Short-Run and Long-Run Relationship of Selected Labor and Macroeconomic Indicators of Employment Rate: the Case of National Capital Region

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SHORT-RUN AND LONG-RUN RELATIONSHIP OF SELECTED LABOR AND MACROECONOMIC INDICATORS OF EMPLOYMENT RATE: THE CASE OF NATIONAL CAPITAL REGION

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A Thesis Presented to the

College of Commerce and Business Administration

University of Santo Tomas

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In Partial Fulfillment

of the Requirements for the Degree

Bachelor of Science in Business Administration, Major in Business Economics

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Dolot, Maynard Jasper R. Laurente, Mikhael D. Pilitro, Ver Lyon Yojie V.

November 17, 2012 University of Santo Tomas – Economics Society ii | P a g e

University of Santo Tomas – Economics Society iii | P a g e

ACKNOWLEDGEMENTS

The authors of this paper would like to express their sincere gratitude to their beloved parents for their love and moral support in doing this paper; the University of Santo Tomas,

College of Commerce and Business Administration-Business Economics Department for giving us the opportunity to acquire skills and knowledge to better enhance the author‟s capabilities, to the UST-Economics Society and to the author‟s Business Economics colleagues for the support and encouragement while the authors are doing this paper. Also, the authors would like to thank our chairperson, Mr. Ronald B. Paguta, Mr. Al Faithrich Navarrete, MA, and Asst. Prof. Marie

Antoinette L. Rosete, MDE, who continue to nourish the author‟s thoughts and by giving their blessing to the authors to join in this research paper competition. And most importantly, the researchers want to thank the Almighty God for the love that He gave to us, for always guiding the authors, for the knowledge that He bestowed upon the authors, and for the unending grace that the authors receive everyday.

University of Santo Tomas – Economics Society iv | P a g e

SHORT-RUN AND LONG-RUN RELATIONSHIP OF SELECTED LABOR AND MACROECONOMIC INDICATORS OF EMPLOYMENT RATE: THE CASE OF NATIONAL CAPITAL REGION

ABSTRACT

This study provides evidence on the short-run and long-run relationship of selected labor and macroeconomic indicators to employment rate and to determine the possible shocks or innovations as well as its degree of influence that can significantly change the variables in the

National Capital Region (NCR) in the Philippines using time-series data from 1985-2010. Using

Johansen co-integration test it was concluded that there is a long-run association between labor force participation rate, regional output, and real wages are significant factors of employment rate. Vector error correction model (VECM), showed that the variables have significant relationship in the long-run. On the contrary, the results showed the insignificance of the relationship between the variables in the short-run. Using impulse-response function, employment shocks and regional output shocks generally showed a positive impulse on employment rate. However, it also revealed that shocks of labor force participation rate and real wage negatively influenced employment rate. Variance decomposition showed that in the short- run, employment rate shocks has the most influence on employment rate but in the long-run, it showed that shocks or innovations on employment rate, labor force participation rate, and real wage almost shared the same influence on employment rate.

JEL Classification: J01, J11, J21

Keywords: Employment Rate Labor force Participation Rate, Regional Output, Real Wage,

Johansen Co-integration Test, Vector Error Correction Model, Impulse-Response Function,

Variance Decomposition.

