39 Jun 2017 21.70 20.37 23.03 19.67 23.73 Jul 2017 21.98 20.62 23.35 19.89 24.07 Aug 2017 21.95 20.55 23.35 19.81 24.09 Sep 2017 22.97 21.53 24.41 20.77 25.17 Oct 2017 23.98 22.51 25.46 21.74 26.23 Nov 2017 25.01 23.50 26.51 22.70 27.31 Dec 2017 25.39 23.85 26.92 23.03 27.74

Source: Own study

Jacek Brożyna, Grzegorz Mentel, and Beata Szetela / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 73-88 Figure 10. The forecast for energy demand in the National Energy System in Poland for the years 2016-2017using the SARIMA model

Forecasts from ARIMA(0,1,1)(0,1,1)[12] [GW] 16 18 20 22 24 26 28

2005 2010 2015 Source: Own study

In Figure 10 one can see the trend and volatility of forecasts in line with the course of the observed series. The errors of such forecasts are: ME -0.03575571 RMSE 0.50070100 MAE 0.38277560 MPE -0.15095150 MAPE 1.73664300 MASE 0.62968460

3.4 Comparison of forecasts The forecasts made by using both the Winters exponential smoothing model and SARIMA model have given similar results (Figure 11). The average difference between the forecast was only 0.26 GW and 1.06 GW maximum for July 2017 year. Also the errors of forecasts for both models are similar - except for a Mean Error, which is higher for SARIMA model, but it is still low enough that it does not raise concerns about the quality of forecasts.

Jacek Brożyna, Grzegorz Mentel, and Beata Szetela / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 73-88 Figure 11. Comparison of forecasts

Winters ETS(AAA) ARIMA(0,1,1)(0,1,1)[12] [GW] 21 22 23 24 25

2016.0 2016.5 2017.0 2017.5

Time Source: Own study

Comparing the results of both forecasts and comparing the forecast a month-to- month to the year 2015 (Table 5 and Table 6), it is possible to make a qualitative assessment of forecasts conformity. As onecan see, the trend in energy demand coincides in both models for the winter months (January, February, March) and summer months (July and August), and for April. For the remaining months (mostly in spring and autumn), the trends vary depending on the year of the forecast, and for June are definitely different - in the model Winters ETS a decline in demand for energy is expected, and in the model SARIMA its growth. Problematic forecasts for the months of spring and autumn may result from the large differences between the energy demand in such periods in the past. This can be caused by substantial weather changes in spring and autumn, and is is one of the main factors affecting the demand for energy.

Table 5. Witers ETS: Comparison of forecasts month to month

Month Winters ETS Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2015 25.10 24.31 23.55 23.24 21.39 21.44 22.18 22.30 22.95 23.83 24.87 24.79 2016 25.39 24.42 23.77 22.44 20.72 20.74 20.80 21.21 22.47 23.76 24.78 25.44 Year 2017 25.66 24.70 24.05 22.72 21.00 21.01 21.08 21.48 22.75 24.03 25.06 25.71 '16/'15 ↑ ↑ ↑ ↓ ↓ ↓ ↓ ↓ ↓ ↓ ↓ ↑ '17/'15 ↑ ↑ ↑ ↓ ↓ ↓ ↓ ↓ ↓ ↑ ↑ ↑

Source: Own study

Jacek Brożyna, Grzegorz Mentel, and Beata Szetela / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 73-88 Table 6. SARIMA: Comparison of forecasts month to month.

Month SARIMA Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2015 25.10 24.31 23.55 23.24 21.39 21.44 22.18 22.30 22.95 23.83 24.87 24.79 2016 25.37 24.50 23.75 22.89 21.30 21.58 21.86 21.83 22.85 23.86 24.88 25.27 Year 2017 25.49 24.62 23.87 23.01 21.42 21.70 21.98 21.95 22.97 23.98 25.01 25.39 '16/'15 ↑ ↑ ↑ ↓ ↓ ↑ ↓ ↓ ↓ ↑ ↑ ↑ '17/'15 ↑ ↑ ↑ ↓ ↑ ↑ ↓ ↓ ↑ ↑ ↑ ↑

Source: Own study

4. CONCLUSION To construct the forecasts of maximum demand for energy in Poland two models have been used: Winters exponential smoothing, and seasonal ARIMA. The forecasts show tendencies and fluctuations and the observed series, and errors are at low, similar to each level, which confirms the correctness of the models selection. Forecast charts have a similar shape, and the average difference between them is small and it is only 0.26 GW. However, one can see the differences by comparing the months of forecasts of both models with data from the last year. In forecasts made using the Winters model of exponential smoothing more often than in the SARIMA model, the predicted values for the years 2016 and 2017 are lower than in 2015. For both models a drop in energy demand is forecast for the summer months, while an increase for the winter months. In spring and autumn months there are differences between the forecasts in terms of the direction of change in relation to the demand for energy from the last year, however, as previously mentioned, the same course of the two forecasts is similar.

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Bagrat Haykovich Yerznkyan / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 89-100

Montenegrin Journal of Economics

Vol. 12, No. 2 (2016), 89-100 ‘

The Strategy for Russia’s Breakthrough to the Future: Lvov’s Legacy1

Bagrat Haykovich Yerznkyan2

1 The paper is supported by a grant of Russian Foundation for Basic Research (Project No. 15-06-08515). 2 Doctor of Sciences (Econ.), Chief of laboratory at Central Economics and Mathematics Institute, RAS, Professor, Moscow, Nakhimovsky avenue, 47, ph. number +7 4991293544, e-mail: [email protected], [email protected]

ARTICLE INFO ABSTRACT Received November 11, 2015 The strategy of for breakthrough to the future developed by Dmitry Received in revised form Feb. 10, 2016 Lvov is not reduced to the national specificity rejecting standard Accepted May 28, 2016 governmental efforts perspective, but points out the multiplicity of Available online June 15, 2016 the real problems needed to solve. The goal of this paper is to attract attention to the Lvov’s insights presented as a strategy for JEL classification: Russia’s breakthrough to the desirable stationary independent future. The strategy includes the attitude to people, the system of B41, H00, O10, O30, P20 public revenue distribution, the social conditions, the distortions occurred after voucher privatization scheme, system of state DOI: property, relation to rent and other items. The paper also considers 10.14254/1800-5845.2016/12-1/6 the global context of the Russian neo-liberal reforms, socioeconomic problems emerged as results of 1990s reforms, the Keywords: scientific grounding of the realization of breakthrough project, the breakthrough strategy, desirable changes and directions of their implementation. Lvov, Russian reform, development policy

1. INTRODUCTION The period of 1990s Russian reforms, when Dmitry Lvov (1930-2007), Academician- Secretary of the Economics Department of the Russian Academy of Sciences, worked at his strategy for breakthrough to the future, was turbulent and dramatic enough: for most countries – both developing and transitional – the period of neo-liberal reforms now sometimes called as the period of lost opportunities; for a great number of countries, including Russia and perhaps all countries of the post-Soviet space, it was a period of negative growth. Practically in all of them economic policy during reforms focused on structural adjustment, a combination of macroeconomic stabilization measures to restore domestic and external equilibrium, and structural changes in policies and institutions designed to make the economy more efficient and flexible, and thereby increase growth. As the time progressed, and the consequences of macroeconomic

Bagrat Haykovich Yerznkyan / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 89-100 disequilibria and non-stationary station became clearer, development economists and practitioners increasingly accepted the view that broad macroeconomic stability is necessary for sus- tained growth and transforming economy into stationary one. For instance, at the start of the new decade, heavy weight has to be placed on likely macroeconomic particularly fiscal- developments in analyzing growth prospects in countries as diverse as the Soviet Union (Rus- sia), India, Turkey, Cote d'Ivoire, and Brazil (Fisher, 1991). The Russian reform package taken by reformers as bold and non-critically as it was possible was not too different from the strategy that groups such as the IMF typically recommended to developing countries. In this context, “typically” means that these groups ignored institutional differences and tended to disregard the distinctions between institutional systems in the countries where reforms carried out. However institutional differences are reality: “each time and each country is different”, claims Stiglitz and asks rhetoric questions: “Would other countries have met the same success if they had followed East Asia’s strategy? Would the strategies which worked a quarter of a century ago work in today’s global economy? Eco- nomists can disagree about the answers to these questions. But countries need to consider the alternatives and, through democratic political processes, make these choices for themselves. It should be – and it should have been – the task of the international economic institutions to provide the countries the wherewithal to make these informed choices on their own, with an understanding of the consequences and risks of each” (Stiglitz, 2002, p. 88). However, such a strategy per se was not the major reason why reforms in Russia had not worked: more serious was the fact that the reformers “neglected to consider the institutional framework within which their reforms were to take part… They did not understand, however, that in order for their reforms to be carried out, it was necessary also to change the existing institutions, such as he collectivized farms, monopolized industry, and weak service sector” (Goldman, 1994, p. 101). Moreover, Western advisers and their Russian followers failed to recognize that the Washington Consensus ideology with its doctrines on the liberalization of the economy and the privatization of property was a prime agent in the tragedy that had been in- flicted on our country. “In noting that the population of Russia would fall from 146 million people at present, to 130-135 million by 2015 – counting a trend triggered in 1992” – the US Na- tional Intelligence Council (NIC) attributes the demographic toll to “such societal costs of transition as alcoholism, cardiac diseases, drugs, and a worsening health delivery system”, claimed in his editor’s introduction Fred Harrison (2001, p. 6). The Russian reforms widely known as and consciously undertaken on the basis of shock therapy were put into effect on January 2, 1992. For reformers it was important in accordance with the IMF recommendations to privatize quickly and to deal with the issues of competition and regulation later. “But the danger here is, – explains Joseph Stiglitz, – that once a vested interest has been created, it has an incentive, and the money, to maintain its monopoly position, squelching regulation and competition, and distorting the political process along the way. There is a natural reason why the IMF has been less concerned about competition and regulation than it might have been. Privatizing an unregulated monopoly can yield more revenue to the government, and the IMF focuses far more on macroeconomic issues, such as the size of the government’s deficit, than on structural issues, such as the efficiency and competitiveness of the industry. Whether the privatized monopolies were more efficient in production than government, they were often more efficient in exploiting their monopoly position; consumers suffered as a result… Not surprisingly, the rigged privatization process was designed to maximize the amount government ministers could appropriate for themselves, not the amount that would accrue to the government’s treasury, let alone the overall efficiency of the economy (Stiglitz, 2002, p. 56, 58). The outcome of reformers efforts predictable enough for Lvov inter alia was demographic crises and social trauma (Veselkova, 2001), national tragedy (Roskoshnaya, Harrison, 2001) or more detailed: the unprecedented peacetime drop in production, high inflation, mass impover-

Bagrat Haykovich Yerznkyan / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 89-100 ishment, degradation of the culture, the orgy of crime, and entire disorientation of economy and society and so on. To understand the need for making efforts on climbing out a reform trap – and it was a real trap because after all “the purpose of the reforms should be to make people’s lives better” (Goldman, 1994, p. 29) – the mere idea which was obvious from the very beginning of the 1990s reforms in Russia for Academician D. S. Lvov, however “what Yeltsin and Gai- dar, as well as Gorbachev, never fully understood” (ibid) – and transit to stationary regime direction was one thing, however to develop the realistic enough strategy for the breakthrough to the desirable state of economy was quite another. The goal of this paper is to attract attention to the yet or, better to say, nowadays even more actual insights-proposals-reflections of D.S. Lvov on the ways for Russia’s breakthrough to the desirable stationary independent future having in mind the contemporary situation with international sanctions undertaken against our country. Today, in a time of renewed interest in the heterodox economic theory, including institutional, evolutionary and other ramifications of modern economic thought, Lvov’s strategy of independent development as a forerunner of recent strategies, appears as a useful instrument which should not be neglected; moreover, it should be carefully reconsidered. While this paper is primarily about the proposals of Lvov to find the ways leading to creation of such a stationary future it is appropriate to briefly present the chronology and essence of the previous proposed plans on reforming the economic system of the USSR and then Russia (see Table 1).

Table 1. Economic Plans Proposed to and Abandoned by Gorbachev

Plan Economist Date 1 Intensification & Acceleration Abel Aganbegyan March 1985 2 Overall Economic Plan Leonid Abalkin & Late 1988 Institute of Econimics 3 Overhaul Economy & Move to Market Abalkin & Commission October 1989 on Economic Reform 4 Plan & Market Nikolai Ryzhkov December 1989 5 Support for Market Nikolai Petrakov May 1990 6 Five-Year Plan Gorbachev May 1990 7 400-Day Plan Gregory Yavlinsky February 1990 Mikhail Zadornov Aleksei Mikhaylov 8 500-Day Plan Stanislav Shatalin August 1990 9 Plan & Market Abalkin & Ryzhkov Fall 1990 10 Integrate Shatalin & Abalkin & Ryzhkov Aganbegyan November 1990 11 Referendum on Property & Market Gorbachev September 1990 Reform 12 Compromise Aganbegyan October 1990

Source: Goldman, 1994, p. 76.

It should be mentioned, that in some of these plans took part researchers from Central Economic & Mathematic Institute, Russian Academy of Sciences, including of course D.S. Lvov himself. And although to find a way out from the post-reform disastrous situation, characterized by reformers as “the adaptation to the new structures of social relations”, however, called by Lvov as “the syndrome of adaptation to catastrophe”, was incredibility difficult, Lvov and his colleagues accounted they had “the right to think a fundamental restructuring of all of Russian society” was underway, in which the abovementioned “Gorbachev period and the following 91

Bagrat Haykovich Yerznkyan / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 89-100 troubled times” were “only episodes in a renewal of the Eurasian and, possibly, world order” (Lvov, Moiseev, Grebennikov, 1996, p. 43). There were, according to Lvov, three determining factors which provided conclusion for the effective development and joining the ranks of the leading countries of the world:  country’s huge reserves of fuel, minerals, fertile soil and other natural resources; exceeding of Russia’s per capita resource potential over that of the U.S. 2 to 2.5 times, Germany – 6 times and Japan – 18 – n 20 times;  a unique potential of highly qualified specialists and scientists enable to solve the most complicated problems pertaining to science, technology and production;  powerful industrial base (Lvov, 1995, p. 2). However, there was a powerful gap between the huge opportunities for Russia’s prosperity and the harsh reality of life, claimed Lvov, and in order to diminish this gap by analyzing the post-reform situation and offering principles and ways of implementing the needed measures for breaking to the future there emerged a need for adequate strategy (Yerznkyan, 2015). The rest of the paper is organized as follows. In section 2 we consider the global context of the Russian neo-liberal reforms. The socio-economic problems emerged as results of mainly 1990s reforms and needed in solution are a theme for study in section 3. Section 4 is devoted to the scientific grounding of the realization of breakthrough project. In section 5 we analyze the desirable changes and highlight the directions of their implementation. In section 6 we give some concluding remarks.

2. RUSSIAN NEO-LIBERAL REFORMS IN THE CONTEXT OF GLOBALIZATION Economic ‘globalization’ is a historical process, the result of human innovation and technological progress. It refers to the increasing integration of economies around the world, particularly through the movement of goods, services, and capital across borders. The term sometimes also refers to the movement of people (labor) and knowledge (technology) across international borders. There are also broader cultural, political, and environmental dimensions of globalization. Perhaps more importantly, globalization implies that information and knowledge get dispersed and shared. Innovators can draw on ideas that have been successfully implemented in one jurisdiction and tailor them to suit their own jurisdiction. Just as important, they can avoid the ideas that have a clear track record of failure. It is remarkable that Joseph Stiglitz, a frequent critic of globalization, has nonetheless observed that globalization “has reduced the sense of isolation felt in much of the developing world and has given many people in the developing world access to knowledge well beyond the reach of even the wealthiest in any country a century ago’. And, what is more remarkable, “the antiglobalization protests themselves are a result of this connectedness’ (Stiglitz, 2002, p. 4). It is worthy to say, in the context of globalization, that although foreign investment was not one of the three main pillars of the Washington Consensus – fiscal austerity, privatization, and market liberalization – but it was a key part of the new globalization, because “growth occurs through liberalization, “freeing up” markets. Privatization, liberalization, and macrostability are supposed to create a climate to attract investment, including from abroad… Foreign direct investment has played an important role in many – but not all – of the most successful development stories in countries such as Singapore and Malaysia and even China” (Stiglitz, 2002, p. 67). Beginning in the early 1990s, our country entered the phase of neo-liberal reforms, “carrying the banner that read: democratization of power, liberalization of the economy and humani- zation of public relations. The people were ready to pay for it”. However, “the result of the adopted policy turned to be deplorable” for them (Lvov, 1995, p. 4). These reforms, their

Bagrat Haykovich Yerznkyan / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 89-100 pluses and minuses, benefits (if any) and losses, the goals, mechanisms, reasons, factors, etc., all of them may be viewed from the different points of view. In this section, let us view them through the prism of globalization that had and still has significant impacts on all economies of the world, including the Russian economy. Since the Second World War, the global economy has been dominated by the USA and the countries comprising the EU. The international economic and financial institutions that have been the centerpiece of the global economy as the goal of globalization project were crafted by these countries (McKinney, 2014, p. 58). Globalization, for example, has produced big gains for the EU in the past. 20% of improvement in EU living standards over the post-war period was due to deeper economic integration at the world level. Globalization is a major source of EU productivity gains through better specialization, economies of scale, technological content of imports, greater competition and the spur to innovation (Globalization, 2006). Much has changed, however, since the beginning of the new millennium. China will soon be the largest economy in the world, and (some of) the other counties are rapidly increasing in economic importance, meanwhile the EU is experiencing slow growth and the USA is struggling with serious economic problems (McKinney, 2014, p. 57). The American economy has undergone several economic and political trials during the past decade. The US sub-prime mortgage crisis which has spiraled into “the largest financial shock since the Great Depression” caused global recession. Most recently the economic and structural problems and fiscal difficulties within the Eurozone caused fears about its countries sustainable development and raised uncertainty about the future of the Eurozone. These difficulties strengthened forces opposed to globalization, which in the minds of many was equated with investor capitalism and greedy, irresponsible pursuit for short-term profits (Yerznkyan, Vardanyan, 2013, p. 86). There is, in our opinion, a deeper reason of the strengthening the mentioned forces: globalization, as underlines Dani Rodrik, can be presented as a kind of trilemma: amongst democracy, high-levels of globalization, and nation states, you can pick any two (Rodrik, 2011); and since one is unlikely to see the end of the last, and he/she doesn’t want to give up the first, globalization in its more extreme forms will have to go. What we now can see it is the changing face of globalization or at least the global economy. It should be mentioned that from the very beginning of realization of the neo-liberal reforms in Russia for many of prominent scholars became clear that realization of proposed for Russia transition experiment “has fallen far short of what the advocates of the market economy had promised, or hoped for. For the majority of those living in the former Soviet Union, economic life under capitalism has been even worse than the old Communist leaders had said it would be” (Stiglitz, 2002, p. 133). It should be also underlined the importance of institutions and related to them social orders as well as a problem of institutional choice when decisions are made in favor of one or another transplanted institution. In the social orders – models of the large-scale social systems’ institutional arrangements – the key role play hierarchically or/and complementarily organized institutions (their settings) that promote the creation of a political, economic, religious, military power and the concentration of control over resources and social functions. Limited access orders which are dominant in most countries of the world – in the presence of a number of conditions – can be transformed into open access orders (North et al., 2009). This transformation is generally carried out by borrowed or transplanted institutions. It is, however, difficult to know what will come of a policy transferring a full set of institutions from one country to another. Thus, to minimize the possible risks of institutions’ transferring and to form the effective control system of the process, it is important yet at an ex ante stage of institutional selection or choice to provide safeguards against the expected risks. In (Yerznkyan, 2014), on a simple schema, created by analogy with a well-known simple contractual schema of Oliver Williamson (1985), the possible situations – consequences of 93

Bagrat Haykovich Yerznkyan / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 89-100 choice – are shown. The main criterion for situations classification is compatibility of the borrowed institution with the institutional system of a recipient country. In a case of compatibility or coherence between the transplanted formal macro-level institutions and domestic non-formal micro-level institutional fabric they can reinforce each other, in a case of neglecting the possible risks the potential incompatibility of external and internal institutions can lead to the economic instability, social and political chaos in the countries with limited access. However, discontents like discussed here were clear for D.S. Lvov as early as two-three decades ago. Prospects for the future under neo-liberal reforms with the Russian anticommunism that served as an ideology for constructing the antisocial market economy were bleak, claimed Dmitry S. Lvov – one of the most prominent Russian scholars who tried to find the exit and save the situation. However, it served without mentioning the very word ‘ideology’, because it was preferred not to speak about capitalism as about a purpose of post-Soviet reforms and to cover it with advertising shields of ‘civilized’ or ‘social’ market economy (Lvov, Grebennikov, Dementyev, 1996, p. 26).

3. PROBLEMS TO BE SOLVED As a result of reformers’ efforts (and contrary to their intentions, at least declarative ones), Russia received a lot of problems. Many of them were due almost entirely to the attempt to adopt Western practices and Western norms. To develop strategies capable of fulfilling everyone’s aspirations – and such was a strategy developed by Lvov – it was necessary at first to formulate the problems that needed in solution. However, economic science does not offer proposals for an effective economic system because it is based on principles that ignore the moral and spiritual development of society, claimed Academician Dmitry Lvov. It is fashionable to say that ineffective labor is even worse than unemployment. That is the reason why full employment is sacrificed to the so-called principle of “the maximization of exchange value wealth”. In Russia, this thinking leads to the abandonment of decaying industries, territories and cities, the extinction of professions, the dying out of national productive forces on a giant scale. Modern economic theory justifies this, repeated often Lvov having in mind mainstream or orthodox theory, and the words of Friedrich List could serve as the best answer to this theory: “There is no world of Wealth! The concept of the world can only be spiritual or alive… How can we talk about the world of minerals, for example? Eliminate the spiritual basis and everything that is called ‘wealth’ will become a lifeless substance. Remember what happened to the treasures of Carthage and Tir, to the wealth of Venice palaces when the spirit had gone from these heaps of stone?” (Lvov, 2001, p. 49). There are more other problems to be solved in order to revitalizing Russian economy and realizing a breakthrough project to the future. Some of essential problems presented as failures spheres and strategic points are given in Table 2.

Table 2. Spheres of Failures and Points for the Breakthrough to the Future

Spheres of Failures Points of Strategy 1 Spiritual and moral The spiritual and moral renaissance of the nation is the starting degradation. point for the breakthrough. 2 Immoral privatization of As a result of three waves of privatization – (i) the voucher and public revenue. (ii) mortgage schemes, and (iii) artificial (false) bankruptcy – state property was passed to private persons (the so-called “new management”) and not to new stockholders.

Bagrat Haykovich Yerznkyan / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 89-100 3 Liberalization of all The labor of productivity is much lower than in the Western factor of production, countries however the level of wages cannot be excused by including labor as the reference to lower productivity. In fact, Russian average worker most “depressed” fac- produces three times more output per dollar of wage than a tor. worker in the USA. There is need for a special income distribution policy and the way to achieve the goal of socializing the income of the “upper 10%” and using it to support social groups that need help to kick-start economic activity is taxation of real estate and luxury – the tax basis for local and state budgets. It is necessary to declare the principle of free housing for people on the lowest incomes, free land plots, and other social guarantees. State guarantees should be expanded to the other social, scientific and technological spheres: a fixed share of GDP must be reserved for education, medical care and science. 4 Failures of the voucher One of the strategic goals for the breakthrough is to correct the privatization schemes. distortions that occurred as a result of the voucher privatization scheme. The essence of the current situation is as follows: - economic power is being redistributed with the help of political power; - political problems are being solved by alienating “tasty morsels” of public property. The solution is: - it should be not allowed government to lose its status; - it must be avoided governmental loss of the right to control the activities of corporate enterprises and to share their profits; - existing rights obtained through privatization should be retained by persons and companies. 5 Failures of the system It is necessary to perform a transition to the new system of of state property. state property with the major elements as follows: - securing, through the Constitution, a significant part of the nation’s natural resources in the ownership of society; - open competitive market regulations should apply to the management of state property; - a national dividend – part of the income of entrepreneurs and all rent from commercial use of national property – must be used as the main source of revenue for the social guarantees fund. 6 The paradox of taxation The solution of the paradox of getting up to 70% of all taxes at on wages. the expense of the labor as the mostly abused factor of production is a shift of the tax burden from the wages onto rent. 7 Problems of socializa- Society must be declared to be the highest legal entity that tion of rent as the basis owns territorial and natural resources. for constitutional de- Using rent as the source of public revenue can be the material velopment of society realization of the highest rights of society to territorial and natu- and of the state. ral resources.

