RECENT ADVANCES in MATHEMATICS and COMPUTERS in BUSINESS, ECONOMICS, BIOLOGY & CHEMISTRY A Panel Data Analysis of the Connection between Employee Remuneration, Productivity and Minimum Wage in Romania MARIA DENISA ANTONIE, AMALIA CRISTESCU, NICOLAE CATANICIU National Scientific Research Institute for Labor and Social Protection 6-8 Povernei Str., District 1, Bucharest ROMANIA [email protected], [email protected], [email protected] Abstract: - In this paper we present the results of a panel data analysis of the impact of productivity and minimum wage upon employee remuneration. We used a fixed effect regression model with Driscoll and Kraay standard errors to account for the possible problem of heteroskedastic and autocorrelated error structure. The main conclusion is that in the studied period the Romanian economy was characterized by a strong correlation between productivity and remuneration, which indicates the economic efficiency. Key-Words: - productivity, remuneration, econometric model, panel data, fixed effects, robust standard errors 1 Introduction (which is actually the most significant component of the In an economy, and especially in an emerging one like labor cost) on the labor productivity and the minimum Romania, the relationship between productivity and wage. growth potential is important, mainly if the productivity The analysis was conducted over a period of five years level is seen as the third factor of economic growth after (2003-2007), using data for the 29 activities of the labor force and capital. The potential GDP growth Romanian economy. As for the method, we choosed a creates the prerequisites for reducing the existing excess panel data model. demand in the economy and for ensuring real economic Panels are attractive since they contain more information convergence. Secondly, the productivity influences the than single cross-section and allow for an increase inflation and the exchange rate. A low correlation precision in estimation. between wages and productivity creates inflationary pressures by increasing the costs. In order to achieve the competitiveness on the European unique market, 2 Data Romania must focus on the economic growth [5]. Also, The variables used are: employee remuneration (lrem), most of the times, the competitiveness is assessed by the productivity (lprod) and minimum wage (lhminwage). correlation between wages (labor costs) and labor Initial data are annual, for the 29 activities of Romanian productivity. economy. We worked with log data, after we brought Since productivity and wages are both essential them to hourly values. Also, employee remuneration and economic factors, the way they interrelate is a constant minimum wage were deflated by using the CPI with the concern for the economists, as well as for employers and base in 2003. For the productivity, in order to ensure policy-makers. The literature is focused on the comparability, the values were divided to the production connection between these two factors. There are several index with the base in 2003. papers concerning labor productivity and wages in The remuneration per hour was calculated by dividing Romania that use different models and tools. A revised the employee remuneration to the number of hours form of the coefficient of structural changes was used in worked. The employee remuneration is part of the added order to determine the regional/sectoral dissimilarities value and includes the total remuneration, in cash (gross between productivity and wage [8]. Also, a short term wages) or in kind, that an employer pays an employee in forecast of the correlation between the labor productivity exchange for the work performed over a period of time, index and the average gross earnings index in the and the employer’s contribution to social insurance. The Romanian industry was conducted using lag econometric employer’s contribution to social insurance covers the models, ARIMA processes, as well as feed forward state social insurance contribution (including neural networks [1]. contributions to the retiring fund); the contribution to the In the analysis undertaken in this study, we tried to fund for of unemployment benefits payment; the capture the dependence of employee remuneration contribution to the social health insurance fund. ISSN: 1790-2769 134 ISBN: 978-960-474-194-6 RECENT ADVANCES in MATHEMATICS and COMPUTERS in BUSINESS, ECONOMICS, BIOLOGY & CHEMISTRY The productivity per hour was calculated as the ratio function that describes the correlation between labor between production and the working hours performed by costs and the productivity level, and the impact of the the occupied population in the 29 economic activities minimum wage. This made the authors to choose the (the occupied population includes employees and following regression equation: freelance workers). lremit = C+ a*lprodit + b*lhminwageit + uit The minimum wage per hour was calculated as the ratio where lrem is the log of the hourly employee between the national minimum wage and the average remuneration, lprod – the log of the productivity per number of working hours per month (170 hours). hour and lhminwage – the log of the national minimum The sources of our data are the publications of the wage per hour. Romanian National Institute of Statistics (National Accounts, Romanian Statistical Yearbook). 