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TABLE OF CONTENTS

Page

Title Page i

Endorsement Letter ii

Acknowledgements iii

Abstract iv

Table of Contents v

List of Tables vii

List of Figures viii

Chapter 1: Introduction 1

Chapter 2: Review of Related Literature 3

2.1 Short-Run 3

2.1A. Labor Force Participation and Employment 3

2.1B. Output and Employment 4

2.1C. Real Wage and Employment 6

2.2 Long-Run 8

2.2A. Labor Force Participation and Employment 8

2.2B. Output and Employment 9

2.2C. Real Wage and Employment 11

Chapter 3: Research Framework 12

3.1 Research Simulacrum 12

3.2 Research Method 13

University of Santo Tomas – Economics Society vi | P a g e

Chapter 4: Presentation, Analysis, and Interpretation 15

4.1 Data Presentation 15

4.1A. Employment Rate 15

4.1B. Labor Force Participation Rate 16

4.1C. Real Gross Regional Domestic Product Ratio 17

4.1D. Real Wage 18

4.2 Results and Discussions 19

4.2A. Long-Run and Short-Run Relationship 19

4.2B. Impulse-Response Analysis 29

4.2C. Variance Decomposition 35

Chapter 5: Conclusion, Policy Recommendations and Recommendations 38

5.1 Conclusion 38

5.2 Policy Implications 39

5.3 Recommendation for Further Studies 45

References 46

Appendix 51

Appendix A: Proposed Model and Hypothesis 51

Appendix B: Historical Trends of the Variables 51

Appendix C: Johansen Co-integration Tests 53

Appendix D: VECM Regression Results 54

Appendix E: Impulse-Response Graph 55

Appendix F: Variance Decomposition Table 57

Appendix G: Unit Root Tests of the Variables 58 University of Santo Tomas – Economics Society vii | P a g e

LIST OF TABLES

Table Page

1 Unrestricted Co-integration Rank Test (Trace Statistics) 53

2 Unrestricted Cointegration Rank Test (Maximum Eigenvalue Statistics) 53

3 Johansen Co-integration Long-run Coefficients 54

4 Vector Error Correction Model (VECM) Regression Results 54

5 Variance Decomposition Table (Employment Rate) 57

6 Unit Root Test on Employment Rate (EMPR) 58

7 Unit Root Test on Labor Force Participation Rate (LFPR) 59

8 Unit Root Test on Real Gross Regional Domestic Product Ratio (RGRDPR) 59

9 Unit Root Test on Real Wage (RWAGE) 59

10 Serial Correlation Test (Breusch-Godfrey Serial Correlation LM Test) 60

11 Heteroskedasticity Test (Breusch-Pagan-Godfrey Test) 60 University of Santo Tomas – Economics Society viii | P a g e

LIST OF FIGURES

Figure Page

1 Proposed Model and Hypothesis 51

2 Employment Rate 51

3 Labor Force Participation Rate 52

4 Real Gross Regional Domestic Product Ratio 52

5 Real Wage 53

6 Impulse-Response Function Graph (Employment Shocks to 55

Employment Rate)

7 Impulse-Response Graph (Labor Force Participation Shocks to 56

Employment Rate)

8 Impulse-Response Graph (Regional Output Shocks to Employment 56

Rate)

9 Impulse-Response Graph (Real Wage Shocks to Employment Rate) 57

10 Normality Test (Jarque-Bera Test) 60

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1. Introduction

The National Capital Region (NCR) is the home of civilization in the Philippines. Being such, the bulk of business and corporate investments are situated in the region. It is also where a large chunk of the country‟s employment is situated. According to Bu`reau of Labor and

Employment Statistics (BLES), the region has a 4,941,000 labor force, the second highest labor force in the country and also, having a 4,371,000 employed or 12.13% of the total employment of the Philippines. It then becomes crucial to create sustainable employment opportunities in the region since it will allow a smoother flow of money throughout the country, and therefore generate greater economic activity.

Despite the region‟s relative advantage in terms of productivity as compared to the other parts of the country, it still continues to be surrounded by various issues, which demand great attention in the realm of employment and human capital. The increasing flow of rural-urban migration calls for greater sustainable employment opportunities, given the limited opportunities available in other regions. The existing underemployment in various sectors, as evidenced by the pronounced job-education mismatch, expose the need for enhanced institutional ties to make employment more efficient for everyone. Aside from the significant drop in the number of graduates in the region, the oversubscription of students in certain courses such as business administration has led to the aggravation of the underemployment problem in the region. The mismatch has also been made rampant due to constantly advancing technology. This causes the deficiency in skills possessed by graduates because firms tend to be more abreast with technological advances and therefore demand workers who can cope with such technology. University of Santo Tomas – Economics Society 2 | P a g e

However, graduates are only taught the fundamentals, causing them to not meet the expectation of potential employers.

The researcher‟s paper discusses the short-run and long-run impact of selected labor and macroeconomic indicators particularly the labor force participation rate, regional output, and real wage to employment rate in the National Capital Region (NCR) within the period of 1985-2010.