Source: adapted according to: Lvov, 2001, pp. 48–55.

Bagrat Haykovich Yerznkyan / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 89-100 4. REFORMS SCIENTIFIC GROUNDING There are a lot of publications where reform failures and problems stemming from them are discussed. Many of them concern such themes as privatization, liberalization (the removal of government interference in financial markets, capital markets, and of barriers to trade), etc.; in (Yerznkyan, 2005), for instance, orthodox and heterodox views on the privatization and corporate governance are considered, the causes of reform failures in transitional economies are analyzed, ways of their development based on the forming the one of two market economy models – market-based or bank-based – are discussed. Some publications study of A systemic approach to them is given inter alia in (Lvov, 1995) where an attempt to catch the real problems of Russian post-reform economy to learn to assess the country’s possibilities realistically, and to give the scientific grounding for designing and realizing the adequate future- oriented transformation of the Russian socioeconomic system is done (see Table 3).

Table 3. Reforms from the Viewpoint of Modern Science

Aspects Explanation 1 Social orientation The thesis of the archaic character of the state and its discrep- ancy with market economy conditions can hardly be accepted for the sole reason that this system was introduced in the countries with the highly developed market economy. 2 Social and psycho- The psychological aspect plays a fundamental role in the com- logical factors plex of measures aimed at overcoming the crisis. Not only the national economy and political institutions must be recon- structed, but also the people’s subjective attitude towards the reality. 3 Correlation of old There are many aspects of co-operation of the new and old eco- and new structures nomic structures. 4 Openness of econ- The thesis of transition to the open economy as such does not omy evoke objection, however its general concepts do net necessarily mean that all exchanges are usually economically and politically effective and their terms are inessential. 5 Privatization Property is the central question of the economic reforms. How- ever, in the situation of 1990’s Russian reforms it could neither be solved nor correctly formulated. 6 Inflation In 1990s Russia, the true vehicle of inflation was not be excessive money demand but the economic behavior of technologically backward and monopolized producers.

Source: adapted according to: Lvov, 1995, pp. 9–18.

5. WHAT SHOULD BE CHANGED In order to begin doing something after reform and post-reform years collapse and thus to catch and stand on the way leading to the favorable future, it should be changed the following positions:  the attitude to the people – they should be supported by their native culture and spirit – the only way to avoid the transmutation of human beings into a physical “labor force” that waits to be exchanged for lifeless animal comforts;

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 the system of public revenue distribution by returning financial resources to everyone for achieving sustainable economic growth and prosperity for every citizen;  the social conditions including: the doubling or tripling of average wages especially in those industries, which should then became a starting norm for other sectors; activation of investment policy; shifting the main tax burden from incomes to people’s real estate; declaring the principle of free housing for people on the lowest incomes, free land plots, and other social guarantees;  the distortions that occurred as a result of the voucher privatization scheme;  the system of state property by creating a system national property and national dividend;  the relation to rent in a sense that its socialization is both a real opportunity to provide sustainable public revenue and a condition for allowing Russia to remain an independent geo- political unit and competitive participant in the modern world (Lvov, 2001).

Table 4. Proposed Directions of Scientific-Technological Development

Problems / Spheres Proposals / Directions 1 Management Economy’s dividing into two intersecting contours of management – state one and commercial (market) one. Strict rules for interacting between these two sectors. 2 Science The fundamental science sphere must be embedded into the state sector. The most important function of management in the state sector is establishing of priorities of scientific-technological development. 3 Presidential Council Forming the Presidential Council on science and technology consisting of the most prominent scientists and specialists of wide profile. The main task of the Council serving as a “brain headquarters” of the President of Russian Federation is estimating those long-range priorities where the country has got a stable niche in the world scientific-technological development. 4 Targeting-programming Creating the Targeting-programming Committee to which the Committee development and accompanying pf Presidential programs should be put on implementing priority directions of scientific- technological development. 5 Presidential Program Synchronizing the procedure of preparation, approval and correcting of Presidential programs with the procedure of development and consideration of state budget. 6 Scientific foundations Creating a network of scientific foundations in Russian Acad- emy of Sciences receiving money for research part of Presi- dential Programs and distributing them for particular projects and grants. 7 Regime of functioning Introducing a regime of tax-free functioning for all organizations of Russian Academy of Sciences, for education-research and experimental-production complexes as well as for enterprises of military-industrial complex participating in fulfillment of Presidential programs.

Source: adapted according to: Lvov, Grebennikov, Dementyev, 1996, pp. 56–58.

Bagrat Haykovich Yerznkyan / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 89-100 To realize the mentioned changes, using mainly rent as the source of public revenue that can be serve as the materialization of the highest rights of society to territorial and natural resources, it is necessary to pay special attention to the scientific groundings of the process of changes and offer proposals as to the directions of scientific-technological development of Rus- sia. Some of the proposed directions are given in Table 4. These directions lead not only to the narrowly understood scientific-technological development of Russia, they indicate ways for or at least create preconditions for the effective development of Russian society and economy as a whole by making our own history through means of the forming new institutional reality and stationary innovative-oriented economic system. As Tony Lawson claims: “Fundamentally I believe that we can make our own history. We can grasp the structures of reality and we – the community at large – can intentionally transform them in part according to our own goals. The future is not predetermined. So as I say we can make our own history” (Cambridge, 2009, pp. 106–107).

6. CONCLUDING REMARKS “The collapse of the Soviet Union has triggered a string of research about previously neglected issues: How to build a market economy? Is there a single brand of capitalism or can a significant variety of capitalisms coexist, even in the long run?” These claims of Rober Boyer (2005, p. 44) are about possibility or impossibility of existing multiple capitalist economic systems, not a single and predominated one – identical for all countries generally and economies in transition particularly. Bruno Amable (2003), for example, distinguishes five [ideal] types of contemporary capitalism (market-based, social democratic, Asian, continental European, South European), explaining this multiplicity by institutional complementarity (close to that developed by Aoki (2001)) as well as institutional hierarchy. Other scholars find even more types of historical and modern models of capitalisms. As for a strategy of Dmitry Lvov, it has been an attempt to understand and describe the ways of constructing such an economy – relevant just for Russian future-oriented needs, however useful at the same time for other countries. Nevertheless, the discussed in the paper points and principles of the breakthrough strategy “are in no way comprehensive and can hardly concretize the ways of implementing the measures suggested”, wrote at the reforms and early post-reform times D.S. Lvov (1995, p. 37), and that was true. However, true is also the fact that many of the arguments and ideas of Lvov – both theoretical and practical ones – remain their actual meaning even today, in our times. Analyzing, for example, the situation with ongoing Ukraine crisis and Western sanctions in the aspect of enterprises of the Ukrainian military-space complex that had been successfully cooperating with the Russian ones until the last time, R.J. Khasbulatov asks: why did the Rus- sian partners “not transfer these manufactures to Russia, for example, through some subsidiar- ies or branches?” Then he adds that he doesn’t sure that the Russian “captains of the military- space complex” “will be able to cope with the current, quickly complicating situation, if they were not able to cope with these tasks almost in the ideal conditions”. And as a conclusion: “Russia has been in need of another theoretic and methodological basis for serious economic policy that will serve the interests not only of the rich class, but also of the whole society for a long time” (Khasbulatov, 2014, p. 39). The conclusion Khasbulatov did so far as concerns to D.S. Lvov had been for him a kind of axiom. Moreover, if Russia adopted such a nation-oriented and theoretically and methodologically proved basis for reforming its own economy it could have “a chance to set an example of economic measures of nature protection for other countries” (Lvov, 1995, p. 36). That is perhaps a central message of this paper – to indicate a way to the future not only for Russia, but also to help other counties to find their own ways to the future.

Bagrat Haykovich Yerznkyan / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 89-100 As for Lvov, and his outstanding insights presented in this paper are the best illustration of it, the only way out of the tragedy caused by reformers’ efforts to copy Western practices and norms leading unambiguously to the situation of institutional nihilism (Draskovic, Draskovic, 2012) with inhibiting institutional and other factors that has caused the dysfunctional conglomerate system, while ignoring the commonality of interests of the population and giving priority to the cult of individual, was “to build an economy that reflects the common interests of the people and their natural endowments, the organizing mechanism for which would be a restructured public finance” (Harrison, 2001, p. 7).

REFERENCES Amable, B. (2003), The Diversity of Modern Capitalisms, Oxford University Press, Oxford. Aoki, M.T (2001), Toward a Comparative Institutional Analysis, MIT Press, Cambridge, MA. Boyer, R. (2005), “Coherence, Diversity, and the Evolution of Capitalisms – The Institutional Complementarity Hypothesis”, Evolutionary and Institutional Economic Review. Vol. 2. No. 1, 43-80. “Cambridge Social Ontology: An Interview with Tony Lawson” (2009), Erasmus Journal for Phi- losophy and Economics, Vol. 2. Issue 1. Draskovic V., Draskovic M. (2012, “Institutional Nihilism of the Post-Socialist Transition”, Mon- tenegrin Journal of Economics, Vol. 8. No. 2, 191-206. Fisher, S. (1991), “Growth, Macroeconomics, and Development”, NBER Macroeconomics An- nual, Vol. 6, 329-379, http://www.nber.org/chapters/c10986 (12.09.2015). “Globalization: Trends, Issues and Macro Implications for the EU” (2006), EC Economic Papers, No. 254. Goldman, M. I. (1994), Lost Opportunity: Why Economic Reforms in Russia Have Not Worked, W.W. Norton & Company, New York, London. Harrison, F. (2001), “Editor’s Introduction: The Individual as an Ideological Construct”, Geophi- los, No. 01(1), 3-20. Khasbulatov, R. I. (2014), “Paradoxes of Economic Theories and Politics”, Economy of Region, No. 4(40), 23-40. Lvov, D. (1995), Of the Russian Economic Reforms Scientific Grounding, Central Economic- Mathematical Institute, Independent Economic Society, Moscow. Lvov, D., Grebennikov, V., Dementyev, V. (1996), “Path of Russian Reforms”, Working Paper # WP/96/014, CEMI Russian Academy of Sciences, Moscow. Lvov, D.S., Moiseev, N.N., Grebennikov, V.G. (1996), “A Conception of Russia’s Socioeconomic Development”, Matekon, Vol. 32. No. 4, 41-68. Lvov, D. (2001), “Rent as Public Revenue: The Strategy for Russia’s Breakthrough to the Fu- ture”, Geophilos. No. 01(1), 48-55. McKinney, J. A. (2014), “The Changing Global Economy: Roles of the United States and the European Union in the Evolving Context”, Economy of Region, No. 4(40), 57-68. North, D. C., Wallis, J. J., Weingast, B.R. (2009), Violence and Social Orders: A Conceptual Framework for Interpreting Recorded Human History, Cambridge Univ. Press, New York. Rodrik, D. (2011), The Globalization Paradox: Democracy and the Future of the World Economy, W. W. Norton, New York. Roskoshnaya, T., Harrison, F. (2001), “The Dangerous Myth: Methodological Individualism as A Tool of Ideology”, Geophilos, No. 01(1), 22-37. Stiglitz, J. E. (2002), Globalization and Its Discontents, Allen Lane. The Penguin Press, London. Veselkova, I. (2001), “The Demographic Crises: Fertility and Mortality in Transitional Russia”, Geophilos, No. 01(1), 38-470. Williamson, O. E. (1985), The Economic Institutions of Capitalism: Firms, Markets, Relational Contracting, The Free Press, New York. Yerznkyan, B. (2005), “The Coase Theorem and its Relation to the Post-Socialist Privatization and the Corporate Governance”, Voprosy ekonomiki. No. 7, 121–135 (in Russian). 99

Bagrat Haykovich Yerznkyan / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 89-100 Yerznkyan, B., Vardanyan, A. (2013), “Incorporating Microfinance into Institutional Setting of Economy”, Theory and Practice of Institutional Reforms in Russia, Collection of scientific works, ed. by B.H. Yerznkyan. Issue 25, CEMI Russian Academy of Sciences, Moscow, 82- 95. Yerznkyan, B.H. (2014), “Institutional Choice and Its Consequences”, Theory and Practice of Institutional Reforms in Russia, Collection of scientific works, ed. by B.H. Yerznkyan, Issue 30, CEMI Russian Academy of Sciences, Moscow,125-128. Yerznkyan, B.H. (2015) “The Breakthrough Strategy of Academician D. S. Lvov: Reflections in the Light of External Unfavorable Factors Activation”, Theory and Practice of Institutional Reforms in Russia / Collection of scientific works, ed. by B.H. Yerznkyan, Issue 32, CEMI Russian Academy of Sciences, Moscow, 80-92.

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Montenegrin Journal of Economics

Vol. 12, No. 2 (2016), 101-115 ‘

Budget Constraint Fulfilment in Some EU Candidate Countries

Miomir Jaksic1, and Milutin Jesic2

1 Professor, Faculty of Economics, University of Belgrade, Serbia, E-mail: [email protected] 2 PhD Candidate, Faculty of Economics, University of Belgrade, Serbia, E-mail: [email protected]

ARTICLE INFO ABSTRACT Received November 20, 2015 One of the crucial fiscal sustainability preconditions is fulfilment of Received in revised form Feb. 03, 2016 budget constraint. We applied the approach of budget revenue and Accepted May 27, 2016 expenditure cointegration in some EU candidate countries, because Available online June 15, 2016 of the reliability of this method for the observed countries. This is the first research of this topic in the majority of these countries JEL classification: based on the above-mentioned methodological set. We showed that weak fiscal sustainability is immanent to Serbia. In Albania and E62, H62, H63 Turkey, we could not find budget sustainability evidence. Our results DOI: are very important to economic policy makers in these countries, but also are of special concern to EU bodies in the European inte- 10.14254/1800-5845.2016/12-1/7 gration process. This is emphasised because of reported public debt crisis and macroeconomic spillovers in the European Union. Keywords: fiscal sustainability, budget constraint, cointegration approach, European Union candidates

1. INTRODUCTION Due to the public debt crisis that has been present in many European countries in recent years, the issue of fiscal sustainability has reemerged in the economic literature as one of the most interesting topics for research. Marking the fiscal policy of a country as fiscally sustainable requires the fulfilment of certain preconditions. However, in the economic literature, there is no agreement on which preconditions exactly have to be met. Jesic (2013, pp. 113-116) states that signals of fiscal irresponsibility could be systematic violation of fiscal rules, conduction of fiscal policy based on permanent budget deficits, not respecting the numerous goals of public debt management, the budget structure which is favorable towards consumption and at the investment’s expense and political budget cycles which are inherent to the economy. One of the most important preconditions is to fulfill the intertemporal budget constraint. However, although this is often recognized as the sole precondition of fiscal sustainability, we believe that the justification of such an approach is reasonable only in strictly defined circumstances. We are more inclined to think that budget constraint fulfilment implies only a necessary condition of fiscal sustainability. Indisputably, there is a long-term close connection between budget constraint fulfilment and fiscal sustainability. However, in terms of uncertainty 101

Miomir Jaksic, and Milutin Jesic / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 101-115 and without rational justification in the movements of macroeconomic indicators, a saturation point for government bonds could result. The empirical testing of budget constraint fulfilment has been experiencing its momentum since the 1980s. This type of research, however, has been carried out mainly in developed countries. Insufficiently long time series for reliable statistical inference and inadequate data quality are the main obstacles to such research in developing countries. The present paper aims to examine the budget constraint fulfilment in the EU candidates, but only for these where we could find necessary data. The movement of macroeconomic variables in these countries in recent times has been closely linked to negative tendencies in the fiscal domain. There is a reversible connection between macroeconomic stability and fiscal stability, and this connection is one of the rationales for research in this area. Therefore, one of the most significant contributions of the current study is the testing, for the first time for the majority of these countries, of the budget constraint fulfilment through the approach of cointegration between budget revenues and expenditures. This work will serve as an incentive for further research on this issue through the prism of this or some other methodology. Economic policy makers in these countries, especially in the fiscal domain, will be able to interpret the results of this work from their own perspective and, based on the main conclusions and recommendations of this study, make fiscal policy in their own country more accountable. This is especially important because of the process of integration into the EU that is more press- ing issue in the macroeconomic sense, than it was for the old members (Brada and Kutan, 2002, p. 32). The research results provide a foundation for further analysis of the concept of fiscal responsibility, which, as stated above, requires a deeper analysis of many other indicators. The remainder of this paper is organized as follows. An overview of the research literature on fiscal sustainability carried out from a methodological viewpoint close to that used in the study is presented first. A theoretical approach to the problem, which is the basis for the empirical part of the work, is in the focus of the next section. Then, we discuss the methodology used in the research, and after that, we provide basic information about the data used in the analysis. Finally, we present the research results, with special emphasis on their economic interpretation, and provide basic recommendations to policy makers in the observed EU candidate countries.

2. LITERATURE REVIEW In the literature, there are, roughly speaking, two different approaches to testing fiscal sustainability. One is the accounting approach, and the other is based on testing the budget constraint fulfilment. The first approach has its advantages; however, given the objective and methodology of our study, we focused only on those studies that empirically tested the budget constraint fulfilment. Special attention was given to works that applied cointegration approach as the basis in their methodological set. Although several studies have addressed this issue in developed countries, as previously explained, the backbone of all other research is formed by a number of works that paved the way for modern testing of the budget constraint fulfilment. One of the first studies that dealt with the cointegration of budget revenues and expenditures was done by Trehan and Walsh (1988), who tried to determine the conditions necessary to meet the budget constraint. These authors showed that stationarity of the primary budget deficit is neither a necessary nor a sufficient condition but that the budget deficit is, including interest payments. They empirically presented the cointegration between revenues and expenditures in the United States for the period of 1890 to 1986.

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Miomir Jaksic, and Milutin Jesic / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 101-115 Hakkio and Rush (1991) also applied the cointegration approach to the problem of fiscal sustainability. They assumed the possibility of interest rate variations, unlike many authors who dealt with this topic. In addition to the usual way of defining the variables for which they investigated the presence of cointegration, these authors carried out their analysis in a different manner, applying a modified version of the government revenue series. By using quarterly data for the period 1950 (Q2) to 1988 (Q4), they pointed to a potential issue regarding the possibility of marketing the debt. Quintos (1995) introduced the concept of weak sustainability. According to her, cointegration is the only sufficient condition for budget sustainability, whereas the value of the parameter from the cointegration vector, which is between 0 and 1, is a necessary and sufficient condition. By using quarterly data from 1947 (Q2) to 1992 (Q3), she showed that the US federal budget was sustainable; i.e., it fulfilled the intertemporal budget constraint. In addition to these works, a few more studies deserve attention. By using quarterly data on the United States from 1950 to 1990, Haug (1995) showed that the parameter in the cointegration equation of revenues and expenditures is close to one absolute data are observed, whereas the value is significantly less than one for normalized data. He also found, based on tests of parameter instability in cointegrated systems, that there were no changes in the way fiscal policy was carried out under Ronald Reagan. Payne (1997) tested the existence of cointegration between revenues and expenditures in seven developed countries during different periods of time. The results of his research confirmed the revenue and expenditure cointegration in four countries, of which only Germany had a cointegration vector of [1,-1]. Bravo and Silvestre (2002), by using annual data on 11 EU countries for the period 1960 to 2000, showed that the revenues and expenditures were cointegrated only in 5 countries, often with a cointegration vector other than [1,-1]. Afonso (2004) studied fiscal policy sustainability in 15 EU countries for the period 1970 to 2003 and concluded that a few countries have no problem fulfilling the budgetary constraints. More importantly, he found that the parameter in the cointegration vector indicated a potential problem in future borrowings for all countries. Bohn (2005) showed that, to find a comprehensive approach to testing fiscal sustainability, we need to go beyond testing what he called ad hoc sustainability, which requires only budget constraint fulfilment. He emphasized the assessment of the so-called fiscal reaction function as the best way to achieve such purpose. Neaime (2015) showed that fiscal policy was viable in Germany and France in the period from 1977 to 2013, whereas it was viable in Ireland, Italy, Spain, and Portugal in the 1970s and 1980s; in Greece, fiscal policy was not sustainable in the observed period. Very few empirical scientific papers apply a similar methodology of budget revenue and expenditure cointegration in developing countries, which are similar to the EU candidate countries in terms of economic system characteristics. Barna and Mura (2011) reported fiscal sustainability based on monthly data on Romania for the period 2003 to 2009. Based on data in the period from January 1999 to June 2013, Dornean and Oanea (2015) showed that the fiscal system in Romania tended toward sustainability in the long term. Finaly, the research interest in this topic has not been developed for the EU candidates. Up to our knowledge, there is no scientific paper that covers this topic for any of the EU candidates, with exception of Turkey. Kustepeli and Onel (2005) analyzed the sustainability of budget deficit in Turkey for the period 1970 to 2003. They found the week sustainability of budget deficits. Ucal and Alici (2010) by using monthly data showed that fiscal policy was weakly sustainable for the period 1989 to 2000. Based on the data from the following period 2001 to 2008, they showed strong sustainability of budget deficits. The lack of research in this scientific area for potential EU members has been our main motive for this study.

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Miomir Jaksic, and Milutin Jesic / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 101-115 3. THEORETICAL BACKGROUND

The intertemporal budget constraint of a state can easily be deduced from an equation that represents the budget constraint of the state in a given period, as shown in Eq. 1. * Dt  (1 i)Dt1  ext  revt (1) where D is the public debt; i is the interest rate; ex* are expenditures, excluding interest; and rev are revenues. If we include n periods into the model, we can transform the equation into: * n n revtm extm Dn1 Dt1   m1   m1  n1 (2) m0 (1 i) m0 (1 i) (1 i)

The literature provides numerous variations of this equation depending on whether the n periods are viewed as a finite number or assumed to tend to infinity, whether the interest rate is constant or varies, whether the values are nominal or real. Hakkio and Rush (1991) and Bohn (2007) explained that the interest rate applied in dis- counting depends on how the state revenues and expenditures are measured. If they are measured in absolute nominal amounts, then the nominal interest rate is applied. If they are measured in absolute real amounts, then the real interest rate is applied. The normalization of state revenues and expenditures according to the GDP, or the population, implies the need to subtract the GDP growth rate or population growth rate from the corresponding interest rate. The essence of fulfilling the intertemporal budget constraint is the absence of a Ponzi scheme. That is, if the state acts in accordance with a Ponzi scheme, the debt due will always be replaced with a new debt. This is possible if the equilibrium is dynamically inefficient. In theory, the absence of a Ponzi scheme implies that: D lim n1  0 (3) n (1 i)n1 In this case, the present value of all future primary budget balances will be equal to the current value of the public debt; i.e., subject to the transversality condition, the present value of public debt will converge to 0 in infinity. This can easily be shown to be feasible when the growth rate of the public debt is lower than the interest rate when the data are viewed in absolute terms. If the data are considered in relation to the GDP, it is essential that the GDP growth rate is higher than the interest rate because this requires the so-called solvency condition. Then, the budget constraint is given as: m1 n1 n 1 y  1 y  dt1         dtn   (4) m0  1 i   1 i  In the previous equation, d, y, τ, and ε are the public debt, economic growth, revenues, and expenditures, respectively, normalized to the GDP. If the GDP growth rate is lower than the interest rate, then the budgetary constraint fulfilment, in which the level of public debt is bounded, requires that the last expression in the formula tends to 0 when n tends to infinity. If, however, the state decides to act on the basis of a Ponzi scheme, that situation will not be possible in terms of the finite number of agents that behave rationally. It can be shown that their welfare declines if they would keep the government debt securities in their portfolios. Bearing in mind the form of the budget constraint, special emphasis should be placed on the so-called second-round effect. That is, financing the budget deficit by issuing bonds affects the income, which in the next iteration affects the size of the state revenues. Rau (1985) presented this as function: Y  f H, B, P,G . In the given function, Y, H, B, P, and G are the income, high-powered money, stock of bonds, prices, and government spending, respectively. The partial derivatives of this function with respect to H and G are positive, whereas the partial de-

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Miomir Jaksic, and Milutin Jesic / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 101-115 rivative with respect to P is negative. Of particular interest is the partial derivative of this function with respect to B, the character of which is vague because four effects are present: transfer effect, wealth effect, money market effect, and the Friedman effect. This implies that fiscal responsibility, which is embodied in budget constraint fulfilment, is not a function of one or a few successive periods of time but rather an ongoing process. This also stresses the importance of building and maintaining the credibility of fiscal policy makers.