4 Methodology A panel data regression differs from a regular time-series 3 Economic description or cross-section regression in that it has a double The economic theory favors the need to link wages with subscript on its variables: labor productivity. From this perspective, the labor ’ yit = a + X it b + uit , i = 1, …, N; t = 1, …, T (1) demand is often described as a decreasing curve of the The i subscript denotes the cross-section dimension and t labor’s marginal productivity. However, in practice, denotes the time-series dimension. Most of the panel there are certain elements that complicate the disclosure data application utilize a one-way error component of the correlation between the wage level and the model for the disturbances, with: uit = αi + εit [2]. productivity level. First, employers are interested in There are several different linear models for panel data. labor costs and not just wages. Second, the employment The fundamental distinction is that between fixed-effects relationship is bilateral between an employer (interested and random-effects models. In the fixed-effects (FE) in labor costs) and employees (interested in wage and model, the αi are permitted to be correlated with the other associated benefits). From a microeconomics regressors xit, while continuing to assume that xit is perspective, such a relationship is characterized by uncorrelated with the idiosyncratic error εit. In the asymmetric information and by incomplete and incorrect random-effects (RE) model, it is assumed that αi is disclosure of both parties’ intentions. This means that purely random, a stronger assumption implying that αi is there are problems in estimating the level of individual uncorrelated with the regressors [4]. labor productivity. From the macroeconomic perspective, the labor supply 4.1 Test for poolability of the data and demand curves are built at the expense of omitting One of the main motivations behind pooling a time the heterogeneous nature of the aggregation elements. series of cross-sections is to widen the database in order Thus, labor demand reflects the marginal productivity to get better and more reliable estimates of the curve of the labor, aggregated at the level of the national parameters of the model. The question is to pool or not economy or of the economic sectors (activities). to pool the data. Technically speaking, the relationship between the labor The simplest poolability test has its null hypothesis the supply and demand should take into account the work OLS model: y = a + b’X + ε and as its alternative the force remuneration. The problem is that this it it it FE model: yit = a + b’Xit +αi + εit [9]. In other words, we remuneration includes a variable component with many test for the presence of individual effects. Formally, we degrees of freedom – the wage (economic activities, write H0: αi = 0, i = 1,…, N. We consider the F statistics administrative units and time) and a semi-variable according to the construction principle: component (or semi-constant), namely the social (ESS - ESS ) /(N -1) R U , where ESSR denotes the contributions paid by the employer (to make it more F1-way = ESS /((TNK--1) ) simple, we will ignore other minor elements of wage U costs) that are changed from time to time, as a result of residual sum of squares under the null hypothesis, ESSU government decisions, but do not vary in relation to the the residual sum of squares under the alternative. Under type of the economic activity. H0, the statistic F1-way is distributed as F with (N-1, (T - On the other hand, the wage structure is not the same for 1) N - K) degrees of freedom. The two sums of squares all workers, depending on the various fields of activity. evolve as intermediate results from OLS and from FE However, these wages have also mutual factors of estimation. influence, the most important of which being the In Stata, if we run the xtreg command with the fe option, minimum wage. we obtain at the bottom of the output the F-test that all Under these circumstances, it is necessary to identify a αi=0. If we reject the null hypothesis it also means that tradeoff between the motivational base of the behavior ISSN: 1790-2769 135 ISBN: 978-960-474-194-6 RECENT ADVANCES in MATHEMATICS and COMPUTERS in BUSINESS, ECONOMICS, BIOLOGY & CHEMISTRY the OLS estimates suffer from an omission variables (yit- y i ) = ( x it - x i )' b +()eit - e i (2) problem and they are biased and inconsistent. The within estimator is the OLS estimator of this model. Because αi has been eliminated, OLS leads to consistent 4.2 The Hausman test estimates of b even if αi is correlated with xit as is the The Hausman principle can be applied to all hypothesis case in the FE model.