It attempts to find evidence whether there is a significant short-run and long-run relationship between the labor force participation rate, regional output, and the employment rate in the

National Capital Region (NCR). It is better to look at the significance of relationship because it is easier to identify how the employment can be sustained in the National Capital Region (NCR) regardless of the positive or negative effects of the selected indicators. The researchers would also want to determine the possible economic shocks or innovations, that could affect the employment rate and its relationship with the aforesaid selected labor and macroeconomic indicators and as well the degree of their short-run and long-run influence that could make a significant change or effect on the endogenous variables used in this study.

This study is significant because there are few studies that are conducted for addressing sustainable employment in the Philippines particularly in the National Capital Region (NCR).

Most of these studies can be found on European countries or to the members of the Organization for Economic Co-operation and Development (OECD). The researchers find it important to have a study here in the Philippines, particularly in the National Capital Region (NCR) in order to know the significant impact of the some labor and macroeconomic indicators to employment rate in the region in the short-run and the long-run. This paper therefore provides new evidence and more comprehensive study regarding on the short-run and long-run relationship of selected labor and macroeconomic indicators and employment rate in the case of the National Capital Region University of Santo Tomas – Economics Society 3 | P a g e

(NCR). The paper does not intend to study all the labor and macroeconomic indicators that affect employment rate; it only focuses on labor force participation rate, real gross regional domestic product ratio and real wage.

2. Review of Related Literature

2.1. Short-Run

2.1A. Labor Force Participation and Employment

Labor force participation is mostly affected by business cycles and demographic changes in the population like gender, culture and age. This includes the welfare effect of joining the labor force in a short-run setting. These changes are further explained by the following studies made by (Binyamini and Larom, 2012; Nour, 2011; Montalvo, 2006).

According to Binyamini and Larom (2012), Middle Eastern Asia specifically Israel is experiencing job mismatch and market friction which leads to a decrease in employment due to some factors such as participation decision, female employment and unemployment benefits.

This is an evidence of a positive correlation between participation and employment. In Sudan, employment and labor force participation rate have been affected by endogenous and exogenous factors like increase in female workers and age gap (Nour, 2011). Lastly, African labor force participation helped increase the employment growth but it is still a victim of low productivity because of unproductive employment growth this is because of mismatch in job qualifications. In some South Asian countries employment and productivity has a positive relationship (Choudhry,

2008).

The study of Montalvo (2006) addressed the effects of Asian financial crisis of 1997-

1998) to participation rate and employment in the Philippines. The study showed that labor market shocks affect the Philippines through a decrease in participation rate followed by a University of Santo Tomas – Economics Society 4 | P a g e decrease in employment rate, but in the future participation returns to its pre-shock state and employment still continues to decrease. Regions in the Philippines with high minimum wage, have slower recovery from shocks.

However, there are also studies that contradict the significant relationship between wage and employment in the short-run. (Bartik, 2002; Elmeskov and Pichelmann, 1993) generally found that in the short-run, the relationship of labor force participation rate and employment is insignificant. The study of Bartik (2002) aimed to correct the endogeneity of welfare caseloads by using instruments that reflect welfare policy. The variables used are real wages, unemployment, employment-to-population ratio, and labor force participation rate. It was found that using a series of F-tests in the eight-lag specification, the relationship between labor force participation and employment are insignificant at one percent level. Therefore, it can be inferred that there is an insignificant relationship between these variables in the short-run. Moreover,

Elmeskov and Pichelmann (1993) found that in France, there is virtually no short-run labor force response to cyclical swings in employment. Hence, there is no short-run relationship between labor force participation and employment.

P2.1A: Relationship between labor force participation and employment is significant in the short-run.

2.1B. Output and Employment

Given the pivotal importance of GDP growth or output as contributing force behind job creation and the prevalence of unemployment or underemployment in economies in general, events such as the collapse in GDP growth in the global crisis are bound to have a major impact on the employment and labour market situation too (UNCTAD Trade and Development Report,

2010). A number of studies emphasized the role of output as an important determinant of University of Santo Tomas – Economics Society 5 | P a g e employment in the short-run. (Caporale and Skare, 2011; Yusop et.al, 2005; Phelps, 1994; Ball and Moffitt. 2001).