4. METHODOLOGY Testing the budget constraint fulfilment and the existence of fiscal sustainability in a country can be done in several ways, as reported in the economic literature. These methods primarily test the existence of a unit root in a series of public debt, model the fiscal reaction functions, and test the cointegration between budget revenues and expenditures. Following the methodology presented by Hakkio and Rush (1991) and Quintos (1995), we empirically tested the budgetary balance sustainability, which in theory is derived from the budget constraint fulfilment, based on the test of cointegration between the consolidated revenues and expenditures. Bohn (2007) showed that, if the expenditure is I(m) and the revenue is I(n), where the debt is I(q), the sufficient condition for budget constraint fulfilment does not have to be the cointegration between revenues and expenditures but only the condition that q  maxm,n 1. Ac- cording to Bohn, most authors neglect cases of revenue and expenditure cointegration of a higher order than 1 and believe that cointegration is the necessary and sufficient condition of fiscal sustainability. Although he proved otherwise, however, similarly to many other authors, he ignored the possibility of financing the budget deficit in the way other than borrowing. We opted for the cointegration approach for one methodological and one essentially economic reason. The time series from the fiscal domain in the EU candidates are not long enough for reliable statistical inference, and their disaggregation is often not grounded in economic logic. The core reason for selecting this approach lies in the fact that the public debt in these countries, especially in the observed period, changed not only due to borrowing to cover the budget deficit but also because of some other methods that are less frequent in developed countries. That is, the public debt varied depending on the debt relief from international credi- tors, privatization revenues, and most frequently, the inclusion of certain expenses (those below the line) directly into the public debt. These are all arguments that undermine the economic terms for applying the other two methodological approaches. On the other hand, the cointegration between revenues and expenditures is not an ideal technique, but it is a superior method of testing fiscal sustainability in these countries. More precisely, it tests only one parameter of fiscal sustainability, i.e., budget constraint fulfilment, which is the objective of this paper. The economic logic behind the approach of budget revenue and expenditure cointegration is simple. If the time series of budget revenues and expenditures are nonstationary, the classical approach to econometric modelling is not applicable because the results of such an analysis are not reliable. Thanks to a Nobel Prize winner, C.W.J. Granger, the cointegration concept has become a very useful instrument for analysing multidimensional nonstationary time series. Even if the time series are individually nonstationary, their linear combination can be stationary. This solves the reliability issue of classic modelling under the conditions of nonstationarity and enables viewing the long-term equilibrium relationship between the observed time series. The approach of budget revenue and expenditure cointegration has a solid foundation in a thesis proven by McCallum (1984). According to that thesis, the budget deficit can be completely financed through borrowing, whereas the primary budget deficit cannot be fully financed through borrowing. This leads to two conclusions. First, if the revenues and expenditures are cointegrated with a cointegration vector of [1,-1], then apart from the budget constraint fulfilment and fiscal deficit sustainability, the public debt is also sustainable; i.e., it is bounded. On the other 105

Miomir Jaksic, and Milutin Jesic / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 101-115 hand, the authors that showed public debt sustainability using primary deficit and public debt cointegration approach made a mistake. The empirical testing of intertemporal budget constraint fulfilment requires the transformation shown in Eq. 5, where ex denotes the total budget expenditures (including interest); the * variable G is derived as Gt  ext  (it  i)Dt1 and represents an unconditional mean of the 1 interest rate, whereas   . 1 i

n m1 n1 ext  revt    (revtm  Gtm )  lim  Dtn (5) m0 n Supposing that the last part of the expression in Eq. 5 tends to 0 and that the revenues and expenditures are series with one unit root, then their first differences result in stationary time series. In this case, the fulfilment of the intertemporal budget constraint requires the left side of the equation to be stationary as well; i.e., the linear combination of the revenue and expenditure series should be stationary. The observed cointegration equation has the following form:

rev    ex  et (6) The most comprehensive approach to budget balance sustainability can be found in Afonso (2004). If the revenue and expenditure time series are integrated of order 0, then this is a sufficient condition of sustainability. If both series are I(1), the fiscal sustainability thesis can be confirmed or rejected through the cointegration concept. If one series is I(0) and the other is I(1), then unsustainability is proven. To obtain reliable conclusions, two types of tests of unit root are used: the Augmented Dickey-Fuller (ADF) test and the Kwiatkowski-Phillips-Schmidt-Shin (KPSS) test. The ADF test is based on an examination of the significance of parameter φ in model 7, where the null hypothesis suggests that there is at least one unit root in a series. A model for the revenue time series is presented. An analogue approach is used in the analysis of the expenditure time series. k marks the number of lags required to remove the autocorrelation of residuals by introducing dynamics into the model, and drev denotes the first difference in revenues. We use Akaike Information Criterion for determination of above-mentioned optimal lag length. The given model tests the presence of a unit root in the level of series. In the event of non-rejection of the null hypothesis, the testing is continued to examine in an analogous manner the presence of a unit root in the series first difference.

k drev  1   2t  rev(1)   drev(i) (7) i1 To ensure the reliability of the conclusions, the analysis also applies the KPSS test, according to the null hypothesis asserts that there is no unit root in the time series. Let us begin with the following model:

revt  rev0 t  ut , t=1,...,T (8)

Let us assume that ut has one unit root. In this case, the model can be presented in the following way:

T revt  rev0 t   vt (9) t1 In essence, this test is based on the answer to the question of whether the variance of the random error of the model Var(vt) is equal to 0. We assumed a linear decline of correlation over time; thus, the Bartlett kernel is used. An analogue approach was used to test the expenditure series. 106

Miomir Jaksic, and Milutin Jesic / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 101-115 Because the above-mentioned tests of unit root are extremely sensitive to the existence of deterministic components in the time series movement, it is important to identify which deterministic components should be used in the analysis. This is done based on visual examination and the Stock-Watson test, which is carried out by regressing the first difference in the revenue and expenditure series on the constant. To remove autocorrelation, dynamics are introduced into the model. The purpose of this test is to verify the significance of the constant in that auxil- iary regression. The rejection of the null hypothesis in this test justifies the inclusion of the constant and trend as deterministic components when testing series for unit root presence. Other- wise, the trend should be excluded from the model and these tests have to be repeated by using only constant as deterministic component. Finally, to test the presence of cointegration between the two series previously mentioned, we use the Johansen test of cointegration. This test is of two types: one is based on trace statistics, and the other on the maximum value of eigen statistics. The first type starts from the null hypothesis that the number of cointegration relations is equal to or less than r. The alternative hypothesis suggests that this number is different from r. The second test starts from the null hypothesis that the number of cointegration relations is equal to r, whereas the alternative hypothesis states that the number is equivalent to r+1. The number of lags is determined based on a VAR model, considering the multidimensional information criterions (Akaike Information criterion (AIC), Schwarz Information criterion (SC) and Hannan-Quinn Information Criterion (HQ)) and the necessary checking of the autocorrelation of residuals by using the Portmanteau test and multidimensional Breusch-Godfrey test. Deterministic components can be involved in Johansen procedure in five ways, which are sorted by their restrictiveness. First case starts with the assumption of deterministic components nonexistence. Second case assumes restricted constant in the cointegration space, but does not allow trend in the data. Third case allows linear trend in the data, additionally. Forth case assumes linear trend in the cointegration space. Fifth case provides the minimum of restrictiveness, because it allows quadratic trend in the data. Based on the above-mentioned analysis, we provide the results and their interpretation, taking into account the fact that the EU candidates are developing countries, and thus budget constraint fulfilment does not necessarily imply fiscal sustainability in the previously defined manner. For developing countries with persistent budget deficits, a case of weak fiscal sustainability is especially relevant. If the coefficient β in the cointegration vector [1,-β] is less than 1, then there is no strong sustainability but rather weak fiscal sustainability. Hakkio and Rush (1991) showed that even when the cointegration vector is not [1,-1], the intertemporal constraint can be fulfilled. If β moves at the interval (0,1), and Dt+n is defined as shown in Eq. 10, * then the last expression in this equation tends to 0, where St  (1  )ext  .

n nk n Dtn   (1 (1  )i) Stk  (1 (1  )i) Dt1 (10) k0 This means that the intertemporal budget constraint is fulfilled, but the undiscounted value of the public debt tends to infinity. Our task is to confirm the hypothesis on fiscal sustainability in the EU candidate countries, with special emphasis on the coefficient β.

5. DATA The data on the consolidated budget revenues and expenditures for Albania, Serbia and Turkey were taken from the websites of the Central Banks and Ministries of Finance of these countries. Unfortunately, the observed time series in other two candidate countries FYRM and Montenegro are too short for valid statistical inference and conclusions about fiscal responsibil-

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Miomir Jaksic, and Milutin Jesic / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 101-115 ity, so we decided to exclude these countries from the observed panel. Detailed information on the data can be found in the Appendix A of this paper. The literature cites various approaches regarding the type of data used in the analysis. The data are either in absolute values or in relative values in terms of GDP or per capita. In addition, the data may be nominal or real. The decision of the researchers depends on their research objectives. In the case of the observed EU candidates, we believe that the nominal data in absolute values provide the best basis for analysis. However, the lack of reliable data on the GDP, changes in the method of calculating the GDP, and the relatively short period of observation led us to opt for the absolute values. On the other hand, by excluding the impact of inflation, we would neglect the influence of monetary policy and the possible coordination between monetary and fiscal policy. In particular, because all the observed countries have their own currency, unlike other countries in which similar research has been done, their central bank has more room to maneuver in managing monetary policy. We observed the time series on a monthly basis. The samples for the observed countries are not the same length, due to the deficiency of the data. Because the observed time series showed distinctive seasonal variations, we de-seasonalized the data by using the CENSUS X12 method. Hereafter, for the purpose of simplification, we will use the terms revenues and expenditures without the attributes “de-seasonalized” and “consolidated”. After this transformation, the foundations for further empirical analysis were set.

6. EMPIRICAL FINDINGS AND ECONOMIC INTERPRETATION To verify empirically the thesis on the fiscal sustainability in the observed EU candidates, we primarily investigated the existence of unit roots in the observed series of revenues and expenditures. The results of the ADF unit root test showed that the revenues and expenditures series are I(1) for all countries.

Table 1. Results of the ADF unit root test

Level First difference

estimated critical estimated critical country variable ADF(k) sta- lags values ADF(k) lags values tistic (5%) statistic (5%)

rev [c] -1.9320 7 -2.8906 -6.1645 6 -2.8906 Albania ex [c] -2.0052 3 -2.8895 -7.9676 3 -2.8898 rev [c, t] -2.6265 5 -3.4497 -8.8640 4 -3.4497 Serbia ex [c, t] -3.4029 3 -3.4490 -8.1571 3 -3.4493 rev [c, t] -1.2346 8 -3.4546 -6.2607 7 -3.4545 Turkey ex [c, t] -1.7004 5 -3.4532 -10.2462 4 -3.4532

Notes: Deterministic components are shown in the brackets in the column named variable. These components are c which stands for constant and t which stands for trend; Lag lengths are based on AIC; Critical values are based on MacKinnon (1991).

Source: Author’s calculation

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Similarly to the previous test, the KPSS unit root test also showed that all the variables are I(1). That is, the application of the test on the levels of series indicated that the series have at least one unit root, whereas the use of the LM statistics of this test applied on the first differences of the series showed that there is no sufficient evidence to discard the null hypothesis of unit root nonexistence.

Table 2. Results of the KPSS unit root test

level First difference

critical country variable LM statistic LM statistic values (5%)

rev [c] 0.6603 0.1624 0.4630 Albania ex [c] 0.8909 0.1753 0.4630 rev [c, t] 0.1933 0.1169 0.1460 Serbia ex [c, t] 0.2172 0.1174 0.1460 rev [c, t] 0.5326 0.0394 0.1460 Turkey ex [c, t] 0.5408 0.0434 0.1460 Notes: Deterministic components are shown in the brackets in the column named variable. These components are c which stands for constant and t which stands for trend; The critical values are based on Kwiatkowski et al. (1992)

Source: Author’s calculation

The justification of the use of the above-presented unit root test modalities, with inclusion of different deterministic components, was investigated by visual examination of the series and with the help of formal test. Table 3 shows a summary of the results of the Stock-Watson test. The free member in the cases of Serbia and Turkey is statistically significant. Therefore, we can conclude that when testing the presence of unit roots in revenue and expenditure series, it is necessary to use both the constant and the trend as deterministic components. In contrast with that, following the results of this test, we used only constant as deterministic component in the case of Albania.

Table 3. Test of the adequacy of deterministic components

country variable coefficient c t value p value lags rev 206.5259 1.2764 0.2047 2 Albania ex 459.9144 1.2559 0.2121 3 rev 2428.1200 * 4.0637 0.0001 4 Serbia ex 3085.8810 * 3.8507 0.0002 5 rev 901.3836 * 3.8384 0.0002 5 Turkey ex 1120.6440 * 5.1134 0.0000 5 Notes: * Denotes significance at the 5% level;

Source: Author’s calculation. 109

Miomir Jaksic, and Milutin Jesic / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 101-115 We finished the first step of the analysis with the conclusion that all series have exactly one unit root. After determining the integration level of the budget revenue and expenditure series, all the necessary terms for the cointegration test are obtained. Because both the revenue and expenditure series are I(1) in all countries, there is a possibility that their linear combination is I(0). The answer to this question is given by two variants of the Johansen cointegration test. More details about the procedure of lag length choice can be found in Appendix B. In accordance with the data, we will focus on two cases of deterministic component inclusion. In cases where we could not determine the linear trend in data, we used Johansen recommendation to involve only constant in the cointegration space. On the other hand, in cases where we could find the significance of the trend in the data, we allowed linear trend in the data. This case allows linear trends to enter the VECM as drift (Ahking 2002, p. 55).

Table 4. Results of the Johansen cointegration test

Cointegration Rank Test (Maximum Eigen- Cointegration Rank Test (Trace) value)

country No. of cointe- trace statis- critical No. of cointe- max-eigen critical gration eqn(s) tic value gration eqn(s) statistic value

H0: r≤0; H1: H0: r=0; H1: Albania 19.2177 20.2618 12.8592 15.8921 r≠0 r=1

H0: r≤0; H1: H0: r=0; 26.6670 * 15.4947 24.0915 * 14.2646 r≠0 H1: r=1 Serbia H0: r≤1; H1: H0: r=1; H1: 2.5756 3.8415 2.5755 3.8415 r≠1 r=2

H0: r≤0; H1: H0: r=0; Turkey 12.5623 15.4947 8.0266 14.2646 r≠0 H1: r=1

Notes: We assume no deterministic trend in the data and restricted constant in the cointegration space for Albania. For Serbia and Turkey, we allow for linear trend in the data, but no trend in the cointegration space; Lag lengths are 6,5 and 5 for Albania, Serbia and Turkey, respectively; * Denotes statistical significance at the 5% level; Lag lengths are chosen based on the VAR model.

Source: Author’s calculation.

The results of the Johansen cointegration test clearly showed one stationary linear combination of revenues and expenditures in Serbia, thus supporting fiscal sustainability. We could not determine the existence of cointegration between these variables by Johansen test in Alba- nia and Turkey for the observed periods. However, our analysis also aimed to examine which form of budget sustainability is immanent in Serbia. That is, value of the parameter β in the cointegration equation should discriminate between the hypothesis of a strong form of sustain-

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Miomir Jaksic, and Milutin Jesic / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 101-115 ability versus the alternative of a weak form of sustainability. The restriction of these coefficients to a value of 1 was statistically tested.

Table 5. Test results on the strength of budget deficit sustainability

country β standard error t-statistic critical value Serbia 0.7520 0.0150 -16.5333 -1.9808

Source: Author’s calculation.

We conclude that the value of the coefficient β is significantly different from 1, which means that in the period from February 2005 to January 2015 in Serbia, budget sustainability was weak. Although the time series of revenues and expenditures are cointegrated, i.e., the budget constraint is fulfilled, the cointegration vector is not [1,-1]; thus, the budget expenditures were growing faster than the budget revenues in the said period. Specifically, for every 1,000,000 Serbian dinars of budget expenditure growth, the budget revenues grew by only 752,000 dinars in average. This conclusion certainly has significant consequences on the overall fiscal sustainability in countires that are potential EU members. Budget constraint fulfilment is the most important factor, but not the only one, in attaining total fiscal sustainability. The persistent budget deficits, lack of cointegration between revenues and expenditures in Albania and Turkey and the calculated value of the parameter β in Serbia, clearly indicate that the public debts of these countries are on a potentially unsustainable path. We suggest the necessity of exploring other factors affecting the sustainability of public debt, most importantly the method of financing the budget deficit; the currency, term, and interest structure of the public debt; the movement of the GDP; and the proportion of external debt to the total public debt, among others. If all this is strengthened by pronounced impact of political business cycles in these countries, then there are even more reasons for concern. EU candidate countries are not signatories of European Union trea- ties that put accent on the fiscal responsibility. Therefore, fiscal responsibility in these countries is dependent on their own fiscal rules. For these reasons, it is important for EU candidates to keep their structural budget deficit within sustainable levels, to ease the burden of interest payments through public debt management, and to apply growth and development strategies to make the deficit and debt less of a burden in relative terms.

7. CONCLUSION

Never before has fiscal responsibility been so frequently mentioned in the economic literature as in recent years. The public debt crisis in many countries has raised a number of questions that policy makers, with the help of the scientific community, need to answer. The status of public finance in many countries requires a deep analysis and review of the way fiscal policy is currently carried out, with the goal of putting as much emphasis as possible on long- term fiscal sustainability in the future. We believe that budget constraint fulfilment is the key factor, but not the only one, in achieving fiscal sustainability. In the short term, many anomalies can break this link. Therefore, we consider the analysis of fiscal sustainability to be much broader than mere examination of the budget constraint fulfilment. In the long run, this relationship becomes stronger in terms of macroeconomic stability. In theory, budget constraint fulfilment implies the absence of a Ponzi

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Miomir Jaksic, and Milutin Jesic / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 101-115 scheme. However, this theoretical concept is not easy to verify empirically, although empirical research on this topic has flourished since the 1980s. One of the most comprehensive approaches to this problem is the analysis of budget revenue and expenditure cointegration. This approach was used in our analysis of the fiscal responsibility in the EU candidate countries, because it has advantages in comparison with other methods of fiscal sustainability accession. Unfortunaltely, we could not find statistical evidence of cointegration between revenues and expenditures in Albania and Turkey. In contrast with that, we showed the cointegration of budget revenues and expenditures in Serbia. This is an important signal toward fiscal sustainability. However, the signal is not strong enough because the cointegration vector of revenues and expenditures Serbia showed a value of [1,- 0.7520]. Therefore, we conclude that there is weak fiscal sustainability in these two countries. The consequences of this conclusion are numerous and valid for all observed countries. Uncertainty can easily turn small economic shocks into large ones that can affect fiscal and consequently macroeconomic stability. Therefore, it is necessary to implement structural reforms in the public finance area in the coming years. Further, fiscal sustainability should be examined in greater depth. This paper is the starting point for such future works.

APPENDIX

A. Data summary

In table A1, we provided information on the raw data.

Table A1. Basic characteristics of the data

country data series length total obs. source of the data

Bank of Albania (according consolidated government 2006 (M2) to Albania 108 to the Ministry of Finance revenues and expeditures 2015 (M1) data)

National Bank of Serbia consolidated government 2005 (M2) to Serbia 120 (according to the Ministry revenues and expeditures 2015 (M1) of Finance data)

central government con- 2006 (M1) to Turkey solidated revenues and 111 Ministry of Finance 2015 (M3) expeditures Notes: Links to the data are presented in the Reference list.

In the following figures, we presented de-seasonalized series of revenues and expenditures across the countries.

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Figure A1. De-seasonalized consolidated revenues and expenditures in Albania

60000

50000

40000

30000

20000

10000

0 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

rev ex

Notes: Revenues and expenditures are presented in millions of Lek.

Source: Author’s calculation.

Figure A2. De-seasonalized consolidated revenues and expenditures in Serbia

250000

200000

150000

100000

50000

0 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

rev ex

Notes: Revenues and expenditures are presented in millions of Dinars.

Source: Author’s calculation.

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Miomir Jaksic, and Milutin Jesic / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 101-115 Figure A3. De-seasonalized consolidated revenues and expenditures in Turkey

45000 40000 35000 30000 25000 20000 15000 10000 5000 0 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

rev ex

Notes: Revenues and expenditures are presented in millions of Lira.

Source: Author’s calculation.

B. The choice of optimal lag length in Johansen test

Since Johansen test is very sensitive to variations of lag length, we put special attention on the optimal lag length choice. The lag length is primarly based on the information criterions in VAR model. This first step is associated with tests of autocorrelations in order to select the optimal lag length. Portmanteau test starts from the null hypothesis that there are no residual correlations up to a lag η. On the other hand, Breusch-Godfrey test is reliable on testing the short lag residual autocorrelations and investigates the presence of autocorrelation at lag of η order. The number of lags used in Johansen test is equal to the number of lags for the VAR model minus one, because the model is now based on the first differences.

Table B1. The summary of lag length choice procedure

country AIC SC HQ optimal lag length Albania 3 3 3 7 Serbia 3 3 3 6 Turkey 6 3 6 6 Notes: Optimal lag lengths are chosen after the necessary checking for autocorrelation by Portmanteau and Breusch – Godfrey test.

Source: Author’s calculation.

REFERENCES Afonso, A. (2004), “Fiscal Sustainability: The Unpleasant European Case”, Paper presented at Money, Macro and Finance Research Group Conference, Cass Business School, London. Ahking, W. F. (2002), “Model Mis-specification and Johansen’s Co-integration Analysis: An Ap- plication to US Money Demand”, Journal of Macroeconomics, Vol. 24, No. 1, 51-66.

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Miomir Jaksic, and Milutin Jesic / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 101-115 Bank of Albania statistical data, http://www.bankofalbania.org/web/Time_series_ 22_2.php? evn=agregate_detaje&evb=agregate&cregtab_id=648&periudha_id=1 (accessed July 7, 2015) Barna, F., Mura, O. (2011), “Fiscal-Budget Policy Sustainability in Romania (2003-2009)”, Petro- leum – Gas University of Ploiesti Bulletin, Vol. 63, No. 1, 65-72. Bohn, H. (2005), “The Sustainability of Fiscal Policy in the United States”, working paper, CESifo No 1446. Bohn, H. (2007), “Are Stationarity and Cointegration Restrictions Really Necessary for the In- tertemporal Budget Constraint”, Journal of Monetary Economics, Vol. 54, No. 7, 1837- 1847. Brada, J. and Kutan, A. (2002), “Balkan and Mediterranean Candidates for European Union Membership: The Convergence of Their Monetary Policy with That of the European Central Bank”, Eastern European Economics, Vol. 40, No. 4, 31-44. Bravo, A. and Silvestre, A. (2002), “Intertemporal Sustainability of Fiscal Policies: Some Tests for European Countries”, European Journal of Political Economy, Vol. 18, No. 3, 517-528. Dornean, A. and Oanea, D.C. (2015), “Romanian Fiscal Policy Sustainability during Financial Crisis: A Cointegration Approach”, Procedia Economics and Finance, Vol. 20, 163-170. Hakkio, S.C. and Rush, M. (1991), “Is the Budget Deficit “too Large”?”, Economic Inquiry, Vol. 29, No. 3, 429-445. Haug, A.A. (1995), “Has Federal Budget Policy Changed in Recent Years?”, Economic Inquiry, Vol. 33, No 1, 104-118. Jesic, M. (2013), “Implications of Fiscal Irresponsibility on Financial Stability”, Journal of Central Banking Theory and Practice, Vol. 2, No. 3, 111-138. Kustepeli, Y. and Gulcan, O. (2005), “Fiscal Deficit Sustainability with a Structural Break: An Application to Turkey”, Review of Social, Economic and Business Studies, Vol. 5, No. 6, 189-208. Kwiatkowski, D.; Phillips, P.; Schmidt, P.; and Shin, Y. (1992), “Testing the Null Hypothesis of Stationarity against the Alternative of a Unit Root”, Journal of Econometrics, Vol. 54, No. 1- 3, 159-178. MacKinnon, J. (1991), “Critical Values for Cointegration Tests“, In Engle, R.F. (Ed.) and Granger, C.W.J. (Ed.), Long Run Economic Relationship: Readings in Cointegration, Oxford University Press, Oxford, 267-276. McCallum, B. (1984), “Are Bond-Financed Deficits Inflationary? A Ricardian Analysis“, Journal of Political Economy, Vol. 92, No. 1, 123-135. Ministry of Finance of Turkey statistical data (accessed July 7, 2015) http://portal.muhase- bat.gov.tr/mgmportal/faces/khbDetail?birimDizini=Central+Government&_afrLoop=36948 9762538400&_afrWindowMode=0&_adf.ctrl-state=96cf4td3w_4 National Bank of Serbia statistical data http://www.nbs.rs/internet/english/80/index.html (accessed July 7, 2015) Neaime, S. (2015), “Sustainability of Budget Deficits and Public Debt in Selected European Un- ion Countries”, The Journal of Economic Asymmetries, Vol. 12, No. 1, 1-21. Payne, E.J. (1997), “International Evidence on the Sustainability of Budget Deficits”, Applied Economic Letters, Vol 4, No. 12, 775-779. Quintos, E.C. (1995), “Sustainability of Deficit Process with Structural Shifts”, Journal of Busi- ness and Economic Statistics, Vol. 13, No. 4, 409-417. Rau, N. (1985), “Simplifying the Theory of the Government Budget Restraint”, Oxford Economic Papers, New Series, Vol. 37, No. 2, 210-229. Trehan, B. and Walsh, C. (1988), “Common Trends, the Government’s Budget Constraint, and Revenue Smoothing”, Journal of Economic Dynamics and Control, Vol.12, No. 2-3, 425- 444. Ucal, M. and Alici, A. (2010), “Is Fiscal Policy Sustainable in Turkey?”, Emerging Markets Fi- nance and Trade, Vol. 46, sup. 1, 83-93.

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Montenegrin Journal of Economics

Vol. 12, No. 2 (2016), 117-129 ‘

Different Values Forms in Organization: is the Congruence Possible?

Jolita Vveinhardt1, Evelina Gulbovaitė2, and Dalia Streimikiene3

1 Professor, Ph.D., Chief Researcher, Lithuanian Sports University, Institute of Sport Science and Innovations, Kaunas, Lithuania; [email protected] 2 PhD student, Faculty of Economics and Management, Vytautas Magnus University, Lithuania; e-mail: [email protected] 3 Full Professor, Ph.D., Chief Researcher, Lithuanian Sports University, Institute of Sport Science and Innovations, Kaunas, Lithuania; e-mail: [email protected]

ARTICLE INFO ABSTRACT Received March 21, 2016 The organizations especially actively declaring the importance of Received in revised form – May, 12 2016 values quite often have not even diagnosed this phenomenon in Accepted June 12, 2016 their environment. The organizations often invite external ex- Available online June, 15, 2016 perts, expecting to purify and implement organizational values, but declaration of values and their opposite reflection in the JEL classification: employees’ behaviour show that the identified, but unimple- M12, L20 Z00 mented values of the organization remain only a formal document, a part of the image of the organization that, however, has DOI: nothing to do with the general activities of the organization. Dif- ferent forms of values exist in organizations, but we tend to uni- 10.14254/1800-5845.2016/12-1/8 form them, and speak only as about organizational values or values of the organization in a general sense, but no more. The Keywords: problem is that the different forms arise from different subjects, values, and the objective is that the congruence would occur between personal values, the different forms of values. Therefore, the aim of the current organizational values, paper is to clarify the concept of values forms in organization and value congruence, highlight the perspective of these values congruence. Based on values alignment the analysis of the different forms of values distinguished in scientific literature, five most frequently encountered and discussed forms of values can be identified: core, espoused, attributed, shared and aspirational. The detailed analysis of forms of values in the organization shows that the congruence of these different forms of values is possible, but the activities of the organization in order to uniform the values must be particularly purposeful and targeted, and the first step is to find out those values. As the congruence occurs when the executives’ espoused values match the employees’ attributed values, they are shared and they go along with the core cultural values of the organization.

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1. INTRODUCTION In recent decades, theorists and practitioners particularly often use the terms “organizational culture”, “mission” and “values”. They also increasingly talk about the “value congruence” phenomenon in the organization. These terms are built into the language of the organization, among other terms that have been used in organizations for a long time. In order to answer the question of how organizational values can serve to enhance the results of the organization and how to evaluate the benefits of organizational values, we could cite the results of studies carried out by various researchers. However, to imagine how we would just recall the inspiration/enthusiasm we work with when we work “as for ourselves” would be more convincing than the specific calculations. And then another question arises: what does it depend on and what the circumstances allow us to feel good, and maybe even happy, and how to create such environment in the organization? Many executives understand that involvement of employees, their initiative and participation in the development of the organization can be the prerequisite for the successful existence of the organization. Executives constantly consider (or at least they should do so), raising the question of the main ways to achieve this in the organization. However, neither the development of the “correct” strategy, structure, nor the investment in the abundance of motivational means “inspire” the employees to be suchlike. Therefore, modern leaders began to focus on the values of the organization. Now, many organizations have formulated their values. However, quite often there is a danger here: there is a list of values and perhaps they are known for employees, but are they really followed in the organization? Are the values “obligatory” for all the employees? Can values be “obligatory” at all? What personal example is shown by the top-level management of the organization? The question is what the employee trusts more – the list of values, given during the employment, or what he sees in reality on a daily basis in the organization? The new employee is watching and making his own conclusions. Unwritten rules of conduct exist in the organization in addition to the written values, and every individual has his/her own personal system of values. These questions presuppose the assumption that there is not the only form of values in the organization and it occurs due to the different subjects participating in the activities of the organization that implicate individual values. Understanding the importance of value congruence within the organization, there raises the question of whether it is possible to ensure, and if possible, how to ensure congruence between different forms of values? Thus the aim of the current paper is to clarify the concept of values in organization and to highlight the perspective of these values congruence.

2. PHENOMENON OF PERSONAL AND ORGANIZATIONAL VALUES Both the dilemmas of personal and organizational values and their harmonization are increasingly often in researchers’ papers, therefore, there is a large body of literature touting the importance of values in organizations. In terms of values, no matter what level they belong to – the organization, the person, or the society, values can be defined as concepts or principles that transcend specific situations and guide the selection or evaluation of behavior and events (Schwartz, 2012). Speaking about values at the organizational level, the term “organizational values” is an established concept in today’s management literature. The pragmatic view stemming from systems theory treats organizational values system as a managerial instrument (Mowles, 2008) and management control mechanism to effect organizational change by es- pousing a new set of normative values which should inform managers’ decisions and actions, particularly in trade-off situations (Marginson, 2009). Just like every human community has its own value system, every organization hats its own value system (Kenny, 1994).

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Jolita Vveinhardt, Evelina Gulbovaitė, and Dalia Streimikiene / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 117-129 Values in personal level represent basic needs and motivations, which may influence people’s choices and behavior (Schwartz, 1992; Verplanken and Holland, 2002), thus organizational values affect an organization’s fundamental mindset by reinforcing or rejecting the basic assumptions that determine behavior (Michailova and Minbaeva, 2012). Organization's values provide an elaborate and generalized justification both for appropriate behaviors of members and for the activities and functions of the system (Chatman, 1989). These values are integrated into personality of an organization thus playing a similar role as do in lives of individuals: direct- ing behavioral patterns, influencing relationships within the organization and influencing how company perceives its customers, suppliers and competition (Gorenak and Kosir, 2012). Therefore, values have a long reach and a wide span of influence on critical processes and characteristics in organizations (Bourne and Jenkins 2013). Albeit different definitions, the heart of organizational values rests in its ability to guide and influence the choices, priorities, actions, and attitudes of the organization and its members (Chatman, 1989; Williams, 2002) and the role of values is first and foremost to regulate employee behavior and to achieve superior performance (Jaakson, 2010). In the ideal case, organizational values are embedded in organizational myths, stories, slogans, mission and vision statements, annual reports, physical design of premises and all the content available on organization’s website, as well as in all the decisions made by the organization (Atkinson, 2003; Shockley-Zalabak, 2009). Failure to understand where values fit in an organization’s structure and culture is a significant factor in the inability of so many organizations to live their values successfully (Henderson and Thompson 2003). Having understood the benefits of values, organizational values are increasingly being used in practice to stimulate, and enforce, the alignment of behaviors (Quappe et al., 2007). Therefore number of empirical studies have sought to understand the relationship between organization’s values and the organization's actions and practices (Garza and Mor- geson 2012). Although research has typically focused on the relationship between organizational values and employee attitudes and behaviors (Johnson and Jackson 2009). However, in recent decades, the studies of congruence between personal and organizational values rather than of the values of the organization become more relevant. Research shows that where the organization cultivates alignment between organizational and individual values, which is called value congruence in academic literature, it induces more positive employee attitudes such as organizational commitment and job satisfaction (O’Reilly et al., 1991; Silverthorne, 2004; Osftroff et al., 2005; Cennamo and Gardner, 2008; Posner, 2010; Leung and Chaturvedi 2011), organizational identification (Edwards and Cable 2009) et al. But when we speak about separate values: those of an individual and an organization and the congruence of values of the two subjects, carry out research and vary these notions/terms in other ways, do we realize whose value congruence we estimate well enough? The truth is of the employees and the organization. But whose values does the organization stand on as a whole? On the values generally declared by the organization, values formed by the management, personal or the most acceptable to all the members of the organization? Thus, if the question is what subject the organizational values are assigned to, it is natural that this presupposes the assumption that there are different values in the organization itself. Although the values construct is widely evoked in organizational literature, but tends to be compromised by lax conceptualization so that the progress of values research continues to be con- strained by the lack of a common theoretical basis (Stackman et al., 2000). It happens, because individuals’ values and values of organizations espouse may differ from what they practice (Schein, 1985). Values are specific to an individual and they only reside in the mind of that person (Branson, 2008), so even assuming consistency between values that are espoused and practiced, individuals within organizations may be confronted with mutually exclusive values (Liedtka, 1991). Not to mention the fact that an individual may hold values that are in conflict across different sources of values or the content of values (Paarlberg and Perry, 2007).

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Jolita Vveinhardt, Evelina Gulbovaitė, and Dalia Streimikiene / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 117-129 Thus, the question arises whether, in general, the value congruence can be achieved, if there are different forms of values, their sources of origin in the organization. Is it possible, and if so, how and in what ways to compare values in a meaningful way? How to ensure that these different forms of values are all the same thing and how they could be working against each other? In this way ‘values thing’ is rather complicated. Usually organizations publish their values on the websites, declare the importance of certain values to the consumers of the organization, but often actions of the organizations are contradictory to the declared values. What is displayed graven on the plate of values does not correspond to the way the organizations live. And often when you ask an employee, what are the values of the organization he works for, he/she cannot define them clearly. Therefore, if executives of organizations understood and estimated the importance of different values, it would become easier to evaluate the real situation between where the organization is and what it aims at, particularly in terms of congruence between personal and organizational values.

3. OCCURRENCE OF DIFFERENT FORMS OF VALUES IN THE ORGANIZATION The authors identify different forms of values prevailing in the organization. Lencioni (2002), Bourne (2013) and Jaakson (2010) examined in detail, what the possible/prevailing forms of values in the organization are and the links they may have with each other. Although while a number of theoretical models incorporate organizational values, gaps remain in understanding their dynamics, thus a careful exploration of the concept, however uncovers differences indicating that organizational values adopt a number of forms (Bourne and Jenkins, 2013). Distinguishing and understanding different forms of values in the organization is essential, because if an organization is not aware of what forms of values they are mediating the consequences can be that management are communicating values that does not exist, or values they only wish they had. According to Lencioni (2002) there are four forms of organizational values - accidental, aspiration, permission-to-play and core values. Bourne and Jenkins, (2013) also have discerned four distinct forms of values in organization - espoused, attributed, shared and aspirational, but they explain these forms of values by their importance and reasons of formation slightly differently than Lencioni (2002). Jaakson (2010) alongside the values distinguished by Bourne and Jenkins (2013) also distinguishes organizational core values, as well as Lencioni (2002). The differences between these different approaches to the forms of values in the organization are confusing, as well as the concept of values and approach towards them. When analysing the papers of different authors, it should be noted that each of them has his/her own expertise. Lencioni (2002) notes the significance of core values and their difference from other forms of values. Jaakson (2010) provides a thorough and comprehensive review of the forms of values and explains their layers/levels. Bourne and Jenkins (2013) present the concept of values forms in 2 x 2 system in which the values are grouped into collective vs. aggregate and embedded vs. intended. According to Williams (1960), Bourne and Jenkins (2013) a group or organization’s values may refer both to those that are presently held in common, and to those that it intends to reach in future. Also Bourne and Jenkins (2013) state, that organizational values may be understood at different levels. Although the system proposed by Bourne and Jenkins appears to be quite clear and logical, it is possible to do additional insights based on the approaches towards the forms of values proposed by Lencioni (2002) and Jaak- son (2010). Bourne and Jenkins (2013) do not analyse the detailed review on the values of the organization made by Jaakson (2010). Therefore, it is appropriate to note that there is another extremely important and expressed form of values of the organization – core values, discussed both by Lencioni (2002) and Jaakson (2010). On the basis of the divisions of values made by the authors analyzed above (Lencioni, 2002; Jaakson, 2010; Bourne and Jenkins, 2013), five different forms of values that occur in

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Jolita Vveinhardt, Evelina Gulbovaitė, and Dalia Streimikiene / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 117-129 the organization will be presented and compared, and the prospect of congruence of these different forms in the organization will be assessed: espoused, shared, attributed, core and aspirational value. Espoused values clearly represent the value consensus among an organization’s senior managers (Kabanoff et al., 1995). These values are formally espoused and sanctioned by top managers in the words and phrases they employ (Kabanoff et al., 1995; Bourne and Jenkins, 2013) through verbal or written statements and formal documents and often presumes and represent as organizational values (Bansal, 2003). Espoused values, although other researchers identify these values as “stated values” or “principles” are typically stated in writing for all members of the organization, and are shared with other stakeholders, including the general public (Jaakson, 2010). It has been argued, however, that the majority of values statements today are empty, or what Lencioni (2002) calls bland, toothless, or just plain dishonest and such values statements are ineffective, costly, and even destructive, because values statements is only the tip of the iceberg when it comes to organizational values in operation – just a fraction of those made visible to everyone (Jaakson, 2010). Top managers may formally espouse values that they believe should be the basis for decisions and actions, but that does not necessarily mean that these equate to organizational values (Bourne and Jenkins 2013). Just by being advocated by the organizations and by communicating it through other more visible aspects of organizational culture these values will not lead to the desired behavior and the fact that values are articulated in annual reports, strategic plans and/or mission statements does not necessarily result in actual behavior (Michailova and Minbaeva, 2012). Moreover, Hofstede (1998) argues that organizational practices, originally established by founders and later modified by succeeding top managers, are based on values not necessarily shared by organization members, who have to follow the practices if they want to remain members, but they do not have to confess to the values. If people within an organization do not authentically support the collective’s values, then the organization cannot implement these values (Henderson and Thompson 2003). Espoused values emerge from the underlying assumptions to which organizational members subscribe, and while they may predict what people will say, they may differ from what people actually do (Argyris and Schon, 1978). Thus, espoused values carry considerable weight in organizations, but to consider them as a valid representation of the entirety of organizational values is problematic (Bourne and Jenkins 2013). Empty values statements create cynical and dispirited employees and undermine managerial credibility (Lencioni, 2002). Especially it is highly problematic when values manifested in the statement are in conflict with actual values or basic underlying assumptions, but one should be aware that the pool of organizational values is probably much wider and complex than reflected by the statement Jaakson (2010). Differently from espoused values core values need not be explicitly stated in written documents, although they typically are a result of a dispute that has taken place in the organization about the relevant values (Jaakson, 2010). Organization’s core values are individual values that are inconsistent with their daily work (Collins, 1996). Collins and Porras (1998) has described it as the organization’s essential and enduring code of beliefs, a small set of timeless guiding principles that require no external justification. These form of values are standards and criteria for choosing goals and actions and, as such, they are the essence of organizational culture (O’Reilly et al., 1991). Core values are the deeply ingrained principles that govern all the organization’s actions and they are the source of organization’s distinctiveness that must never be compromised Lencioni (2002). Core values are used to denote highly congruent values between organizational members as well as between the organization and its members (Liedtka, 1989; Jehn, 1994) and as such, these refer to at least some overlap between what is actually believed and what is said to be believe in (Jaakson, 2010).

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Jolita Vveinhardt, Evelina Gulbovaitė, and Dalia Streimikiene / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 117-129 Many companies make the mistake of picking core values out of thin air and trying to fit them into their organization. Collins (1996) states, that organizational values could not be “set”, they can only be “discovered” and new core values could not be “installed” into people. Core values are timeless and do not change. In many cases, core values are seen as purely aspirational rather than real, hard-edged principles to which the organization wholeheartedly commits itself. If there is a disconnect between your organization’s stated core values and the behavior of its decision-makers, it’s probable that the values are simply aspirational. Finegan (2000) defined organizational values in terms of their perceived importance to the organization by its members. So there may be overlap with the values espoused by senior managers, but it is not necessarily the case (Bourne and Jenkins, 2013). According to Pruzan’s (2001) that because they underlie decisions, they are differentiated from those that may be espoused but not enacted. Organization’s values that are described and regarded as representative of the organization by its members are called attributed values (Balazs, 1990; Pruzan 2001). Members attribute the values that characterize their organization through the patterns they observe in day-to-day actions (Bourne and Jenkins 2013). While members may recognize attributed values as being characteristic of the organization, and although those members may also identify with the organization, it does not necessarily follow that they share these values (Ashforth and Mael 1989; Hofstede, 1998). Attributed values therefore represent the history of the organization, but do not typically hold aspirations or intentions for the future (Bourne and Jenkins 2013). A number of scholars adopt the attributed values form, particularly when using values as a variable in assessing person-organization fit (Kristof, 1996). In contrast to espoused values, shared values do not have to be explicitly stated, and in contrast to core values they might be unconscious (Jaakson, 2010). The shared values form positions organizational values as an aggregation of the values of its members (Bourne and Jenkins, 2013). Members are generally able to identify shared organizational values, at least within their immediate work groups (Schein, 1985). Wiener (1988), who states that the shared values of organizational members constitute an organizational value system, its breadth measured by the proportion of members who share the values, and its intensity by the importance with which a value is held in relation to other shared values. Sharing with the organization is a subjective fit of personal values typically with either espoused or attributed values (Bourne and Jenkins 2013). Fit with the organization’s values corresponds to fit with the prevailing values of other members, leading over time and in stable environments to increasing within-organization homogeneity (Kristoff, 1996). The shared values form also overcomes objections to organizations ‘possessing’ values (Stackman et al. 2000). The internalization of shared values by actors in a social system should ensure that each ‘wants what it should want, and acts as it should act’ (Nohria and Ghoshal 1994). Representing the organization’s values as an aggregation of the personal values of individual members is, however, clearly distinct from the espoused and attributed values forms (Bourne and Jenkins 2013). While attributed values represent organization members’ understanding of existing preferences, aspirational values represent ideas of what should be in the future and so may signal a break from historical patterns (Bourne and Jenkins 2013) so these values are similar to “ideals” (Jaakson, 2010). Those values are needed in order to succeed in the future (Lencioni, 2002). Note that here is where a traditional value may be out of step with a strategic value (Lencioni, 2002). Aspirational values are those which members believe ought to be the values of the organization (Enz, 1988). Changing trends in social life may lead to changes in personal values that become reflected in the aspirational values of organizational members (Bourne and Jen- kins, 2013). More may come through the growth of the organization via new recruits, mergers, takeovers and new stakeholder influence. The aspirational values they believe their organization should adopt if it is to thrive in the longer term (Bourne and Jenkins 2013). Aspirational values are likely to have close similarities with the shared personal values of those individuals

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Jolita Vveinhardt, Evelina Gulbovaitė, and Dalia Streimikiene / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 117-129 promoting them, but they differ from the shared values form in that they emphasize intention: what ought to be, rather than what is (Bourne and Jenkins 2013). According to Lencioni (2002) there are more organizational values forms - accidental and permission-to-play values. Accidental values arise spontaneously without being cultivated by leadership ant take hold over time and don’t really reflect the core or aspirational values. Per- mission-to-play values or non-core, non-distinctive values, namely, those minimum standards of behavior required of people in the organization, typically as set out in employee handbooks. Thus, we can note that other approaches to the forms of values, like the one of the five described in detail above can be identified as well. For example, permission-to-play values may be called espoused values, and accidental values can be named attributed values. Therefore, they coincide according to the sense given to them, and this shows that the approaches to the forms of values in the literature are structured inadequately and different terminology is ascribed to them.

4. COHERENCE/OVERLAPPING/ POTENTIAL OVERLAPPING OF DIFFERENT FORMS OF VALUES Values of different sources of origin prevailing in the organization may be congruent and incongruent, depending on how the management and members of the organization accept them and behave with them. Looking at the analysed forms of values according to the meaning given to them, they can be positioned according to two main criteria: the time and the subject, and two additional criteria: existent/ non-existent and conscious/unconscious. This structure of values in the organization is presented in Figure 1, that allows defining the forms of values more clearly and ensure that other forms of values are not missing, as some of them are not essential and according to the meaning are only a part of the values considered above.

Figure 1. Structural diagram of different forms of values in the organization according to the viewpoints provided to them

Source: Author‘s creation 123

Jolita Vveinhardt, Evelina Gulbovaitė, and Dalia Streimikiene / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 117-129 The basis for this conception is given by the stereotypical course of transformation of values: 1) espoused vales  2) attributed values  3) shared vales  4) core values 5) aspirational values. The forms of espoused values and attributed values are introductory, but they can vary more freely, as they are related to the individuals who may vary in the organization: both managers and employees. Shared values are what is common for both employees and the organization, core values are the standards, which must be followed, they are settled, general values. According to the subject from which values are derived, it can be said that shared values and attributed values are based in the individual, core values and espoused values are based in the organization. Aspirational values are those that can be rooted both in the organization and the individuals. This concept confirms that Bourne and Jenkins (2013) rejecting the form of core values, worsen their decisive influence that the founder, leader of the organization or other individual can have on the prevailing values of the organization. The forms of values are also different due to different time perspectives. Although Bourne and Jenkins (2013) distinguish only the present and the future perspectives towards values, however, three perspectives – of the past, the present, and the future should be suggested. Core values and shared values are more fundamental, established in the past and very difficult to change. And attributed values and espoused values characterize the current time/moment, moreover, they are related to the individual, thus, they are more likely to be altered, as an individual who expresses them can also leave the organization: both the employee, so the system of attributed values is changing, and the executive, the replacement of whom may change espoused values in the organization. Aspirational values are still non-existing idealistic values, oriented to the future. All the discussed forms of values, with the exception of aspirational values, in a sense, are in one or another way existing in the organization. We can also divide the values according to the consciousness of their formation. Attributed values are usually perceived unconsciously, expressing how it all seems, however, they may not always be significant/important. Shared values can also be assigned to subconscious values, as they show the unity of the employees, but not necessarily their compliance with the organizational values, which they are trying to put together in practical activities. Es- poused values arise from the conscious will of the founder or head of the organization, and core values arise from the tension between the founders’ expectations and the real challenges arising in the work of the organization. Thus, both latter forms of values appeal to value consciousness. Organization’s espoused values turn back to core values from which they arise, and shared values occur from attributed values at a certain moment of time. Different forms of values are not statically determined as the opposite, they are dynamic, and occurring at the range from the more developed (looking in the past and more fixed/established) to the less developed in the organization (looking to the present/future and more adaptive/flexible). When trying to compare different analysed forms of values in the organization, it can be stated that core values are unique and described as deeply integrated principles that guide all of organization’s actions, serve cultural cornerstones and must never be compromised. If espoused values are determined by the management and recorded in

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Jolita Vveinhardt, Evelina Gulbovaitė, and Dalia Streimikiene / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 117-129 the documents and they are acceptable to the majority of the members of the organization, and followed in the daily work of the organization – these values can overlap with core values, but not necessarily, if they are not essentially important to members of the organization. Attributed values are usually supported by members of the organization and represent the organization. Attributed values and core values overlap, when they are unique, they are basically very important to the members of the organization and the most influential compared to other values in the system. Attributed values may be distinguished from core values, when they are not unique to the organization, are not important to the members of the organization or they are not the values significantly affecting behaviour. Shared values are those values, which the members of the organization share, they constitute the system of values of the organization, and are measured in proportion to the number of members who share these values, the intensity of their importance compared to other values in the system. Not all shared values are core values, but they are not always unique, leading, more important or influencing than other values. The example of shared values that are not core values might include aspirational, accidental, the permission-to play values. Aspirational values, which, according to members of the organization, should be the organizational values, are very important to the organization, as they represent the response of the organization to the growing needs or changing circumstances. Aspirational values can be distinguished from core values, as core values are defined by long-term principles which do not change depending on the short- term circumstances. Thus, the main task of the management is to ensure the strong congruence of these different forms of values in the organization, which would ensure not only the accept- ability of the values for all members of the organization, but also their conscious recognition and empowerment in their daily activities.