Caporale and Skare (2011) analyzed the short- and long-run relationship between employment growth, inflation and output growth in Phillips‟ tradition. For this purpose, the researchers employed VECM methods to a nonstationary heterogeneous dynamic panel including annual data for 119 countries over the period 1970-2010, and also carry out multivariate Granger causality tests. It was found out that the estimates of equation imply bidirectional Granger causality employment growth and output growth as well as in the short- run. On the other hand, Yusop et.al (2005) used Johansen's procedure was conducted to see the long run and short run relationships between output, productivity, wage and labor in Malaysia‟s manufacturing sector. The Johansen co-integration test revealed that in the short-run dynamic analysis, it was found that output and employment are correlated. Moreover, Phelps (1994) and

Ball and Moffitt (2001) argued that output growth has only temporary, short-run effects on employment.

However, there are also studies that contradict the significant relationship between output and employment in the short-run. (Akcoraoglu, 2010; Hanusch, 2012) generally found that in the short-run, the relationship of output and employment is insignificant. Akcoraoglu (2010) found an insignificant relationship between output and economic growth. The author‟s study aimed to explore the empirical relationship between employment and economic growth in Turkey over the period 1995Q1-2007Q4 by using estimation results of the short-run dynamic model based on error-correction mechanism. It was concluded that real GDP seems to have positive but statistically insignificant effects on employment in the second and third quarters. Moreover,

Hanusch (2012) found that there is an insignificant relationship of employment to economic University of Santo Tomas – Economics Society 6 | P a g e growth in the Philippines by plotting the estimated OLC against hiring and firing scores. There are also studies that concluded a negative long-run relationship between output and employment rate. The United Nations Research Institute for Social Development (UNRISD) stated that the ideal scenario is for demand for labour and productivity of labour to increase simultaneously, but this appears to be becoming less likely. There appears to be something of a quantity/quality trade-off emerging in the global demand for labour, as over time the impact of productivity growth seems to be to slow down the rate of employment growth. While in the 1960s, a 1% increase in output per worker was associated with a reduction in employment growth of 0.07%, by the first decade of this century the same productivity increase implies reduced employment growth by 0.54% (UNRISD, 2010).

P2.1B: Relationship between output and employment is significant in the short-run.

2.1C. Real Wage and Employment

One of the crucial roles of minimum wages is they can influence the income distribution between both capital and labour as well as between different groups of workers (Herr and

Kazandziska, 2011). Several studies found that there is a significant relationship between wage and employment particularly in the short-run (Mitsis, 2012; Corcoran, 1982; Minsky, 1975).

Mitsis (2012) used using VAR models, which may capture the short-run relationship between the total employment and the minimum wage. As indicated in the VAR model estimates, there is evidence of a short-run relationship between employment and the minimum wages, since in all four models the lagged values of the one endogenous variable appear to have significant effects on the other. Corcoran (1982) on the other hand, concentrated on short-run employment effects described teenage women‟s work activity in the years following high school completion and investigated whether early non-employment reduces women‟s chances of later University of Santo Tomas – Economics Society 7 | P a g e employment once they are able to adjust for individual differences that are stable over time and affect employment. The author found that non-employment is pervasive and prolonged among teenage women with less than fourteen years of schooling. It is associated with a lower probability of employment in the short run and with lower wages throughout women‟s work careers. From here, it can be inferred that in the short run, there is a relationship between wages and employment or the two variables are associated with each other. Moreover, in the book entitled, “John Maynard Keynes”, it was stated that, Keynes as well as the Keynesians accepted the presence of an inverse relationship between real wages and employment, which was primarily due to the presence of diminishing returns to labor over the short-run (Minsky, 1975).

Therefore, real wages and employment have a short-run relationship.

However, there are also studies that contradict the significant relationship between wage and employment in the short-run. (Apergis and Theodosiu, 2008; Yusop et. al., 2005) generally found that in the short-run, the relationship of wage and employment is insignificant. Apergis and Theodosiu (2008) concluded the insignificant relationship by using a panel from ten different OECD countries, from 1950 to 2005, and applying panel co-integration and causality methodology that it firmly rejected the hypothesis that the authors formulated that wages cause employment in the short-run. On the other hand, Yusop et.al. (2005) used Johansen's procedure in order to see short run relationships between the variables. The Johansen co-integration test results revealed that a long-run equilibrium relationship exists among the variables. However, when it comes to short run dynamic analysis, it was found that except for real wages, labour productivity and employment are statistically have significant relationship.