4. CONCLUSIONS AND DISCUSSIONS: STRENGTHENING CONGRUENCE OF DIFFERENT VALUES FORMS IN ORGANIZATION Many executives of organizations perceive the importance of organizational values to the organization, thus, they try to express the values, but the expressed values are often only publicly declared or are the aspiration of the executives, and are not always consistent with those which prevail in the organization, and sometimes conflict with personal values of some of the members of the organization. Management of organizations should attempt to make values not only formally publicly declared and communi- cated to the users of organizations and other stakeholders, but also the real organizational values, which inspire the staff, which are accepted, supported and followed by the majority of the members of the organization. But when people come together to form a group, team or organization they each bring their own personally unique and individualistic set of values with them (Branson, 2008). Employees will take ownership for the organization’s values only to the extent they are in synch with their personal values, thus, harmonization of employees’ values is very important to the organization. However, as the analysis has shown, there are five forms that characterize partial representations of organizational values: those that top managers formally espouse; those that members attribute to the organization; those

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Jolita Vveinhardt, Evelina Gulbovaitė, and Dalia Streimikiene / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 117-129 that members share; those that that members aspire; those that are core or cultural values. Thus differences in the relative importance placed on these requirements mean they hold potential for conflict within and between individuals and groups (Bourne and Jenkins 2013). Organizations with unaligned values struggle to maintain their identity during periods of change (Branson, 2008). The difference between personal value hierarchy, and the perceived value hierarchy of a management, reference group or organization, in this case an employing organization is described as values incongruence. In contrast to the value incongruence, an overlap between forms of organizational values occurs when members share values that are similar to those they attribute to the organization and which correspond to those that top managers espouse in formal documents and statements (Bourne and Jenkins 2013). Congruence has to occur between what we feel, talk and do. Shared values, as it has been mentioned above are unconscious congruence of values among unorganized individuals in the organization. How- ever, looking from the point of establishing of the organization, the foundation of congruence should be espoused values of founders and executives. Thus, the challenge to the organization is firstly how to equate shared values and espoused values. A strong value system is said to exist when organization members share key values related to acceptable behavior within the organization and the organization’s strategic direction (Wiener, 1988) and, more important, that they share the espoused values of organizational leaders (Deal and Kennedy 1982). Therefore, different forms of values will be congruent when espoused values (of executives/founders) will match the actual attributed values of the employees, share them and they will go along with the core cultural values of the organization. So the difference lies in creating alignment-alignment to preserve an organization’s core values, to reinforce its purpose, and to stimulate continued progress towards its aspirations (Collins, 1996). Alignment is referred to as consistency between espoused values and lived values (Schein et al., 2000). Value-aligned organizations are aware of the impact of values on people, performance and outcomes ant these organizations work deliberately with values to create alignment between people’s values and those of the organization (Branson, 2008). Values-aligned organizations do everything in their power to understand the influence of values within their organization and strive to align employee values with those of the organization (Henderson and Thompson 2003). A high degree of values congruence (overlap) may be considered desirable because from the perspective of top managers, high overlap would simplify normative control as there would be widespread agreement about what is good and bad for the organization (Bourne and Jenkins 2013). When there is alignment between individual and organizational values there is also a natural connection between people throughout the organization and when an organization has a defined set of values that are embodied by all employees there is less need for overt management and control (Branson, 2008). Build- ing alignment within an organizational context is about enhancing the group’s capacity to think and act in new synergistic ways, with full coordination and a sense of unity, because each person knows each other’s hearts and minds (Branson, 2008). But only organizational values espousement, enactment and internalization affect individual behavior (Michailova and Minbaeva 2012). According to Lešinski (2006) improper procedures when defining organizational values could rise conflict between employees and owners and most common errors it these procedures are: poor timing of discussion, inadequate vision, poor cooperation between management and lower levels of employees, one way communication, lack of transparent demonstration how organizational 126

Jolita Vveinhardt, Evelina Gulbovaitė, and Dalia Streimikiene / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 117-129 values should work in practice and lack of recognition of success or punishment of failure. Thus, organizations have to seek to integrate so that the employees’ attributed values, management espoused values, organizational shared and core values are congruent. The best way to achieve it is to use comprehensive tools to assess the level of congruence of these values and to diagnose the each values form. It could be done by using right instrument, for example Personal and Organizational Value Congruence Diagnostic Instrument (Vveinhardt and Gul- bovaite 2015), which, depending on its application conditions and the objects of the research would allow identification of employees’ attributed values, managers espoused values, organizations core values and shared values (personal and organizational value congruence). And therefore, after the diagnosis of these values, according to Collins (1996) a two-part process for creating alignment should be used. The first is identifying and correcting misalignments and the second is creating new alignments, or what is called “mechanisms with teeth”. It is one thing to eliminate misalignments that exist but should not and it is another to create something that doesn’t yet exists but ought to. As only the harmony of values of all the members of the organization can provide the purposeful and desired behaviour of the members of the organization and result in the success of the organization, not only in the present, but also in the future.

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Evgeny V. Popov, Evgenia V. Ersh / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 131-146

Montenegrin Journal of Economics

Vol. 12, No. 2 (2016), 131-146 ‘

Institutions for Decreasing of Employee Opportunism1

Evgeny V. Popov2, Evgenia V. Ersh3

1 The study was financially supported by the Russian Science Foundation at Udmurt State University (Izhevsk, Russia), project No. 15-18-00049. 2 Doctor of Sciences (Econ.), corresponding member of the Russian Academy of Sciences, Institute of Economics of the Ural Branch of the Russian Academy of Sciences, E-mail: [email protected] 3 Head of department of human resource management Joint Stock Company “Scientific-industrial automation union named Academician N.A.Semikhatov”, E-mail: [email protected]

ARTICLE INFO ABSTRACT Received November 21, 2015 In manufacturing plants opportunism is appear in the form of stall- Received in revised form Feb. 20, 2016 ing, negligence, use of official position and hiding reserves jobs by Accepted May 23, 2016 the staff, also providing managers with incomplete or distorted Available online June. 15, 2016 information about the working conditions and the existence of personal sympathies in the distribution of incentive bonus, work task, JEL classification: awards, etc., There are technical and institutional factors influencing the level of manifestation of opportunistic behavior on the en- D02; D23; terpriseas a whole and in departments of various types. Identifying these factors and determining the nature of the relationship with DOI: the level of various forms of dishonest behavior is the basis to con- 10.14254/1800-5845.2016/12-1/2 trol the level of opportunism in manufacturing plants.

Keywords: opportunism, institutional factors, corporate institutions, labor relations, forms of opportunism

1. INTRODUCTION The problem of opportunism studyingin firmsistopical for several reasons. Employment relations mean always contractual relations that make the opportunism both of employee and employer possible (Williamson O.E., 1979). Opportunistic behavior causes high transaction expenses, connected with its prevention and limitation, and also decreases labor productivity level in firms. In the current context the rise of economic efficiency and the growth of labor productivity are the necessary conditions for competitive recovery. The purpose of this scientific paper is a posteriori estimate of the opportunistic behavior of employees in firms in current conditions.

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Evgeny V. Popov, Evgenia V. Ersh / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 131-146 2. FORMS OF EMPLOYERS’ AND EMPLOYEES’ OPPORTUNISM The Nobel Prize winner of 2009 O. Williamson defined opportunism as a form of «the economic agent’sbehaviour, when they were provided with the incomplete ordistorted information (including deceit, delusion, holding back the truth, and other ways of partner's confusion)» (Wil- liamson, 1993). It should be pointed out that the opportunism problem of economic agents is widely investigated in the political sphere. So, the political opportunism's limitations influence the economic overcoming crisis (Walter S., 2008). However, human opportunism can be sur- mounted, perhaps, through the governmental efforts (Kraft, 2010). The development of presidential power in the USA has stimulated formation of the theory of aspirant opportunism (Brown, 2009). The political opportunism can be evaluatedby the global financial system valuation (Wood S., 2012) or by the governmental regulation of the public organizations' activity (Zhenglai et Yi, 2013). Moreover, the influence of gender, age and qualifica- tion differences on the opportunistic behavior of researchers has been assessed in the scientific community (Acar et Ende, 2013). On the other hand, the assessment of agents’ opportunism in the universities management is possible in the framework of principal-agent theory by the modeling (Kivisto, 2008). However, the most important for the economic activity is to assess the opportunistic behavior in market relations (Roberts, 2012) and relations between agents within a firm (Squire, 2010). The decrease of opportunism in market relations is possible by regulations' institution (e.g., patents) for the new products launching on the market (Yoo, 2013) or by the psychological preparations of consumers to achieve specific goals (Seifert et Patalano, 2001). In case of intra- firm activity, the regulation of employee’s opportunism is possible by the establishment of re- strictive standards of behavior (Hirschmeier, 1970) or by the established rules of interaction (of economic institutes) between economic agents (Kostritsky, 2013). Meanwhile, for the intra-firm relations application of the economic institutions for the opportunism's decrease is applicable both for employers (Note, 1989) and employees (Hansmann et al., 2006). Summarizingall the present publishedstudies, we canemphasizethe features that characterizeopportunistic behaviourin employment relations. The firstcondition for the oppor- tunismemergencein the system ofemployment relationsis aclash of interestsof interactinge- conomic agents-an employer and anemployee. The employer aims to maximize his profits and minimizeexpenses, but the employee is interested in pay rise and minimization of productive efforts. The second condition may be either an asymmetric dissemination of information between an employee and an employer or the dependence of one of the interacting subjects of employment relations within a symmetrical dissemination of information that leads to theproblem of inexpedient termination of established relations. The labor market is characterized by a mutual information asymmetry. The essence of mutual information asymmetry is that one party is informed more about some parameters and characteristics of the transaction andthe other is informed about other characteristics.For instance, awage earneris more informed about his own job characteristics, and an employer is more informed about job conditions offered to the job applicant. Thus, the adverse effects of information asymmetry may emerge both for one and the otherparty of employment relations. Another important feature of opportunistic behavior is a deliberate act. This means that the employee or the employer consciouslyuses theexisting opportunities for the opportunism manifestation and does not providethe contractor with the reliable information about the essence ofhis actions. Inthe employment relations the opportunism means the deliberate action of the employee and/or employer violating explicitly or implicitly the stipulations of an agreementin order to gainadditional profit, not specified in the agreement, and damaging to the other party.

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Evgeny V. Popov, Evgenia V. Ersh / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 131-146 Thus, the intrinsic causes of opportunism in the employment relations are work division and alienation, incomprehensive rationality of economic agents, their tendency to opportunism and contractual incompleteness. The forms of opportunism manifestation in employment relations in firm sare extremely varied (Popov et Simonova, 2006). The forms of opportunistic behavior in firms summarized in the Table 1. The firms of different industries are characterized bytheir own particular forms of opportunistic behavior ofboth the employees and the employers.Therefore, for each firmfactors that influence the level of misconduct should be revealed, and institutions thatcan provoke its decrease should be identified.

Table 1.The forms of employee's and employer’s opportunism

Opportunism form

 the probation period- (It is imposed upon a candidate with premeditated subsequent dismissal)  conscious concealment of the negative aspects of work  unpaid overtime job  demonstration of personal sympathies (family, diaspora and others) in Ex-ante employer the work assignment, remuneration, job positions opportunism  the employer doesn’t provide benefits and compensation prescribed by the law  undervaluation of the employee's work (demotion, cutting down remuneration)  the assignment of tasks beyond the employment contract without payment  Salary manipulation

 unfavorable activities (the candidate exaggerates his real abilities, Ex-post employer skills, knowledge) opportunism  corporate espionage  concealment of the plans about the true purpose and duration of stay on the new position

 unfavorable activities (the candidate exaggerates his real abilities, Ex-ante employee skills, knowledge) opportunism  corporate espionage  concealment of the plans about the true purpose and duration of stay on the new position

 shirking  using the working time for dealing with personal problems  work of lower quality  negligence sabotage Ex-post employee   different backstairs of the staff during the promotion of colleagues opportunism  concealment of their workplaces' reserve by the employees  pulling rank  fraud  blackmail  plunder

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Evgeny V. Popov, Evgenia V. Ersh / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 131-146 3. METHODOLOGY For the research of employee’s opportunism a large firm, which refers to thehigh-tech industry, has been investigated.The main directions of the firm'sactivities are research and devel- opmentandsmall-scale production. In course of the studythe employees of production and- design departmentswere interviewed. The offered questionnaire contained questions assessing the level of opportunism and potential factors that could influence it. In this work the most significantfor the companyforms ofopportunistic behaviorof employeesand managersin the process of concluding the contrac- tand after that were analyzed. Among theseforms ofopportunismin the system oflabour rela- tionsin the firmsare:  shirking  negligence  concealment of workplaces' reserve  pulling rank  managerprovides incompleteor unreliable informationabout the working conditions  unpaidovertime  the assignment of task beyond the employment contract without payment  demonstration of personal sympathies and antipathies in the work assignment, remuneration, job positions, etc.

4. INSTITUTIONAL EFFECTS OF THE DECREASE OF EMPLOYEE’S OPPORTUNISM In the course ofempirical research an assessment ofdifferent factors’ influence on the manifestation of «post contract»opportunismof the employees has been conducted. Depend- ence analysisbetween the scale ofemployee’s opportunismandestablishedin the companyfinan- cialsystemsimulation hasshown thatsuch factorsascompliance salary setting tothe average marketlevelinfluences employee's opportunismmanifestation in the form of shirkingand concealment of workplaces' reserve.Figure 1 shows the dependence of employee’s opportunistic behavior onthe salary compliance to the average marketlevel. The shirkinglevel has been esti- matedas a fraction of time which employee does not use to achieve production goals.

Fig.1. Dependence of shirking and concealment of workplaces' reserve on salary

Here: ----- concealment of workplaces' reserve; shirking

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Evgeny V. Popov, Evgenia V. Ersh / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 131-146 The level of opportunism in the form of concealment of workplaces' reservehas been estimated as the difference between the technically (technologically) possible volume of production (performed work) and actual volume of production. As shown in the Fig. 1 with a decrease of salary level below the average a level of shirking andconcealment of workplaces' reserve increase. While salary reduces more than 30% below the average, a level ofconcealment of workplaces' reservedramatically increasesand reaches 30% or more. However, in case of salary cor- respondence to the average market level employee’s opportunistic behavior in these forms is also observed (its average value is R1overage= 13.8% = 17.6% R3 overage). The minimum shirking level and concealment of workplaces' reserveis observed in a significant (30% or more) excess of salary level to the average marketlevel. In addition, as a result of the researchit was found outthat the dependence between the opportunism level of employees in the form of negligence and pulling rank from salary level relatively to the average market level is insignificant. The results of the research have showed that the reward system, specifically its use in the employee’s promotion for specified behavior, influence the opportunism level of employees. As shown in the Fig. 2 the most obvious influence of the reward system is on the increasing level of shirking.

Fig. 2. Dependence of shirking level on reward system

Here: shirking.

0 - the manager does not encourage conscientious behavior; 1 –the manager extremely rarely encourages the employees’conscientious behavior; 2 - the manager often encourages the employees who behave well; 3 - the manager encouragesall employees who do not admit misconduct.

It should be noted that it does not matter what kind of rewards are there and how varied they are.Primarily, its regularity and interconnection with the "correct" behavior are of great importance. Therefore, we can talk about the real instruments of managersthat can be used to influence the employee’s opportunism, especially in the form of shirking through the encour- agementincludingnon-financialconscientious behavior of employees. Uniquenessof knowledge and skills that employees possess is the factor affecting the misconduct. As shown in the Fig. 3 themoregeneral knowledge employeeshave, the less they tend to behave opportunistically by shirking, showing negligence and concealing workplaces' reserve.

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Evgeny V. Popov, Evgenia V. Ersh / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 131-146 Fig. 3 Dependence of the level of shirking, negligence and concealment of workplaces' reserve on the degree of work force peculiarity

Here: shirking; negligence; - - - - - concealment of workplaces' reserve

Accordingly, in departments with a large proportion of employee’s whopossessunique (highly specific) knowledge and skills the level of employee’s misconduct is higher.

5. INSTITUTIONAL EFFECTS OF REDUCING EMPLOYEE’S OPPORTUNISM In production divisions of the enterprise mass and small-scale production are carried out. Specific features of these divisions are:  Generally, a routine activity with a minimum share of creative process;  A big parts of general knowledge and skills that employeespossess;  A big number of divisions  An application of various forms of the organization of a working process

During the research it has been stated that the scales of “post-contract” opportunism are not connected with the number of divisions. It can be explained by the fact that at the state enterprises there is a multilevel hierarchical structure which is built on the basis of the standards of spans of control developed to take into account a chanceof control over the employee’s activities. A poll conducted amongthe employees of production divisions has showed that the system of punishment has an impact on the level of opportunistic behaviour of employees. In the fig. 4 dependence of a level of shirking on the regularity of application of punishment in case of detection of similar opportunistic employees’ behavior is shown.

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Evgeny V. Popov, Evgenia V. Ersh / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 131-146 Fig. 4 Dependence of a level of shirking on the regularity of the use of punishment system

Here: shirking.

0 – the manager never punishes employees for misconduct; 1 –the managerpunishes employees for misconduct when it becomes a standard of behaviour; 2 –the managerpunishes employees for misconduct when it starts to have negative impact on the productive process; 3 –in case of detection of an employee’s misconduct the manager surely applies punishment system.

Apparently, in the fig. 4, in divisions where the punishment system for suppression of employees' opportunistic behavior is more consistently applied, the share of working hours loss decreases, whereas in divisions where the punishment system is not applied or applied extremely irregularly, shirking level is much higher. In the fig. 5. the dependenceof employees' opportunism level in the form of shirking and negligence from the degree of loyalty (involvement) of employees of production divisions is shown.

Fig. 5. Dependence of a shirking and negligence level from employees’ loyalty

Here: shirking; - - - - negligence.

Thus, developing corporate culture and increasing the number of employees loyal to the enterprise losses of the enterprise from negligence of the production personnel and shirking will 137

Evgeny V. Popov, Evgenia V. Ersh / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 131-146 be minimized. The other aspect of the corporate culture development is the formulated and clear to the employees existence of the conscientious behaviour corporate model that have an impact on the level of negligence of the production personnel that is shown in the fig. 6.

Fig. 6. Dependence of level of the employees’ opportunism in the form of negligence from the corporate culture development (existence of the conscientious behaviour corporate model)

Here: negligence

It should be noted that even with an insignificant decrease inemployees’ assessment of the perception of the conscientious behavior model the negligence level considerably increases, and in the situation of lack of conscientious behavior model clear toemployees the level of negligence reaches 30% maximum. Thus, for minimization of losses of the enterprise from negligence of the production personnel it is necessary to formulate the norms and rules reflecting conscientious behavior ofemployees and provide their full understanding andemployees’ acceptance. Besides, in the fig. 7 and 8 the dependence of shirking level from the staff appraisal development system andemployees’ social security system is displayed.

Fig. 7 Influence of the system of staff appraisal on a shirking level

Here: shirking

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Evgeny V. Popov, Evgenia V. Ersh / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 131-146 Thus, at the increase of the development degree of the staff appraisal system, the definition of the assessment criteria that excludes personnel shirking possibilities, its regular carrying out and bringing results toemployees, and also the establishment of interrelation of assessment results with remuneration of labour level in production divisions of the enterprise conditions for the decrease in losses of working hours byemployee's fault will be created.

Fig. 8 Influence of social security system on the employees’ shirking level

Here: shirking

In the fig. 8 it is clear that the social security system has an essential impact on the level of the opportunism ofemployees in the shirking form.Thus, the development of the social security system towards the differentiated provision of the additional social maintenance encouraging conscientious behavior ofemployees will promote the decrease in shirking.

6. INSTITUTIONAL EFFECTS OF THE DECREASE IN OPPORTUNISM OF THE SCIENTIFIC SPHERE EMPLOYEES The main function of the scientific (design) enterprise divisions is the implementation of research and skilled-design works. For these divisions there are following characteristics:  A significant part of the creative work connected with the generation of new scientific and technical knowledge,  high peculiarity of knowledge which divisions employees possess,  arather low number of divisions,  a big share of the employees who have been working at the enterprise more than 20 years.

According to the results of the research conducted among employees of design divisions the influence of a creative component of labour process onemployees’ shirking level and official position use (fig. 9) has been revealed.However, the dependence of the level of negligence demonstration and the concealment of workplaces' reserve has not been revealed.

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Evgeny V. Popov, Evgenia V. Ersh / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 131-146 Fig. 9. Dependence of the shirking level and pulling rank from a share of a creative component in the productive process

Here: - - - - shirking, pulling rank

Apparently, in the fig. 9 it is shown that there is an inverse relation between a share of a creative component in the labour process of the employees of design divisions and scales of demonstration of such forms of the employee’s opportunistic behavior as shirking and pulling rank. As the creative activity is inalienable in essence, one of the reasons of theemployees’ opportunism emergence disappears. Conformably, for the reduction of misconduct level of the employees of design divisions it is necessary to have a great number ofemployees been involved into creative work. The other factor that has an impact on the level ofemployee’sopportunistic behavior de- monstrationis uniqueness of knowledge and skills whichemployees possess.Apparently, in the fig. 10 it is shown that the more general knowledgeemployees possess, the less they are inclined to the manifestation of the opportunistic behavior in the form of shirking, negligence and concealment of workplaces reserves.

Fig. 10. Dependence of a level of shirking, negligence and concealment of workplaces' reserve from a degree of the universality of labour force

Here: shirking; - - - - concealment of workplaces’ reserve; negligence 140

Evgeny V. Popov, Evgenia V. Ersh / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 131-146 Conformably, in the divisions with a big share ofemployees possessing unique (high- specific) knowledge and skillsthe level of manifestation of theemployee’sopportunistic behavior is higher. The influence of an institute of corporate culture on the extent of manifestation ofemployee’s opportunism level has been estimated in two aspects.Firstly, such an element of the corporate culture as the existence of the accurately formulated and clear tothe employees model of the conscientious behavior has been estimated, that is such a standard ofemployee’s labour behaviour which is perceived by managers andemployees as a correct one, corresponding to the interests of the enterprise and conditions of the employment contract. In the analysis of the received results the interrelation between theemployee’s assessment of the expressiveness of conscientious behavior model and the level of the opportunistic behaviour of the employees of design divisions in the form of shirking (fig. 11) has been established.Apparently, in the fig. 11 it is shown that the minimum level of shirking is observed among theemployees who are completely informed about the conscientious behavior standards.\

Fig. 11. Dependence of employee’s opportunism level in the form of shirking from the development of the corporate culture (the existence of corporate model of the conscientious behavior)

Here: shirking

However, the influence of this factor on the level of manifestation of such forms of the opportunism as negligence, pulling rank and concealment of workplaces' reserve is not revealed; that can be an absence ofemphases on unacceptability of such behaviour in the corporate model of the conscientious behaviour. The second aspect of the assessment of influence of the corporate culture on the level ofemployee’s opportunism is the involvement (loyalty) ofemployees. The involvement (loyalty) here means such a condition of employees when employees realize and divide values and the purposes of the company, and feel the internal need to do their work qualitatively thereby help- ing the enterprise to achieve the goals (Popov, 2012, P. 82).

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Evgeny V. Popov, Evgenia V. Ersh / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 131-146 Dependence of the level of manifestation of such opportunism's forms of design division’s employees as negligence, concealment of workplaces'reserve and pulling rank is reflected in thefig. 12.

Fig. 12. Dependence of the level of manifestation of negligence, concealment of workplaces' reserve and pulling rank from the degree of employees' loyalty to the enterprise.

Here: negligence; - - - - concealment of workplaces' reserve; __ .. __ pulling rank

In the fig. 12 it is shown that at the highest loyalty of theemployees connecting their lives with the enterprise and focusing on the «lifelong employment» the level of manifestation of the specified forms ofemployee’sopportunistic behaviour is minimum.Thus,the level of negligence and concealment of workplaces' reserve are the most sensitive to the change of the loyalty of the personnel, whereas a significant increase in the pulling rank happens when the decrease in the loyalty of the personnel below the average level appears. Thus, implementing the personnel strategy focused on the long-term labour relations with the employees of design divisions and developing corporate culture for the purpose of the increase of the level of the personnel's loyalty (involvement) it is possible to reduce the level of the opportunistic behaviour of the personnel significantly. Studying the influence of corporate training system and the development of a personnel professional career it has beenfound out that it is present at the relation of the extent of shirking manifestation, however, at the same time such an influence on the other forms of the opportunism has not been noted.In the fig. 13 it is shown that at a high level of development of the system of corporate training theemployees shirking level is minimal. Thus, developing the system of the corporate training and planning of a professional career at the enterprise, the conditions for a decrease of the level ofemployee’s opportunism in the form of shirking are created. Besides, the development of an institute of personnel assessment, firstly, the establishment of interrelation between the results of an assessment with theremuneration has an impact on the level of manifestation of the opportunistic behaviour in the form of negligence.

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Evgeny V. Popov, Evgenia V. Ersh / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 131-146 Fig. 13. Influence of the system of training and professional development on the personnel shirking level.

Here: shirking

In the fig. 14 it is shown that at a high level of development of the assessment system and its close interrelation with the level of remuneration the losses of the enterprise fromem- ployee’s negligence are minimum.

Fig. 14. Influence of the staff appraisal system on the negligence level

Here: negligence

Thus, with the development of staff appraisal system, first of all, the definition of the criteria of the assessment, its regular carrying out and bringing results tothe employees, and also the establishment of the interrelation of the assessment results with the level of remuneration, at the enterprise conditions for the decrease in the level of negligence of the personnel of design divisions are created. 143

Evgeny V. Popov, Evgenia V. Ersh / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 131-146 7. INSTITUTIONAL EFFECTS OF THE DECREASE IN OPPORTUNISM AMONG THE MANAGERS The conducted research has revealed the existence of such a form of the precontractual manager’s opportunism as providing a futureemployeewith the incomplete or distorted information about working payment conditions. The dependence (fig. 15) of an extent of manifestation of this form of opportunism from the level of labour remuneration has been established.

Fig. 15. Frequency of giving the complete or distorted information about working conditions by the manager

Here: furnishing of incomplete or distorted information

Apparently, in fig. 15 it is shown that at the remuneration level in the division corresponding or a little bit exceeding the average level (to 15%) the frequency of manifestation of precontractual opportunism of managers is minimum, and at the excess of more than 15% the precontractual opportunism of managers is not noted.Thus, even a small lag of the level of remuneration from the average market level significantly increases the degree of precontractual opportunism of managers. Within the empirical research the assessment of the following forms of the post-contract opportunism of managershas been carried out:  The use of the over-employment mode without the corresponding payment  An assignment of the additional works which are not provided by the employment contract without adequate payment  Manifestation of personal sympathies and antipathies at distribution of works, rewards, additional social guarantees.

The analysis of the questionnaires completed by the employees of the enterprise showed that cases of manifestation of such forms of post-contract managers opportunism as overtime work and an assignment of the works which arenot provided by the employment contract are rather rare.Less than 30% of respondents note that overtime work without the corresponding payment in the division is used and that employeesare charged with the work which is not provided by the employment contract without adequate payment.Thus,the dependence of scales of

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Evgeny V. Popov, Evgenia V. Ersh / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 131-146 post-contract opportunism of managers in the specified forms from the relative level of remuneration has not been stated. Moreover, there is no interrelation between the levels of post- contract opportunism of manager’s andthe share of a variable part ofemployees' salaries. Thus, as a result of empirical review, dependence of the level of post-contract opportunism of managers in the firms of RCP from the institute of material incentiveshas not been revealed.This is the consequence of the fact that in the firmsthe system of control overthe implementation of requirements of the labour legislation is built.Therefore, manifestation of post- contract opportunism in the forms directly violating the current legislation has no systematic character and is incidental. It should be noted that the most widespread form of post-contract manager’s opportunism is the expression of personal sympathies during the distribution of works, rewards, positions, additional social guarantees.All the interrogatedemployees note a manifestation of a similar form of manager’s opportunism in a bigger or a smaller scale. According to the results of the conducted research, the interrelation between the level of manifestation of manager’s opportunism and the development of the protective function of the labour union has been established.Thus, the labour union is understood as the trade-union cell operating directly in the division, first of all, as a possibility of influence of the trade-union leader of the division on the manager for the purpose of protection of the division employees' interests.In the fig. 16 it is shown that the moreemployees estimate an extent of the development of protective function of the labor union, the lower likelihood of manifestation of personal sympathies of the unit manager is.

Fig. 16 Dependence of frequency of manifestation of personal sympathies and antipathies of the manager during the distribution of rewards, works, positions, etc. from the development of protective function of a trade-union cell in the division.

Here: manifestation of personal sympathies and antipathies of the manager

Also, a mild negative dependence of the level of manifestation of a post-contract opportunism of the managers in forms of the over-employment mode use and an assignment of performance of additional work without payment from an extent of labor unions' institute development is observed. Thus, as a result of the empirical research,the influence of production factors and institutes of intra-firm management (Popov, 2012) on the level of manifestation of post- contract opportunism ofemployees and firm managers of hi-tech knowledge-intensive sector of economy has been defined. The assessment of influence of such economic institutes as institutes of corporate culture, system of corporate training and professional development, system of personnel assessment, material stimulation, system of encouragement and punishment, and also institute of labor unions on the decrease in opportunism of the employees of the firm has been carried out. 145

Evgeny V. Popov, Evgenia V. Ersh / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 131-146 REFERENCES Acar, O.A., Ende J. (2013), “Understanding Fear of Opportunism in Global Prize-Based Science Contests: Evidence for Gender and Age Differences”, Plos One, Vol. 10, No.7, 1-13. Brown, L.M. (2009), “Around Closed Doors and Through Open Windows: a Theory of Aspirant Opportunism, 1796-2004”, Congress & the Presidency, Vol. 36, No.1, 1-26. Hansmann, H., Kraakman R., Squire R. (2006), “Law and the Ruse of the Firm”, Harvard Law Review, Vol. 119, No. 6, 1333-1403. Hirschmeier, J. (1970), “The Japanese Spirit of Enterprise, 1867-1970”, The Business History Review, Vol. 44, No. 1, 13-38. Kivisto, J. (2008), “An Assessment of Agency Theory as a Framework for the Government- University Relationship”, Journal of Higher Education Policy and Management, Vol. 30, No. 4, 339-350. Kostritsky, J.P. (2013), “The Law and Economics of Norms”, Texas International Law Journal, Vol. 48, No. 2, 465-506. Kraft, H.J.S. (2010), “The Philippines in 2009: the Fourth-Quarter Collapse”, Southeast Asian Affairs, 237-257. “Note: Employer Opportunism and the Need for a Just Cause Standard” (1989), Harvard Law Review, Vol. 103, No. 2, 510-529. Popov, E.V. (2012), “Transactions & Institutions”, Montenegrin Journal of Economics, Vol. 8, No. 2, 115-124. Popov, E.V., Simonova V.L. (2006), “Forms of Opportunism between Principals and Agents”, International Advances in Economic Research, Vol. 12, No. 1, 115-123. Roberts, J., Ng W. (2012), “Against Economic Conceptions of the Individual: Constructing Finan- cial Agency in the Credit Crisis”, Culture and Organization, Vol. 18, No. 2, 91-105. Seifert, C.M., Patalano A.L. (2001), “Opportunism in Memory: Preparing for Chance Encoun- ters”, Current Directions in Psychological Science, Vol. 10, No. 6, 198-211. Squire, R. (2010), “Shareholder Opportunism in a World of Risky Dept”, Harvard Law Review, Vol. 123, No. 6, 1151-1212. Walter, S. (2008), “The Limits and Rewards of Political Opportunism: How Electoral Timing Af- fects the Outcome of Currency Crises”, European Journal of Political Research, Vol. 48, No. 2, 367-396. Williamson, O.E. (1979), “Transaction Cost Economics: the Governance of Contractual Rela- tions”, Journal of Law and Economics, Vol. 2, 233-261. Williamson, O.E. (1993), “Opportunism and its Critics”, Managerial and Decision Economics, Vol. 14, 97-107. Wood, S. (2012), “The Euro Crisis”, Policy, Vol. 28, No. 1, 32-48. Yoo C.S. (2013), “Standard-Setting, FRAND, and Opportunism”, Texas Intellectual Property Law Journal, Vol. 22, 69-70. Zhenglai, D., Yi D. (2013), “The Logic of the “Tutelary-Style” Monitoring System: an Assessment of State Policies on Social Organizations in the Past 30 Years”, Journal of Chinese Political Science, Vol. 18, 21-40.

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Milica Delibasic / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 147-159

Montenegrin Journal of Economics

Vol. 12, No. 2 (2016), 147-159 ‘

Hypothetical Matrix for Institutional Modeling of the Basis for Economic Development in the Countries of Southeast Europe

Milica Delibasic1

1 PhD student, Faculty of Economics, International University Travnik, Bosnia and Herzegovina; e-mail: [email protected]

ARTICLE INFO ABSTRACT

Received March 11, 2016 In this paper we propose three hypothetical matrices for institu- Received in revised form –May, 04 2016 tional modeling of the basis for economic development. They Accepted June 08, 2016 apply selectively chosen elements of Neo-Institutional Theory Available online June, 15, 2016 (NIT) and convention theory, which are in line with affirmation of institutional pluralism and criticism of institutional monism. In JEL classification: this sense, the developed institutional pluralism is critically and B52; D02; E11; O17; P37; polemically opposed to all forms of opportunistic behavior, which in the conditions of the domination of institutional monism leads DOI: to the creation and strengthening of alternative institutions. Its hypothesis is that the hypothetical modeling of pluralistic institu- 10.14254/1800-5845.2016/12-1/9 tional basis for economic development must be based, inter alia, on the elements and recommendations of the NIT and the con- Keywords: vention theory on key issues (research parameters). This is espe- institutions, cially the case with institutional elements, factors and recom- institutional analiz, mendations that have been confirmed in the practice of devel- neo-institutional theory (NIT), oped countries. The conclusion is that the economic growth re- countries of Southeast Europe (SEE), quires strong and pluralistic institutions, which represent the best means of protection from all forms of opportunistic behavior.

1. INTRODUCTION In the period of expansion of the parallel processes of globalization and post-socialist transition, which are ongoing for 25 years, there were rapid and dynamic changes of economic reality, the structure of contradictions, systems and criteria of values, development priorities, expression of interests of various social groups and the like. All this had a significant impact not only on the practical manifestations, which often had a dominant crisis character, but also on the development of many schools of economic thought, of which the most renowned were the neo-institutional theories (NIT).

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Milica Delibasic / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 147-159 This paper studies the analytical and methodological models of bounded institutional rationality on both theoretical and practical level. It is created with the aim of explaining the role and importance of pluralistic institutions in developed countries, which is reflected through economic growth and sustainable development. Hence, there was a need: a) to prove the negative role of all forms of institutional monism, which characterize, to a greater or lesser extent, the practice of those countries, and b) to criticize the deficit of institutions, which significantly reduced and deformed its role. Those are objective and long-term constraints of economic development. Therefore this research topic is extremely important for the future reforms, development plans and strategies of the SEE countries, which need be based on the radical, real, and pluralistic institutional changes. It is known that deficient and degenerated institutional factors are the core of the hindering mechanism, which for two and a half decades prevents the desired economic growth and development of most transitional economies, including economies of the SEE countries. Institu- tional indicators and institutional changes are unsatisfactory and far behind the corresponding indicators in developed countries. This was directly reflected in the lagging behind of transitional economies of the SEE countries, deepening their social and economic crisis. Given research could significantly contribute as a landmark for the policy-makers in adopt- ing realistic and pluralistic institutional changes and the principles of bounded rational behavior in those countries. The subject matter of study in this article is wide, but in summary it includes: a) a comparative analysis of theoretical concepts of bounded institutional rationality, which in- volves a combination of constructive contributions of various NIT and effective pluralistic institutional practical arrangements. Scientific research was set according to the aforesaid subject of study, and consisted of identifying the relevant elements recommended by NIT, in order to design and prove the hypothetical exemplary model of bounded economic rationality, which meets the needs of modern economies that favor sustainable development. This article formulates original matrixes, which can be used for hypothetical institutional modeling of the economic development foundation (for analyzing elements of the NET relevant to the institutional model, and elements of the convention theory relevant for institutional modeling. The benefits of institutional pluralism as a mandatory condition of economic growth and sustainable development have been reaffirmed..

2. THEORETICAL APPROACH The theoretical framework of hypothetical matrix for institutional modeling of the basis for economic development has been formulated based on the most important research papers of neo-institututionalists and their key definitions, which are mostly heterogeneous (probably due to the complex nature and numerous functions of the institutions). This paper is an attempt to selectively display the basic ideas of the NIT representatives and economics of convention, which can be applied to analyze the character, quality and level of real institutional changes in the transitional countries of SEE. In conceptual sence, as an inspiration and a theoretical guide for creating hypothetical matrices, which affirm the institutional pluralism, helped the research by D. North, J. B. Wallis and Weingast (2009), the scheme by E. Ostrom, R. Gardner and R. Walker (1994), presented in Figure 1, and the reasoning by W. Scot (1995), as shown in Table 1 and Table 2. Scott (2004) argues that this theory also provides insights into conflict and change within social structures. It should be noted the importance of logical scheme, shown by R. Greenwood, M. Raynard, F. Kodeih, E. Micellota, and M. Lounsbury (2011, p. 324), indicating the importance of institutional pluralism and its connection to institutional complexity. It is believed (Jar- zabkowski, Matthiesen and Van de Ven, 2009) that only developed and pluralistic institutional environment enables efficient managing the balance of social interests, with applied simultaneous skills for stimulating investment and entrepreneurship. 148

Milica Delibasic / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 147-159 Figure 1: A Framework for Institutional Analysis

Source: Ostrom, Gardner and Walker, 1994, p. 37.

Table 1. Three pilars of institutions

Regulative Normative Cognitive Basis of compliance Expedience Social obligation Taken for granted Mechanisms Coercive Normative Mimetic Logic Instrumentality Appropriateness Orthodoxy Rules, laws, Certification Prevalence isomor- Indicators sanctions accreditation phism Basis of legitimacy Legaly sanctioned Morally governed Culture, knowledge

Source: Scott, 1995, p. 35.

Table 2. Instittional carriers carrier Pillar Regulative Normative Cognitive Cultures Rules, Values Categories, laws Expectations typifications Social structures Governance, Regimes, Identities, power sys authorita sys isomorphism Routines Protocols, Conformity, Scripts, standard procedures performance of duty performance programs

Source: Scott, 1995, p. 52.

According to A. Stulhofer (1995), five characteristics of institutions are significant for our analysis, related to the hypothetical modeling of institutional behavior, as follows: ─ institutions are permanent and organized social practice, a set of interactive activities, ─ institutions include norms which direct, regulate and restrict given activities (thereby the norms are interpreted as socially constructed system of expectations, which directs individual actions, based on an external mechanism (formal and/or informal) sanctions and internal mechanism of socialization (the process of identification ). To overview the classification of social norms see more in: Elster, 1997, Stulhofer (Ibid., p. 957) points 149

Milica Delibasic / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 147-159 out that norms are the building blocks of institutions, and the institutions guarantee the maintenance of norms. ─ institutions include the system of sanctions, which ensure the effectiveness of norms, ─ institutions imply a role system, strictly defined tasks, responsibilities and interpretative framework, and ─ institutions provide an important influence on the social structure because they act co- hesively.

The analysis of institutional models has showed that economic development includes not only an economic subsystem, but also the broad spectrum of non-economic variables, including formal and informal institutions, cultural and other systems of values, as well as all forms of opportunistic behavior, that is established by alternative institutions (Figure 2). In some countries, various formal institutions (economic, legal, political and other) can not be considered only as an instrument for achieving specific objectives. Because they need to include the existence of precise limits between permissible and impermissible. These limits are defined by certain standards of social behavior arising from general moral norms, and cultural and social traditions. Thus, institutions have an instrumental character, as well as an inner value character, because they make the foundation for the commitment to the general objectives that go beyond personal interests.

Figure 2: Interrelated developments in the social system

Source: adapted from Hayami and Godo, 1997, p. 11

Bounded rational behavior (institutional or any other type) directly contradicts opportunistic behavior (Delibasic, 2014, p. 15). The latter is caused by the existence of alternative institutions (shadow institutions), which have been shown to have a destructive influence on the valorization of economic resources. Opportunistic behavior has several negative meanings in economic theory (see more in: Williamson, 1993, p. 115). However, it generally represents the action of economic agents in accordance with their own interests, not taking into account the moral norms, but it contradicts the interests of other agents. The institutional structure is a subject to various manipulations by private and/or group interests in all cases with loose borders with inner values. For example, the typical case where the nomenclature of government, or the political institutions, ignore the interests of the people, allowing the action of alternative institutions, by which they achieve the interests of privileged individuals and/or small social groups. In such cases, the legal system (laws, rules, standards, and procedures) is abused and undermined. In other words, the case management is dominated by autocratic institutionally irresponsible "games without rules" that marginalize "games with specific rules." During the period of transition in the SEE countries, the entire system of hindering factors was operating. It caused the creation of a non-functional conglomerate system and institutional

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Milica Delibasic / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 147-159 failure, especially in the state regulation. This was caused by an affirmation of institutional monism of neoliberal type, characterized by numerous market deformations and limits, favored by the policies and representing the basis for strengthening of alternative institutions. Generally, any institutional monism is a fertile ground for the manifestation of opportunistic behaviors and affirmation of alternative institutions, representing a form of informal institutions. This is especially important for understanding D. North (1991, p. 36). According to him, different societies with the same formal institutions have different results - due to different effects of informal institutions. This is particularly reflected in the countries with excessive market power and in the conditions where the ruling elite uses political power in the unethical way and obstructs the functioning of the rule of law. In these cases there is a blockade of action and development of socio-cultural capital and the reduced activity of formal institutions. Alternative institutions are a classic example of a conflict between privileged individual behavior and existing institutional structures. M. Draskovic, S. Bauk and M. Delibasic (2016) argue that their establishment and operation is enabled by the existence of informal and privileged combination of two basic institutional monisms (the market and the state regulation). This combination of institutional monisms has been dictated by the so-called "new elites", leading to institutional deficit in general, and institutional pluralism in particular. Alternative institutions have illegal, personified, sociopsychological, and destructive character. They extremely affect the real institutional changes in a dysfunctional way, leading to institutional fiasco. It was the practice in the SEE countries, where alternative institutions dominated over formal and other informal institutions, producing a long-term institutional vacuum, and thus deforming institutional structure of society. This has significantly influenced the reproduction of social and economic crisis. The aforesaid has enabled a number of quasi-institutional behavior, which led to the increase of non-market forms of appropriation and other deformities. In the absence of real institutional control and institutional change, and even institutional adaptation, all of these factors coexist in a system of limited access to resources eventually will turn into a quasi-institutional monism, which ignores the massive social interests, subordinating objective regulators to the party control, imposing the narrow lobbying interests and subjective regulators of behavior. Many economists have warned that inadequate institutions have a destructive effect on the valorization of economic resources. Hence, to identify and overcome the mentioned phenomena, processes and behaviors, it is necessary to consider and analyze the relevant elements of institutional behavior recommend by the NIT and the convention theory.

3. GENERAL HYPOTHETICAL MATRIX FOR RESEARCHING AND INSTITUTIO- NAL MODELING OF THE BASIS FOR ECONOMIC DEVELOPMENT Given that this is a study of numerous elements and attitudes towards the above- mentioned key issues from several respectable NITs and the convention theory, we decided to show it hypothetically and matrically. In the general hypothetical matrix for institutional modeling and researching the factors of economic development, vertically are listed the key analytical questions, and horizontally are listed the views and recommendations, as well as relevant theoretical answers to them (Table 1). Everything was done accordint go D. North (2006, p. 163) statement: "In order to improve the institutional structure we must first have a clear understanding of the sources of such institutional structure." Thereby were taken into consideration the views of K. Shepsle (1986, 1989) about the "institutional equilibrium" as well as affirmative interpretations of the institutional pluralism by several authors (Jarzabkowski, Smets, Bednarek, Burke, G. and Spee, 2013; Kraatz and Block, 2008).

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Milica Delibasic / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 147-159 Table 3: Hypothetical model matrix for researching the basis of economic development

Research parameters Dominant views and recommendations Public choice Institutional pluralism Property rights Relationship between politics and economics Relationship between formal and informal institutions Level and impact of alternative institutions An attitude towards state regulation An attitude towards opportunism An attitude towards rationality An attitude towards social and cultural capital An attitude towards experiences of current development path Form of order and an attitude towards resources’ access (open or restricted) An attitude towards violence

Source: self creation

The research process for a particular country requires separate analyses for the NIT, and separate analyses for the convention theory.

4. MATRIX OF THE NIT ELEMENTS RELEVANT FOR INSTITUTIONAL MODELLING OF ECONOMIC DEVELOPMENT Below is the original hypothetical matrix for research and institutional modelling of economic development. It is consisted of selectively chosen ruling views and recommendations from the basic research parameters, which are refined from the relevant neo-institutional theories.