P2.1C: Relationship between real wage and employment is significant in the short-run.

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2.2. Long-run

2.2A. Labor Force Participation and Employment

In the long-run as labor force participation increase the surplus of labor goes to the unemployed and this is affected mostly by the evolution of the population structure, a fast job separation or a slow job search. The following journals created by (Balleer Et. Al., 2009;

Weerakoon and Arunatilake, 2011; Carrasco Et. Al., 2004; Montalvo, 2006 and Hüfner and

Klein, 2012) showed a long-run relationship of labor force participation rate to employment and unemployment in different countries.

As a continent with a fast aging population, Europe has been recorded of having a decreasing quantity in labor force participation (Balleer Et. Al., 2009). Considering an evolving population structure (such as changing demographic factors, work attitude and age) and constant shock effects (such as job availability) in a long-run time period. European countries are having a hard time coping up with its participation due to age, but job openings and the acceptance of female workers in the society have provided a drive for a substantial increase in Euro area labor supply. Leading to a conclusion that employment and labor force participation is positively related in Europe with the consideration of having jobs available in the Euro area. The labor market of Spain is affected by immigration with a higher number of supply rendering wages (the price of labor) to become lower if this does not follow it would lead to lower employment

(Carrasco Et. Al., 2004). On the other hand, a work conducted in Germany by Hüfner and Klein

(2012) to prepare for shocks, they suggested that it is better if incentives for work, job matching and working hour flexibility were increased to lessen the effect of shocks like 2008-2009 recession to the labor market. In Sri Lanka, employment growth is more affected by the government and the informal sectors rather than formal and private sectors as stated by University of Santo Tomas – Economics Society 9 | P a g e

Weerakoon and Arunatilake, (2011), most of the labor force tend to be contractual or part of the informal sectors and according to the study it is not conducive to the growth of Sri Lanka because most workers are not given social safety nets. Most of females, younger age groups and educated are unemployed. In the Philippines, there are significant differences in each region.

Specifically in the National Capital Region, the impact on migration is lower than other regions in the first period. The effects on the level of employment in the long run is associated with wide variation, variation ranging from 1.73 in Region 2 to figures not that different from zero in other regions (Montalvo, 2006).

P2.2A: Relationship between labor force participation and employment is significant in the long-run.

2.2B. Output and Employment

Gross regional product or regional total output is conceptually equivalent to gross domestic product or national output; the latter measures newly created value through production by resident production units in the domestic economy, while for the former measures newly created value through production by regional production units in the regional economy. (Viet,

2010). A number of studies emphasized the role of output as an important determinant of employment in the long-run. (Massimiliano et.al., 2000; Krolzig and Toro, 1998; Caporale and

Skare, 2011; Yusop et.al., 2005; Caporale and Skale, 2011).

Massimiliano et.al. (2000) aimed to propose a statistical model that offers a congruent representation of post-war UK labour market using a co-integrated vector autoregressive

Markov-switching model where some parameters change according to the phase of the business cycle with three regimes representing recession, growth and high growth provides a good characterization of the sample data over the period 1966(3)-1993(1). They concluded that output University of Santo Tomas – Economics Society 10 | P a g e and employment is associated to a long run increase of the same magnitude that the shape and timing of the responses to a one standard deviation impulse to output innovation with a slightly

stronger positive impact on employment , but with a certain delay. Krolzig and Toro (1998) also aimed to propose a statistical model that offers a congruent representation of post-war US employment and output data by using a co-integrated vector autoregressive Markov-switching model where some parameters are changing according to phase of the business and employment cycle. Employment and output are found to have a common cyclical component and the long- run dynamics are characterized by a co-integrating vector including employment and output.