Table 4: Model matrix for researching the NIT elements

Research Dominant views and recommendations parameters Public The mechanism for decision-making at the political level should be choice fundamentally changed and improved. The development of economic policy depends on it. Also, a new system of political decision making should be established, similar to the system of marketing decision-making. People do not change when leaving the market and paving the path to the political scene, they act the same way in social roles as well as in any private role: guided by reflections on personal benefits and realization of their own interests. The choice of economic subjects in any economic system depends on a social choice, directly or indirectly, sooner or later, by its nature. Since people act in the political sphere following their personal interests, it directly indicates the

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Milica Delibasic / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 147-159 link between business and politics, demystifying the notion of the state (government) as the sole protector of (state) social interests. "Rational" politicians support programs that contribute the growth of their popularity, prestige and opportunities to achieve victory in the next elections. They seek political rent through the political processes. There are cases when the government is unable to ensure the efficient allocation and use of social resources. That is called government failure. Therefore, it is necessary to constantly control the activities of the government and correct it in accordance with the socio-economic and political conjecture. The government failure (insufficiency, fiasco, misfire) is affected by the scarcity and asymmetry of information, the existence of powerful groups of influence, groups with special interests, active lobbyists, strong bureaucracy, imperfection of the political process (rational ignorance, lobbyism, manipulation of voting rules as a consequence of imperfect rule book, vote trading, seeking political rents, political-economic cycle, etc.) and restrictions regarding the possibility of control bureaucracy. The influence of the majority on the political decision- making depends not only on their preferences, the level of democracy, the specificity of the political conformation, the power of certain social groups, and the corresponding influence on politics, but also on the voting procedures (i.e. a rule book that it’s based upon), which is not neutral. Political power in the so-called "democratic societies" is "naturally" switched (with the logic of organized interests of small privileged groups) to the hands of political leaders, as the representatives of those groups, who win the elections over unorganized and unprotected (or poorly protected) interests of large latent groups, which is the opposite to the rule the majority (and thus the real democracy). This way, relatively small lobby groups (or individual branches, clusters, etc.) often receive various benefits and privileges (tax, customs, monopoly, information, etc.) on account of the million consumers and taxpayers, which serves as the basis of their unjust enrichment. High quality statute need to precisely define: equal justice for all, human and other rights and obligations of citizens, the level of economic freedom, the structure of the institutional environment, the power limits of basic economic institutions (state and market regulation), specifications and protection of property rights, moral and other restrictions of economic freedom, contract validity and insurance, regulation of natural and other monopolies, and all the other situations where the state should intervene (economic aid, transfers, restrictions, taxation, external effects, etc.). This way, the theory of social choice gives direct and indirect recommendations against influential latent groups with "special interests." Institutional The development requires institutional pluralism of economic institutions, pluralism through various combinations. It is an imperative in overcoming numerous contradictions between the public and private interests, in establishing a dynamic equality and harmonization of mutual competition in a variety of institutional forms of regulation and coordination of human activities (social and economic). Institutional pluralism (as a combination and synergy of all institutions) is a condition for the formation and sustainability of market-oriented structure of every economic system. It contributes to the functional reduction of transaction costs and an increase of economic efficiency. Representatives of the NIT advocate a specific form of institutional pluralism in the economy: for the synergy of command hierarchy and regulation within the company and market regulation as their own environment. They insist on "coevolutionary process" of ideology and institutions. According to them, institutional synergy of the market and state regulation has no rational alternative. 153

Milica Delibasic / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 147-159 Property Specified and protected property rights essentially bring multiple restrictions rights into economic behavior. In reality, there are numerous restrictions and resolutions of property rights. The restructuring of property rights leads to changes in the system of economic incentives. Entities respond to these changes of behavior. Underdevelopment of property rights causes underdevelopment of the market, and an increase of the negative external effects, and thus the economic slowdown. No one shall be privileged in accessing the resources, thus the possible privileges may only be the result of manipulation and social pathology. Every act of exchange is essentially an exchange of authority groups: making the deal in the market, exchanging two sets of property rights. Relationship The institutions regulate the social and economic relations. They actually between reflect through the relationship between the politics (ideology, party influence, politics and form of government, democratic institutions, etc.) and the economy (economic economics activities, structures, entities, behavior, economic institutions, etc.). Therefore, institutions influence all other forms of social superstructure. Relations between politics and economics are intertwined in a real life, absorbing certain ethical, cultural, and civilizational values, through which are implemented certain policies as a social consensus within the society. The institutions have a positive impact on the reduction, control and relativization of the political dominance over economy. Relationship Informal institutions (customs, traditions, norms, and religion) are not a between subject of study of the economic theory. They are accepted as a fact, changing formal and slowly – for hundreds and thousands of years, and many of them are formed informal spontaneously. institutions Formal institutions (property rights, politics, law, judiciary, bureaucracy) may hinder or stimulate the production possibility boundary. They are evolutionary built in the process of institutional competition. In the society there are also alternative institutions that operate in greater or lesser extent and they are a major threat to the institutional structure. Relationship There are doubts in the effectiveness of state regulation of the economy, to state which is questioned in the process of government decision-making. State regulation (public) sector is not an ideal economic mechanism, because, among other things, it is unable to perform the transformation of resources into social goods in a way that meets the demands of consumers of those goods. In all forms of activities, people are driven by their own interests and preferences. Therefore, political decisions may to a greater or lesser degree correspond with the interests of the population (i.e. a criteria of economic efficiency and social justice). Relationship In the real market it is not possible to fully control the contracting parties, due towards to the opportunistic behavior. It represents a major threat for the company opportunism business, leading to uncertainty in behavior between the contractual partners. It occurs before or after the contracting, focused on achieving own goals of economic agents, and is not limited by moral consideration. It is necessary to control the opportunism in order to reduce transaction costs. This can be achieved through the satisfactory management mechanisms, including the vertical integration of the management hierarchy. Relationship Real institution reliably regulate and rationalize individual behavior to the to rationality extent of increasing interactional rationality between individuals. The specifics of institutional rationality is dictated by three factors: a) holism, according to which the institutions are primary, and individuals are secondary, b) limitations of information, and c) dependency on social factors (socio-cultural capital). Rationality of institutional man includes the minimization of transaction costs

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Milica Delibasic / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 147-159 in in conditions of fraud and coercion. Rational behavior is placed in the context of universal norms and rules of conduct, acting either restrictively or motivationally. Therefore, economic rationality objectively manifests as bounded. Due to incomplete information, institutional behavior is characterized by procedural or bounded rationality, which is based on the selection of under- informed individuals who have subjectively developed their models, which differ from the models of other individuals. An individual is not able to make an objective optimal choice. To be "limitedly rational" means to be rational in the context of limited human capacity, and complexity of the environment. Therefore, chosen alternatives that are satisfactory but not optimal do not assume the knowledge on future events, nor the maximization of utility. From institutional perspective, a key source of bounded rationality of actors who choose in the conditions of true uncertainty is not a lack of information, but the fact that a decision-maker is generally faced with the information overload compared to his limited abilities to process them. Therefore, an importance of routines, habits, unwritten and written heuristics (rules in decision-making) is growing. A final result of choice depends on the selected procedure of decision-making. Although the institutions appear as exogenous in the processes of rational behavior and choice, they are extremely important. Especially is significant the pluralism of institutions. Relationship Socio-cultural capital is a set of social values, adopted norms of behavior, towards ideological beliefs and other social structures. As a set of intangible social socio resources and informal institutions, it has great importance, because in a cultural certain way it makes the connection between formal and informal institutions, capital or the macro institutional dynamics. Since institutions reflect the hierarchical structure of authority, which is a necessary condition for the effective punishment of violations, it can also affect the negative processes of decision- making monopolization and the abuse. Secondly, it creates the possibility of affirmation of imposed asymmetrical conditions for accessing the resources and strengthening the alternative institutions, allowing the particularism as a specific promotion of economic, political, social and other interests of privileged social groups and individuals. Relationship Institutional innovations strongly rely on the current Path Dependency (i.e. to the ex- latter events depend on former). Therefore, institutional innovations are not periences of possible in terms of the dominance of alternative institutions, or informal the previous mechanisms of choice. Relatively inefficient economic systems show that Path De- "history has significance." Dependence on the past development is determined pendency in the part of institutions primarily by the social factors. It is expressed on two levels: individual institutions i institutional system (such as economic). Very important factors of influence on the modern development are: network effect, coordination effect, the effect of cultural factors (mentality, education and social consent), and the effect of the longterm social capital (i.e. quasi- irreversibility of the original socialization). Closely related is also the effect of rejecting the new, which raises the question: how is it possible that bad institutions dominate over good ones, or why is negative institutional inertia (a.k.a. "institutional trap") prolonged? Relationship It is necessary to study the methods of limiting the violence in the society, and to access various forms of social pathology, which include: non-market rents resources appropriation, vote trading, corruption, the use of privilege, coalitions of and violence interests, ignoring the masses, protecting their own people, etc.). That can be achieved in two ways: the first is political manipulation of the economy in order

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Milica Delibasic / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 147-159 to build a privileged interest groups, and the second is institutional stimulation of political and economic competition, aimed at creating stimulating developmental conditions. The first corresponds with the so-called limited access (to the political and economic resources), and the corresponding "natural state" with numerous factors of economic and political development. The second method also corresponds with so-called open access and appropriate institutionally developed state. In countries with limited access, there are individual organizations and elite groups, which extract the rent due to privileges and certain tacit, "special rights", or personal "connections". Therefore the system is disbalanced with volatile order, the politics is linked to the economy and dominates over it, the minority (the alleged "elite") manages the majority, deformed informal and alternative institutions (which are extremely personified) are dominating, and organizational structures are very unstable. Limited access (inequality) is ensured by the deficit of the rule of law, insufficient guarantees of rights and freedoms, and the lack of competition in the political and economic system. Place in the hierarchy determines the position of individuals in relation to the law and the nature of a governance. Civil society and democracy have not been developed, the opposition is weak, and there is a partial provision of services by the state. Bureaucracy is poorly controlled and unprofessional. All this has a negative effect on economic growth, and on the adaptive efficiency. There are three conditions for the transition from the "natural state" (limited access) towards open access: a) the subordination of elite to the rule of law (equal treatment for everyone by the law), b) the existence of unlimited and stable organizations, which do not depend on the state nor of the specific individuals, and c) consolidating the control over armed forces and technologies of violence and demolition (curbing violence). The logic of "natural state" stems from the methods of solving the violence: elite (members of the ruling coalition) coordinate the privileges, including property rights and access to certain types of activities. Creation and appropriation of rents is manifested as the "glue" that holds the coalition together. It increases the cost of privilege, because elite turns into more productive, thanks to their organizations based on networking (hierarchy of personal relationships). Such organizational method drastically reduces the efficiency of society, economy, and politics. It produces a deep and intricated web of corruption, which is the most common in patron-client relationships. Its sustainability is based on the elimination of strong internal institutional structures. Open access in the economic system protects the political system from manipulation of economic interests, and it guarantees the equality of citizens and the shift of power in case of abuse. The political system should restrict access to the means of violence. Along with the judicial system, it ensures respect for the prohibition of the use of violence. This allows strong and transparent institutions that provide impersonal democratic and party competition, preventing illegitimate use of violence.

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Milica Delibasic / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 147-159 5. MATRIX OF THE CONVENTION THEORY ELEMENTS RELEVANT FOR INSTITUTIONAL MODELING OF ECONOMIC DEVELOPMENT Below is the original model matrix designed to analyze the matter in question. It consists of selectively chosen ruling views and recommendations from basic research parameters identified from the respectable French convention theory.

Table 5: The model matrix for researching the convention theory elements

Research Dominant views and recommendations parameters Public choice No form of argumentation of the so-called "institutional worlds" has a universal character, because it contradicts other forms of argumentation, whose analysis allows to explain the nature of the critical situation. Each of the coordinated forms in some sense is a constitutional agreement, whose character is manifesed only in the process of dispute with other forms of institutional coordination. Institutional An existence of numerous institutional "worlds" (subsystems) is condi- pluralism tioned. Proposed is their synergism, which maintains and provides dynamic balance and compromised harmonization of their relations. It neutralizes possible expansion of individual subsystems at the expense of other subsystems (i.e. it eliminates institutional monism). This is not the case of the market imperfections per se, but the characteristics of complex economic reality where all institutional "worlds" coexist. In the so-called "critical situations" (conflict and/or non-conflict relations between the various institutional subsystem) it is possible to use different ways of the coordination, not just one as a supposedly "naturally given and objective." There are a lot of important causes underlying the economic motivation, as well as many ways of economic coordination. Relationship The central place of institutional analysis belongs to the politics, because it between is an ambience of mutual interaction between economic agents which ini- politics and tially bears a political character. Conventions act as the representatives of economics a common world, and institutions as mechanisms for monitoring the rules and objects of the structure, and thus simplifying the process of forming joint worlds Relationship to Free market and government intervention are not the only universal forms state regulation of coordination. Essential is the existence of the prescribed norms and rules of conduct (in addition to the convention - an agreement). State regulation must ensure satisfaction of political adaptation (or suitability) and criteria of the common good in the society. Relationship Rationality is given a relative and interpretive character, because people in to rationality everyday economic activities, in addition to their own rational budget, also must apply and respect different conventional frameworks, through which they understand the intentions and actions of other people. This requires cognitive, and evaluational (interpretative) efforts. Interpretative rationality is the ability of harmonizing economic activities through oriented behavior, comprehensible to all participants in the transaction. It includes the ability to form correct expectations from another entity’s action, or the proper interpretation of his intentions and plans, allowing others to understand (interpret) his intentions and actions. The rational-economic individual is positioned in the simplest institutional

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Milica Delibasic / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 147-159 environment, where nature of institutions influence the substance of individual rationality. He must be able to assess the characteristics of the collective that interest him, which are the use factor for him. Therefore, it is essential that homo economicus, in addition to rationality, knows linguistic interpretation of the processes. Rational behavior draws resources from institutional environment and par- ticipates in its transformation. Uncertainty and lack of information can be reduced using agreements (conventions), through introduction of the general procedure of evaluation (interpretability) as a prerequisite for coordination. Rationality is just one of the incentives of market exchange. For this reason, to indicate these actions, the term reasonable, not rational, has been used.

6. CONCLUSION In the context of affirmation of institutional pluralism, representatives of the NIT recommend strong institutions, including the state and market regulation, which are limited in the realization of their own functions. Institutions guarantee that state and market regulation can coordinatedly perform their function. This means that strong and pluralistic institutions, as "rules of the game" (North, 1990), serve as a means of protection from any kind of opportunity behavior, among others from all forms of non-market behavior, abuse of state regulation, and various stalling of institutional activity. An institutionalized selection and institutionalized exchange are the conditions for sustainable economic development. However, the degree of institutional changes in the economy and society is often limited by opportunistic quasi-institutional behavior, especially in relations: pluralism-monism, formal-alternative, changes-status quo, horizontal-vertical, mass-individual, legal-privileged, political-economic, etc.. Numerous restrictions in economic reality (including institutions) influence economic behavior, which therefore has a nature of bounded rationality. Limited are intellectual capital, information, and access to the resources. If one adds opportunistic behavior, uncertainty, risk, previous development, socio-cultural capital, unprotected and unspecified property rights, increase of transaction costs, incomplete contracts, influence of politics, alternative institutions, and global environment, etc., it becomes clear just how big is a gap between the theoretical models of institutional behavior and its actual implementation. Theoretical research has confirmed the initial hypothesis that the institutional modeling of basis for economic development need to be based, inter alia, on the elements and recommendations of respectable NIT, and the convention theory, at key research issues (parameters). The aforesaid has been presented in the originally created research matrix for the hypothetical modeling of institutional behavior. Thus it was started from the relevance of the five key characteristics of institutions, which have been listed in the Introduction. There have been proposed two original hypothetical model-based matrices for broader and deeper study of the institutional basis for economic development in each particular country. It consisted of selectively chosen ruling views and recommendations from the basic research parameters, identified from the two groups of relevant theories: the NIT and the convention theory.

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Milica Delibasic / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 147-159 REFERENCES Delibasic, M. (2014), “The Post-Socialist Transition Through the Prism of O. Williamson’s In- sight”, Montenegrin Journal of Economics, Vol. 10, No. 1, 13-24. Draskovic, M., Bauk, S., Delibasic, M. (2016), “Testing the Level and Factors of Institutional Rationality in Montenegro, Serbia and Bosnia and Herzegovina”, Economics and Sociology, Vol. 9, No. 2. Elster, J. (1997), Nuts and Bolts for the Social Sciences, Cambridge University Press, Cam- bridge. Greenwood, R., Raynard, M., Kodeih, F., Micellota, E., & Lounsbury, M. (2011), “Institutional complexity and organizational responses”, The Academy of Management Annals, Vol. 5, No. 1, 317-371. Hayami, Y., Godo, Y. (1997), Development Economics From the Poverty to the Wealth of Na- tions, Third Ed., Oxford University Press, Oxford. Jarzabkowski, P., Matthiesen, J., Van de Ven, A. (2009), “Doing which work? A practice approach to institutional pluralism”, In Lawrence, T. B., Suddaby, R., and Leca, B. (Eds.), Insti- tutional work: Actors and agency in institutional studies of organizations, Cambridge Uni- versity Press, Cambridge, 284-316. Jarzabkowski, P., Smets, M., Bednarek, R., Burke, G., Spee, A. P. (2013), “Institutional ambidex- terity: Leveraging institutional complexity in practice”, In Lounsbury, M., & Boxenbaum, E. (Eds.), Institutional logics in action, 37-36 Kraatz, M. S., Block, E. (2008), “Organizational implications of institutional pluralism”, In Greenwood, R., Oliver, C., Sahlin, K., and Suddaby, R. (Eds.), The sage handbook of organizational institutionalism, Sage, London, 243-275. North, D. C. (1991), “Institutions”, Journal of Economic Perspectives, Vol. 5, No. 1, 97-112. North, D. C., Walis, J. J., Weingast, B. R. (2009), Violence and Social Orders – A Conceptual Framework for Interpreting Recorded Human History, The Syndicate of the Pres of the Cambridge University. North, D. (1990), Institutions, Institutional Change and Economic Performance, Cambridge Uni- versity Press, Cambridge. North, D. (2005), Understanding the Process of Economic Change, Princeton University Press. Scott, W. (2004), “Institutional Theory: Contributing to a Theoretical Research Program”, Chap- ter prepared for Great Minds in Management: The Process of Theory Development, Ken G. Smith and Michael A. Hitt, eds. Oxford University Press, Oxford UK. Shepsle, K. (1986), “Institutional Equilibrium and Equilibrium Institution”, in Weisberg (Ed.), Political Science: The science of politics, Agathon Press, New York. Shepsle, K. (1989), Studying Institutions: Some lessons from the rational choice approach, Journal of Theoretical Politics, Vol. 1, No. 2, 131-147. Ostrom, E., Gardner, R., Walker, R. (1994), Rules, Games and Common-Pool Resources, Univer- sity of Michigan Press, Ann Arbor. Scott, W. R. (1995), Institutions and Organisations, Sage, London. Stulhofer, A. (1995), “O racionalnosti, normama i institucijama: evolucija sociokulturnog kapitala kao model institucionalne promjene”, Društvena istraživanja, Vol. 4, No. 6 (20), 953- 981. Williamson, O. E. (1993), “Transaction Cost Economics and Organization Theory”, Industrial and Corporate Change, Vol. 2, No. 2, 107-156.

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Montenegrin Journal of Economics

Vol. 12, No. 2 (2016), 161-175 ‘

GDP and Net Migration in Some Eastern and South-Eastern Countries of Europe. A Panel Data and Bayesian Approach

Mihaela Simionescu1, Daniel Ciuiu2, Yuriy Bilan3, and Wadim Strielkowski4

1 Senior Researcher, dr hab., Romanian Academy Institute for Economic Forecasting, Romania [email protected] 2 Reader, Ph.D., Bucharest Technical University of Civil Engineering Institute for Economic Forecasting, Romania [email protected] 3 Assoc. prof., Ph.D., Szczecin University, Microeconomics Department, Poland, [email protected] 4 Associate Researcher, Ph.D., Cambridge Judge Business School, University of Cambridge, Cambridge, United Kingdom; [email protected]

ABSTRACT ARTICLE INFO Received March 06, 2016 This paper analyzes the relationship between the GDP and the Received in revised form –May, 29 2016 net migration using the comparative approach represented by the Accepted June 11, 2016 panel data and Bayesian analysis. The panel data analysis is Available online June, 15, 2016 made for the period 1991-2013 in Central and Eastern European countries (CEECs): Czech Republic, Slovakia, Ukraine, Poland, JEL classification: Bulgaria, Romania, Croatia, Slovenia and Hungary. The Bayesian F22, O15; approach is utilized for checking whether Poland and Ukraine have similar expectation of GDP and net migration during 1991- DOI: 2013. A negative correlation was recorded between net migration and the real GDP rate in the previous period. During the period of 10.14254/1800-5845.2016/12-1/10 1991-1994 corresponding to transition, each 10 percent increase in the GDP rate caused a 0.6 percent decrease in net Key Words: migration at the significance level of 5%. A higher increase was GDP, registered in the economic depression (1994-2000), while the net migration, greater decrease, with 4.58 percentage points for each 10 per panel data, cent in the GDP rate, was observed for the period of economic Bayesian test, boom. Computing the differences between Ukraine and Poland, Central and Eastern European countries we obtained the expectations of -17.7187 and 15.745 with a higher variance of the estimator for Ukraine.

1. INTRODUCTION Central and Eastern European countries (CEECs) record rising immigration, a process that puts the responsibility on their government to come up with the targeted immigration strategies for selecting a certain type of migrants. The economic literature attempts to study this problem looking at the immigrants’ absorption, their characteristics, and the consequences of their 161

Mihaela Simionescu, Daniel Ciuiu, Yuriy Bilan, Wadim Strielkowski / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 161-175 presence in certain countries. However, few economists are interested in finding out the real determinants of international migration. With regard to this, it has to be noted that the trends in European migration in the last decade underwent a high number of spectacular changes. A series of studies from economic literature analyzed migration developments and estimated of the statistical relation between migration and its determinants (e.g. GDP rate, wage, unemployment rate, or productivity). The majority of these studies were based on the theories related the migration impact on labor markets of the target countries. It is considered that migration influences overall labor supply and wage in case of economies with fixed capital and small product range. The main goal of our paper is to analyze the relationship between GDP and net migration in CEECs: Bulgaria, Romania, Croatia, Slovenia, Ukraine, Poland, Hungary, and the Czech Republic. Therefore, the panel data and the Bayesian approach were both applied to achieve comparative and compatible results. Our results make us to conclude that the economic prosperity influences immigration more than the unstable periods that are less favorable for immigrants in those specific countries. The paper is structured in several sections. After the introduction, the two approaches (panel data and Bayesian approach) are described and the empirical results are presented. The last section concludes by giving important interpretations and discussion of results.

2. LITERATURE REVIEW: EFFECTS OF IMMIGRATION The literature regarding the effects of immigration (there are many studies regarding to US and only few papers for Europe) follows various strands. Some of them provide predictions on the effects of migration on GDP and employment in a simulation framework supported by the Computable General Equilibrium (CGE) Models. The simulations consider competition between native labour and migrants, on various skill groups, considering mobility between industries and regions as an effect to immigration phenomenon, allowing the sector composition modification and supposing that demand consequences from the larger household sector that also include the immigrants. Many studies analyzed the consequences of growth of immigration in convergence models. According to observations of Barro and Sala-i-Martin (2004), the effect of net migration on GDP per capita rate is small and positive, affecting the convergence parameter in a positive way. Etzo (2008) and Ozgen et al. (2010) offered surveys of the literature on this topic and Niebuhr et al. (2012) proposed an application for German economy. Barro and Sala-i-Martin (2004) discovered a negative impact of migration on GDP per capita growth. Ozgen et al. (2010) drew the conclusion that empirical applications usually proposed a small and positive effect with only one percentage point increase in migration rate when the GDP per capita increases only about 0.1 percent. Shioji (2001) explains that this is due to two countervailing effects migration. The quantity effect, referring to population growth, generates the reduction of growth and foster convergence. Moreover, the composition effect, referring to human capital composition of migrants, supposes a positive growth rate and economic divergence. Clowes and Bilan (2014) having analyzed income per head trends in the Czech Republic, Hungary, Poland and Romania, it was revealed that higher GDP capita was a key factor in successful economic recovery of the countries during the global downturn. Boeri and Brücker (2001) used an econometric model that predicted that the number of immigrants from the NMS in the Old Member States might increase from less than one million in 1998 to some three to 4.5 million people in 2030. Fassmann and Münz (2002), Čajka et al. (2014)conducted various macro and micro econometric studies for the estimation of migration flows from the East to the West. The functional form for the effect of GDP on migration is not

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Mihaela Simionescu, Daniel Ciuiu, Yuriy Bilan, Wadim Strielkowski / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 1619-175 straightforward in literature. Pedersen et al. (2004) showed that the relationship is not necessarily linear, but in many cases it was observed a form of an inverted U-shape. Hatton and Wil- liamson (2002) made a quantitative evaluation of the demographic and economic determinants of the migration in the entire world. The authors studied aspects like: the effect of poverty and inequality on migration, the distinction between ex-post migration and pressure of migration, the actuality of migration theories. Jennissen (2003) studied the influence of economic factors on migration in the countries from Western Europe during 1960-1998. The dependent variable (net migration), is explained using exogenous variables like income per capita, education level and unemployment rate. The results based on regression models showed that the unemployment rate has a negative impact on net international migration. Blanchflower (2007) showed that the immigrants to UK increased the supply more than the demand in short term. Moreover, it seems that the migration flow has advantages like a lower inflation pressure and a smaller natural unemployment rate. Longhi et al. (2008) showed that among 185 estimates of the effects of migration on unemployment analyzed in 13 studies, 81.6 % remain insignificant 12.4 % are significantly negative, if the probability is 95%. Interna- tional migration may determine internal migration flows in the recipient nation. Therefore, the unemployment impact evaluation over the regions of the country can determine spurious positive effect of immigration on labour market. Cadil and Kaderabkova (2012) evaluated the effect of migration on convergence among regions in the Czech Republic, discovering that there is no general relation between migration and GDP/capita or wages growth, neither positive, nor negative. Brunborg and Cappelen (2009) proposed an econometric model for migration in Norway, using as explanatory variables the unemployment rate in Norway and the income level in Norway relative to the average of OECD countries. Ojapinwa (2012) determined the migrants’ remittances inflow considering as independent variable the GDP and other macroeconomic indicators. Passel, D'Vera Cohn and Gonzalez- Barrera (2012) made a description of the characteristics of the Mexican immigrants to USA. Huber and Tondl (2012) analyzed the relationship between migration and regional convergence in European Union. It was made an econometric study to measure the impact of migration on regions from Europe and EU-27 during 2000-2007. The migration depends on output per capita and the labour productivity, but the regional perspective has not an influence on migration. In the European regions with low GDP, the migration does not determine convergence. Bijak et al. (2013), Miłaszewicz et al. (2015), Bilan (2014), Minneci (2015), Oliveira et al. (2015) presented some scenarios regarding the future evolution of international migration in 27 countries from Europe during 2002-2052. The authors described the migration theories and simulations and predictions are made for net migration, labour force and population from selected European countries.

3. PANEL DATA APPROACH Our empirical approach is in accordance with the recent researches made for several East- ern and Western countries. The recent studies provide evidence that there is no specific positive or negative relationship between GDP and migration. The relationship depends on the particular set of data. A comparative analysis based on econometric results for Eastern and South- Eastern Europe countries was not made before. The variables are represented by the real GDP rate and the net migration (difference between the number of persons entering and leaving a country during the year per 1,000 people). 163

Mihaela Simionescu, Daniel Ciuiu, Yuriy Bilan, Wadim Strielkowski / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 161-175 The period is 1991-2013 and the data refer to seven countries from Eastern and South-Eastern Europe: Ukraine, Poland, Bulgaria, Romania, Croatia, Czech Republic, Slovenia, Slovakia and Hungary. The dependent variable is the net migration and the independent one the GDP real rate. A positive value of the net migration shows that more people entering the country than leaving it, while a negative one implies that more people leaving than entering it. The real economic growth rate builds onto the economic growth rate by taking into account the effect that inflation has on the economy. The economic growth is concerned with the long-run trend in production due to structural causes such as technological growth and factor accumulation. We used annual data, so the problem of seasonality did not appear here. The net migration is computed the same in other countries. The World Bank offers data sets with the values of net migration for almost all the countries, but this database has a short length. The start regression is the following one: (1) where:

net migration in country i and year t - real GDP rate in country i at time t-1 individual effects - the error

First of all, we have to decide if we use a usual regression or a panel analysis. The OLS estimator is biased and inconsistent, the individual effects being present (Baltagi, 2008). The application of Hausman test was made in order to decide if the model with fixed effects is better than the one with random effects or else. The probability associated to Hausman statistic is less than 0.05, the fixed effects model being better, according to results in Table 1. However, we have to take into account the economic reasons for this type of model. The standard model used for the errors starts from two important assumptions: the errors are homoscedastic and non-auto-correlated. The results of the applied tests put into evidence auto-correlated and heteroscedastic errors. Therefore, some robust estimators are necessary.

Table 1. Results of Hausman test

Test Summary Chi-Sq. Statistic Chi-Sq. d.f. Prob. Cross-section random 0.5420 1 0.4787 Cross-section random effects test comparisons: Variable Fixed Random Var(Diff.) Prob. GDP_rate(-1) 0.1472 0.2564 0.0197 0.4787 Cross-section random effects test equation: Dependent Variable: net_migration Cross-sections included: 9 Total pool (balanced) observations: 180 Variable Coefficient Std. Error t-Statistic Prob. C -7.3489 3.8012 -1.9370 0.0520 GDP_rate(-1) 0.14657 0.0162 9.3345 0.0000

Source: own

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Mihaela Simionescu, Daniel Ciuiu, Yuriy Bilan, Wadim Strielkowski / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 1619-175 For the two types of models (fixed effects model and random effects model), the hypotheses of errors‘ homocedasticity and auto-correlation were checked and the results are presented in Table 2.

Table 2. Results of the homoscedasticity and auto-correlation tests

Tests: Autocorrelation Heteroscedasticity Fixed effects model F(1,8)=5.32 Chi2(9)=16.919 F computed= 47.23 Chi2 computed= 35.18 Random effects model F(1,8)=5.32 Chi2(9)= 16.919 F computed= 88.44 Chi2 computed= 54.23

Source: own

Stata software package proved to be efficient in computing the regression with standard errors proposed by Driscoll and Kraay (1998), using the command xtscc. It is estimated the fixed effects model with Driscoll and Kraay errors that are heteroscedastic, auto-correlated up to a certain degree and possibly correlated with other groups. The results are presented in Table 3.

Table 3. Estimations for fixed and random effects models (1991-2010)

MODEL Fixed effects model Random effects model Constant 45.16 (18.502)* 53.39 (23.049)** -0.00192 (0.0047)* -0.036 (1.368)** SIC (Schwarz information criterion) 463.223 562.784

Note: In brackets Driscoll-Kraay errors were written, the level of significance being 1% (*) and 10% (**); Source: own

For the fixed effects model the coefficient is significant compared to the other model, that with random effects. Moreover, the SIC criterion has a lower value for fixed effects model. The results for overall sample showed a negative correlation between net migration and real GDP rate when fixed effects model is used. Indeed, recent empirical researches put in evidence a decline in migration when a considerable increase was anticipated for GDP. We chose the fixed effects model because we have logical arguments: the statistical tests results are confirmed by the economic reality: there is correlation between the errors and the exogenous variable (real GDP rate in the previous period). Individual effects that affect the net migration (for example, the level of development of each country) is correlated with the GDP rate. An increase with one percentage point in average in the real GDP rate in the previous period will determine a decrease in the net migration with 0.19 percentage points. Therefore, we used three models corresponding to three periods: a) 1991-1994, b) 1995-2000, and c) 2001-2013.

The reasons for choosing these periods are related to some common aspects for the 7 countries. The period of a relative decline of GDP rate for these countries was interrupted by a relative growth in 1995-2000. Instead of b in each model we will have b1, b2 and, respectively b3. The models‘ coefficients and the associated standard deviations that are written in brackets can be observed in Table 4. 165

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Table 4. Coefficients and standard deviations for fixed and random effects models corresponding to the three periods

Period Fixed effects model Random effects model Coefficient (standard deviation) Coefficient (standard deviation) 1991-1994 -0.006 (51.22)** 0.012(387.15)*** 1994-2000 -0.036 (62.018)** -0.0901 (114.65)*** 2000-2013 -0.0458 (86.22)*** -0.742 (13.98)***

Note: *p<1% **p<5%, ***p<10%; Source: own

A negative correlation can be observed between net migration and the real GDP rate in the previous period. For a level of significance of 5%, in the period 1991-1994 corresponding to transition, each increase with 10 percentage points in the GDP rate determined a decrease in net migration with 0.6 percentage points. A higher increase was registered in the economic depression (1994-2000), while the greater decrease, with 4.58 percentage points for each 10 percent change in the GDP rate, was observed for the period of economic boom. These results make us to conclude that the economic prosperity influences more the migration than the unstable periods are less favorable for immigrants in that specific country. We take the case of Ukraine in order to estimate a single regression model with a dummy variable, corresponding to different periods (1995-2000 and 2001-2013). There are not statistically significant and economically reasonable results for Ukraine regression in 1991-1994. The dummy variable is called “period” and it takes the values 0 for the first period and 1 for the second one. For the last period we do not have to consider another value of the dummy variable. We have enough evidence from the graph to identify a correlation between net migration and those periods. Moreover, the corelation between GDP and the economic cycles is obvious. We will consider the following regression model for Ukraine: (2) The GDP rate and the dummy variable are not correlated with the errors. The matrix of correlation is computed, observing coefficients of correlation closed to zero (0.0354, respectively 0.115). The data series are stationary. Taking into account that we have few data for Ukraine, the coefficients are estimated by stochastic simulations (bootstrap procedure). The number of replications is 10 000, the residuals being re-sampled. The Breusch-Godfrey Serial Correlation test for a level of significance of 5% has the test’ statistic equaled to 5.415, which is less than the critical value of 5.979. Therefore, the errors are independent. Moreover, the probability associated to White test is less than 0.05, fact that implies that the errors are homoscedastic. The results of these tests are presented in Table 5. The normality of the errors is assured by the large number of replications.

Table 5. Tests for serial correlation of order 1 and homoscedasticity

Test Computed statistics Critical values Breusch-Godfrey Serial Correlation test 5.4225 5.9889 Heteroskedasticity Test: White test 12.5965 15.8026

Source: own

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Mihaela Simionescu, Daniel Ciuiu, Yuriy Bilan, Wadim Strielkowski / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 1619-175 The assumption of the regression model being checked, the following model was estimated, the parameters being statistically significant: (3) For Ukraine separately analyzed the sensitivity of the net migration to the previous GDP rate coefficient is higher. Higher GDP determined lower migration abroad. An explanation could be that the economic growth determines Ukrainian people to remain in Ukraine and also attracts foreign here.

4. BAYESIAN APPROACH Let us consider X a random variable whose distribution depends on the parameter  . If

X is discrete random variable, we denote by px 00  PX x , and, if X is continuous random variable, by fx0 the pdf of X that is conditioned by   0 . In the Bayesian inference the parameter  is considered a random variable having the pdf g, called the prior distribution of  . The posterior pdf of  is:

px00 g  gx0  (4)  px  g d  in the discrete case, respectively:

fx 00 g  gx0  (5)  f xgd    in the continuous case.

2 2 According Preda (1992), if XN  ,  with known  and prior distribution of  is N , 2 , then the posterior distribution of  is:  2222X    N 22, 22 (6)   It is also presented (see Preda, 1992) that a two-sided significance test in this case should yield the following results. We test the null hypothesis H00:   with the first degree error  against the alternative hypothesis H10:   .

We consider p0 the prior probability to have   0 , and, using this value we built a prior distribution having the cdf.

1,pG00 if  G    (7)  ppGif001,    0 where G is a continuous cdf.

It has to be noted that the cdfG is continuous in all values of  except 0 , where it has a jump equal p0. Usually, p0 is taken 0.5, from maximum entropy principle (Preda, 1992).

The posterior probability to have   0 is

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pfx00    PX0 (8) pfx 1 p fx g d 00 0  

We accept H0 if and only if the above posterior probability is at least 1 .

In Ciuiu (2013) we use an estimator of  , ˆ, instead of X, and the above relation is rewritten as ˆ pg00  p P ˆ  0 (9) 0 ˆˆ pg00 11, p 0 g 0 p 0 p 0 R  0 where g   R , ˆ  0 (10) 0 ˆ g 0 

In the case of normal distribution with known variance  2 , in Ciuiu (2013) there is denoted 1   , and it is considered   0 . The above value of R becomes  2 0 2  2 ˆ  1      2  R ˆ,,2  exp  (11)    22 2  2 1 212  

Ciuiu (2013) runs the left-sided test (where the alternative hypothesis is H1 :0  ) and the right-sided test (where the alternative hypothesis is H1 :0  ). There are considered as prior distribution either the left (right) truncated normal distribution, or distribution such    is exponential. It is proved that the posterior distribution is left (right) truncated. More exactly, in the case of left-sided test, we have:       g            (12)   221  ˆ    2 2  1 1 g ˆ,    2 ˆ    2  1 in the case of left-truncated distribution, and ge    ˆ  (13)  ˆ  g ,   ˆ      168

Mihaela Simionescu, Daniel Ciuiu, Yuriy Bilan, Wadim Strielkowski / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 1619-175 where   0 , in the exponential case. In the case of right-sided test, we have       g           (14)   221  ˆ    2 2  1 1 g ˆ,    2 ˆ     2  1 in the case of right-truncated distribution, and ge     ˆ  (15)  ˆ  g ,   ˆ      where   0 , in the exponential case. These tests were performed for the regression coefficients of the household savings in terms of nominal average wages, and the example is from Jula and Jula (2012), where the Student test is performed. 2 22 22 Solving the equation P0,0,     1 we obtain first the solution  0 . Next, for  0 2 ˆ we solve the equation P0,,     1 , and we obtain the solution   min if   0 or in the ˆ case of right-sided test and right-truncated normal distribution, respectively   max if   0 or in the case of right-sided test and right-truncated normal distribution (Ciuiu, 2013). The condition to accept the null hypothesis if ˆ  0 , and to reject it if ˆ   (a natural assumption) is to choose   min , respectively   max . In the exponential case we solve the equation

P0,    1 , and we obtain the solution   max . The condition to accept the null hypothesis ˆ ˆ if   0 is to take   max . Finally we estimate the interval of confidence for  as the interval in which we must have the value of the estimator such that we accept H0. Using this interval and the normal distribution, there is estimated the power of the test. In the case of unknown variance (hence unknown  ) we consider the prior distribution of  m2b 2 as a,b , obtaining the posterior distribution a, 2 , where S is an estimator 2 mbS  2 ˆ of the variance of  with m degrees of freedom (Ciuiu, 2013). P is replaced by a value P that does not depend on  : the expectation of P according the above posterior distribution of  . The same expectation we do for the power of the test:

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  E (16)   Consider the net migration and the real GDP for Poland and Ukraine in the period 1991- 2013. First of all we test if the two countries have the same expectation in the case of the two above variables. We compute the differences between Ukraine and Poland, obtaining the expectations - 17.7187 and 15.745, and the variances of the estimators (variances divided by 23) 640.37911 and 32.05437. First we consider known variances equal to the above estimators. For the net migration the results are listed in Table 6. The powers of the test in Table 6 and Table 7 are calculated if the real value of the parameter is null, if its real value equals the right limit of the acceptance interval and if the real value equals the estimated value.

Table 6. The Bayes tests in the case of net migration, known variance- Poland

Probabil-

2 2 Type of ity of Interval for Power of  0 /   /    max max the test accept- accepting H0 the test ing H0 0.99136 (-0.27412, Two-sided -24<-23.14854 0.93692 0.99136 0.27412)  2  0.99324 230000 0.49979 Left-sided -1<-0.73681 0.93608 (-0.01318,0) 0.5 0.75793 0.90563 Two-sided -60<-55.78763 0.93721 (-3,3) 0.90629  2  2 0   0.92606 230536. 230536. 0.49291 478 478 Left-sided -9<-8.26718 0.937 (-0.44996,0) 0.5 0 0.84124 (-5.06899, Two-sided -6<-5.06877 0.93818 0.84435 5.06899)  2  0.87535 250000 0.48925 Left-sided -1<-0.66572 0.91257 (-1.92383,0) 0.5 0.7496

Source: own

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Probabil- 2  0 / 2 Type of ity of Interval for Power of the  /    max the test accepting accepting H0 test max H0 0.99472 (-0.03747, Two-sided 23>22.95 0.28009 0.99472 0.03747)  2  0.99989 11000 0.49741 Left-sided 4>3.29227 0.21047 (0,0.04102) 0.5 0.99724 0. 15>12.4813 Two-sided 0.28445 (-0.75,0.75) 0.89553  2  2 9 0   0.99774 11539. 11539. 0.49295 57455 57455 Left-sided 2>1.73363 0.28611 (0,0.1) 0.5 0.99714 0.84329 (-1.11927, Two-sided 2>1.11835 0.29005 0.84628 1.11927)  2  0.99655 15000 0.48858 Left-sided 0.5>0.14488 0.23351 (0,0.16211) 0.5 0.99704

Source: own

For instance, in the case of known variance, the first accepting interval is (-0.27412, 0.27412). The power of the test is 0.99136 if the real expectation is -0.27412 and the test power is the same for a real expectation of 0.27412. The highest powers of the test for net migration with known variance were obtained for the 2 2 case when we have a two-tailed test with 0  230536.478 and   230000. The highest powers of the test for real GDP with known variance were obtained for the case 2 2 when we have a two-tailed test with 0  11539.57455 and   11000. For real GDP, in the case of known variance, the first accepting interval is (-0.03747, 0.03747). The power of the test is higher than in the case of net migration, being 0.99472 if the real expectation is - 0.03747 and the test power is the same for a real expectation of 0.03747. In Table 8 and Table 9, Bayes tests are computed in the case of real GDP of Ukraine.

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Probabil- Interval for Type of ity of Power of  2 /  2    accepting 0 max  /  the test max accept- the test H0 ing H0 0.96673 (-1.03661, 2 Two-sided -60<-55.52595 0.93642 0.96676   1.03661) 230000 0.97458 Left-sided (-,0) 0.5 0.90563 2 2 (-2.81232, 0    Two-sided -57<-56.06537 0.93678 0.90638 2.81232) 233103.8 233103.82 0.92908 809 2809 Left-sided (-,0) 0.5 0.86337 (-4.27802, 2 Two-sided -5<-4.27786 0.93746 0.8655   4.27802) 240000 0.8953 Left-sided (-,0) 0.5

Source: own

The highest powers of the test for net migration with unknown variance were obtained for 2 2 the case when we have a two-tailed test with 0  233103.82809 and   230000. The power of the test is lower than in the case of known variance, being 0.96673 if the real expectation is -1.03661 and 0.96676 for a real expectation of 1.03661. The highest powers of the test for real GDP with unknown variance were obtained for the case 2 2 when we have a two-tailed test with 0  11815.32174 and   11000.

Table 9. The Bayes tests in the case of net migration, unknown variance- Ukraine

2 Interval for  0 / 2 Type of Probability of Power of  /    max accepting  the test accepting H0 the test max H0 0.92978 (-0.49315, Two-sided 30>28.04654 0.29021 0.93007  2  0.49315) 11000 0.99805 Left-sided (-,0) 0.5

2 0.90584 2 (-1.28243, 0    Two-sided 26>25.6229 0.29564 0.90649 1.28243) 11815. 11815. 0.95666 32174 32174 Left-sided (-,0) 0.5 0.88263 (-0.8264, 2 Two-sided 1>0.70263 0.29782 0.88398   0.8264) 12000 0.99669 Left-sided (-,0) 0.5

Source: own

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Mihaela Simionescu, Daniel Ciuiu, Yuriy Bilan, Wadim Strielkowski / Montenegrin Journal of Economics, Vol. 12, No. 2 (2016), 1619-175 The power of the test is lower than in the case of known variance, being 0.49315 if the real expectation is -0.49315 and 0.93007 for a real expectation of 0.49315.

5. CONCLUSIONS We analyzed the influence of the GDP dynamics on the net migration for seven CEE countries in the period of 1991-2013.The general results of our analysis showed that the increased income, where GDP is used as a proxy (Napolitano and Bonasia, 2009), has a negative influence on the net migration, which is calculated as a difference between the entering and leaving number of persons. This result appeared to be true both for models with fixed and random effects. Our main result become seven more interesting if one pays attention to the details. The proposed model with assumed fixed effect provided better results in all specifications than the model with random effects. Statistically significant results were observed also when the sample was divided into three different time periods. GDP rate has negative influence on the net migration dynamics during the assumed periods of the transition, depression and economic boom in the Eastern Europe. In addition, the results we got suggest that the periods of economic prosperity (here, ‘economic boom’ in 2000- 2010) influence more net migration than in the other periods, making it lower with each addition percent of the GDP growth, which is not intuitively anticipated. For Czech Re- public and Slovakia, there is a negative and significant relationship between GDP and net migration. This conclusion was also obtained by Strielkowski (2012). In these countries the main reasons for emigration had a political and economic explanation. Many people felt free after the totalitarian regimes, while for some of them the standard of living was still unsatisfactory. For Ukraine separately analyzed the sensitivity of the net migration to the previous GDP rate coefficient is higher. Higher GDP determined lower migration abroad. Consider the net migration and the real GDP for Poland and Ukraine in the period 1991-2013. First of all we test if the two countries have the same expectation in the case of the two above variables. Computing the differences between Ukraine and Poland, we obtained the expectations -17.7187 and 15.745, and the variances of the estimators 640.37911 and 32.05437. Separate investigation for Ukraine supported the achieved results, when each next year and positive GDP trends make fewer Ukrainians leave the country and more Ukrainians to come back. These unexpected results need more attention. In particular we have to consider a quality study of the migration dynamics and reasons for this reason. Also we have to consider other, unobserved factors like economic integration into EU of the Eastern European countries.

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Montenegrin Journal of Economics

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Author Guidelines Submit to the journal Submissions should be sent via email to: Professor Veselin Draskovic E-mail: [email protected]

Review process Each paper is reviewed by the editor and, if it is judged suitable for this publication, it is then sent to two referees for double blind peer review. The authors’ names are anonymous to the review- ers. Based on their recommendations, the editor then decides whether the paper should be accepted as is, revised or rejected. The Editorial Board retains the right to methodologically adjust the article to the journal propositions and standards of the English language, as well as not to consider articles which do not meet the requirements of these guidelines.

Copyright Articles submitted to the journal should not have been published before in their current or sub- stantially similar form, or be under consideration for publication with another journal. Use this in conjunction with the points below about references, before submission i.e. always attribute clearly using either indented text or quote marks as well as making use of the preferred Harvard style of formatting. Authors submitting articles for publication warrant that the work is not an infringement of any existing copyright and will indemnify the publisher against any breach of such warranty. The author is responsible for ensuring the authenticity of data, facts, quotations and other information. The Editorial Boards may publish articles for discussion, without necessarily sharing the author’s views.

Manuscript requirements Please prepare your manuscript before submission, using the following guidelines:

Format All files should be submitted as a Word document, A4 format, Franklin Gothic Book, font size 11 pt.

Article Length Articles should be between 3000 and 10000 words in length. For long articles, compliance of editor-in-chief is required. Pictures, graphics and other attachments should be marked and sent as separate files, or in text, and must not exceed the journal format with margins.

Article Language It is strongly recommended to send articles in the English language. However, upon the compliance of the Editorial Board, it is possible to publish articles in some of the other world languages. Authors from Montenegro and surrounding countries should submit articles both in English and mother tongue due to the bilingual nature of the website.

Article Title Page - An Article Title Page should be submitted alongside each individual article. This should include:

 Article Title - A title of not more six eight words should be provided.  Author Details - Details should be supplied on the Article Title Page including: Full name of each author, Affiliation of each author, E-mail address of the corresponding author

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 Structured Abstract - Authors must supply a structured abstract: Purpose, Methodology, Ap- proach, and Findings. Maximum is 250 words in total.  Keywords - Immediately after the abstract, provide a maximum of 6 keywords.  Article Classification - The articles are classified in the following categories: original scientific paper, preliminary communication, review, professional paper, and book review.  Classification codes - Please provide up to 6 standard JEL codes. The available codes may be accessed at JEL: http://www.aeaweb.org/journal/jel_class_system.html  Article structure - The structure of article should comprise: the title, abstract, key words, introduction, subtitles, conclusion and bibliography. Articles can also be structured in the following way: introduction, starting hypotheses, solutions, discussion, conclusion and bibliography. Divide your article into clearly defined and numbered sections (1, 2, 3, ...). Subsections should be numbered 1.1 (then 1.1.1, 1.1.2 ...), 1.2, etc. (the abstract is not included in section numbering).  Footnotes - Footnotes should be used as least as possible, and only for the necessary explanations, with the continuous use of Arabic numbers.

References Literature is not to be numerated. It is to be arranged in alphabetic order of authors and chrono- logically for the articles of the same author. Literature is to be quoted according to the examples for books, magazines and other sources. References to other publications must be in Harvard style and carefully checked for complete- ness, accuracy and consistency. You should cite publications in the text: (Ilic, 2009) using the first named author's name or (Ilic and Tot, 2009) citing both names of two, or (Tot et al., 2009), when there are three or more authors. At the end of the paper a reference list in alphabetical order should be supplied:

 For books Surname, Initials (year), Title of Book, Publisher, Place of publication. e.g. Bagdikian, B. H. (1983), The Media Monopoly, Beacon Press, Boston.  For book chapters Surname, Initials (year), “Chapter title”, Editor's Surname, Initials, Title of Book, Publisher, Place of publication, pages. e.g. Picard, R. G. (2005), “Money, Media, and the Public Interest”, in Overholster, G., Jamieson, K. H. (Ed.), The Press, Oxford University Press, Oxford, 337-350.  For journals Surname, Initials (year), “Title of article”, Journal Name, volume, number, pages. e.g. Thacher, D., Rein, M. (2004), „Managing Value Conflict in Public Policy”, Governance Vol. 17, No. 4, 457-486.  For published conference proceedings Surname, Initials (year of publication), "Title of paper", in Surname, Initials (Ed.), Title of published proceeding which may include place and date(s) held, Publisher, Place of publication, Page numbers. e.g. Draskovic, V., Grego, Z., Draskovic, M. (2011), “Media Concentration, Neoliberal Paradoxes and Increase in Virtuality”, in Media Concentration proceedings of the international conference in Podgorica, Montenegro 2011, Elit, Podgorica, 33-45.  For working papers Surname, Initials (year), “Title of article”, working paper [number if available], Institution or organization, Place of organization, date. e.g. Draskovic, V. (2007), “Specificities and problems of Montenegrin transition”, working paper, Leeds University Business School, TIGER, Warsaw, September.  For newspaper articles (authored) Surname, Initials (year), “Article title”, Newspaper, date, pages. e.g. Miller, M. C. (1997), “The Crushing Power of Big Publishing”, The Nation, 17 March, p. 10.  For newspaper articles (non-authored) Newspaper (year), “Article title”, date, pages. e.g. Vijesti (2011), „The New Media“ 2 December, p. 5.  For electronic sources If available online, the full URL should be supplied at the end of the reference, as well as a date that the resource was accessed. e.g. Compaine, B. M. (2005), „The Media Monopoly Myth: How New Competition is Expanding our Sources of Information and Entertainment”, available at: http://www.NewMillennium Re- search.org//archive/ final_Compaine_Paper_050205. pdf (accessed 10 december 2011).

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