Moreover, Caporale and Skare (2011) analyzed the short- and long-run relationship between employment growth, inflation and output growth in Phillips‟ tradition by applying FMOLS,

DOLS, PMGE, MGE, DFE, and VECM methods to a non-stationary heterogeneous dynamic panel including annual data for 119 countries over the period 1970-2010, and also carry out multivariate Granger causality tests. The results showed that it strongly reject the null of no co- integration in favor of the existence of a long-run relationship between employment growth and output growth in the panel. The aim of Yusop et.al. (2005), is to investigate the linkages between output, productivity, wage and labour in Malaysia‟s manufacturing sector. Johansen's procedure was conducted to see the long run and short run relationships between the variables. The

Johansen co-integration test results revealed that a long-run equilibrium relationship exists among the variables. Furthermore, Caporale and Skale (2011) examined the short- and long-run linkages between employment growth, inflation and output growth applying panel co-integration and causality tests to data for 119 countries over the period 1970-2010. It was found out that all panel co-integration tests strongly reject the null of no co-integration in favour of a long-run relationship between employment growth, inflation and output growth. University of Santo Tomas – Economics Society 11 | P a g e

P2.2B: Relationship between output and employment is significant in the long-run.

2.2C. Real Wage and Employment

At the policy level, the issue of the minimum wage remains deeply controversial as it introduces moral considerations as to what constitutes minimal and fair compensation in a given economy and the role of wage in ensuring that people earn enough through their labor to afford to sustain themselves and their families (International Journal of Labour Research, 2012).

(Apergis and Theodosiu, 2008; Yusop et. al. 2005; Rath and Madheswaran, 2008; Mitsis, 2012;

Dickens et.al., 1999) emphasized the role of wages as an important determinant of employment in the long-run.

Apergis and Theodosiu (2008) investigated the existence and direction of a relationship between real wages and employment using a panel from ten different OECD countries, from

1950 to 2005, and applying panel co-integration and causality methodology. The results found statistical evidence for a long-run relationship between these two variables. Yusop et. al. (2005) aimed at investigating the linkages between output, productivity, wage and labour in Malaysiam manufacturing sector. Johansen's procedure was conducted to see the long-run and short-run relationships between the variables. The Johansen co-integration test results revealed that a long- run equilibrium relationship exists among the variables. Rath and Madheswaran (2008) investigated the relationship between labour productivity, real wages, employment and prices in

Indian manufacturing sector. The empirical results derived from conventional co-integration and error correction models provide evidence for long-run relationship among these variables during

1960-61 to 2001-02. Moreover, Mitsis (2012) examined the relationship of the total employment with the minimum wage in the special case where only a number of occupations are covered by the relative legislation. A theoretical background is provided by a recently developed search and University of Santo Tomas – Economics Society 12 | P a g e matching model and empirical evidence is provided by analysing time series data from Cyprus using unit root tests under exogenous and endogenous structural breaks. The empirical results suggested the existence of a negative long-run relationship between the minimum wage and total employment. Specifically, a 10% increase in the minimum wage in Cyprus is associated with a decrease in total employment of 0.2%. Moreover, Dickens et.al. (1999) presented a general theoretical model whereby employers have some degree of monopsony power, which allows minimum wages to have the conventional negative impact on employment but which also allows for a neutral or positive impact. Studying the industry-based British Wages Councils between

1975 and 1992, it was found out that minimum wages significantly compress the distribution of earnings but do not have a negative impact on employment in the long-run.

P2.2C: Relationship between real wage and employment is significant in the long-run.

3. Research Framework

The right hand side shows the employment rate measured by percentage of employed persons in the total labor force of National Capital Region (NCR). The left hand side shows that labor force participation rate, real gross regional domestic product and real may give impact to employment rate. Figure 1 summarizes the relationship.

Figure 1: Proposed Model and Hypothesis

3.1 Research Simulacrum

Labor Force P2.1A Participation P2.2A

Regional P2.1B Employment Output P2.2B Rate

Real P2.1C Wage P2.2C

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This framework is based on the neo-classical theory of employment, Phillip‟s golden triangle internal equilibrium theory and an endogenous labor market participation which provides a clear and more dynamic theoretical link between labor indicators and employment rate. Neo-classical economists believe that although prices and wages are totally flexible in the long run, they are rigid in the short sun. Therefore, although the economy will be at the full- employment equilibrium in the long run, it can stay at an above-full-employment equilibrium or a below full-employment equilibrium in the short run. (Quek, 2011). Phillip‟s golden triangle theory analyzed the quantitative relationship between employment growth, inflation and output growth. (Phillips, 1962). Endogenous labor market participation is embedded in the framework successful in explaining the dynamics in the labor market particularly the variability of employment (Haefke and Reiter, 2006).

3.2 Research Method

This study used quantitative analysis in determining the relationship between selected labor indicators and employment of the National Capital Region (NCR) in the Philippines. Due to the complete dataset of employment rate, labor force participation rate, regional output, and real wages for the National Capital Region, it was possible to construct a study with these variables. This design was chosen based on the studies of (Yusop et. al, 2005; Haefke and Reiter,

2006) where the studies relate to the selected labor indicators to employment rate.

To determine factors that will affect employment rate in the National Capital Region, this study used labor indicators. The researchers conducted a quantitative analysis using time-series data from 1985-2010. The variables will be subjected to multiple regression analyses using the

Johansen Cointegration Test and Vector Error Correction Model (VECM). Annual data for employment (measured in percent), labor force participation (measured in percent), regional University of Santo Tomas – Economics Society 14 | P a g e output (measured in National Capital Region‟s real gross regional domestic product in terms of contribution to total real gross domestic product of the Philippines) and real wage rate (measured in Philippine pesos) were all gathered from the Philippine Statistical Yearbook which was published annually by National Statistical Coordinating Board (NSCB). To examine the short run and long run impact of these variables on economic growth, a vector error correction model

(VECM) drawn from the work of (Yusop et. al, 2005) has been developed and took the following form:

Equation 1:

∆퐸푀푃푅푡 = 훼푖 ∆퐸푀푃푅푡−푖 + 훽푖∆퐿퐹푃푅푡−푖 + 훿푖∆푅퐺푅퐷푃푅푡−푖 + 휃푖 ∆푅푊퐴퐺퐸푡−푖 + 휎푖퐸퐶푡−1 + 휀1푡

The dependent variable used in measuring economic growth was the employment rate (EMPR) in the National Capital Region per year. LFPR will be the labor force participation rate that of the aforementioned and was measured by the percentage of working-age persons in an economy.

In this study, it will be particular to the National Capital Region‟s economy. RGRDPR will be the real gross regional domestic product and it is usually the macroeconomic measure of the value of regional economic output adjusted for price changes. However in this study, the researchers preferred to get its real gross domestic product adjusted at 2000 prices and convert it into ratio to the total gross domestic product of the Philippines in order to have a better measure of regional output. The reason is because to make the model more fitted and to make the model stationary in order to run the vector error correction model. On the other hand, RWAGE is the real income of an individual that has been adjusted to price changes. The real wage was adjusted to 2000 prices, the same thing that has been done to regional output (RGRDP). However, unlike the real gross regional domestic product, it is not converted into percentage terms because it is better to express the variable into Philippine pesos. 휎푖퐸퐶푡−1 represents the coefficient of the University of Santo Tomas – Economics Society 15 | P a g e lagged value of the residuals derived from the cointegrating equation of labor force participation rate (LFPR), regional output (RGRDPR), and real wage (RWAGE) on employment rate

(EMPR). 훼푖, 훽푖, 훿푖, 휃푖 represents the short run coefficients, and lastly, 휀1푡 represents the residual in the regression model

4. Presentation, Analysis, and Interpretation of Data

4.1 Data Presentation

Figure 2: Employment Rate (National Capital Region, in %)

EMPR

90.0

87.5

85.0

82.5

80.0

77.5

75.0

72.5

70.0 86 88 90 92 94 96 98 00 02 04 06 08 10

The general trend and behavior of the variables are examined through the collated data.

Figure 2 showed that the National Capital Region experienced a fluctuating trend in terms of employment rate from years 1985-2010. The lowest recorded employment rate was 71.4% during 1986. This can be attributed to the economic crisis that happened after the EDSA People

Power Revolution and towards the end of Marcos regime, underemployment is still a problem.

However, the highest recorded employment rate was during 2010 where the National Capital

Region reached its employment rate of 88.5%.

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Figure 3: Labor Force Participation Rate: National Capital Region (in%)

LFPR

58 86 88 90 92 94 96 98 00 02 04 06 08 10

Data of labor force participation rate which measures the percentage of working-age persons in an economy would be seen in Figure 3. Labor force participation rate in the National

Capital Region generally showed fluctuating trend. The National Capital Region experienced an rapid increase from years 1985-1998. It was in the year 2004 where the highest labor force participation rate was experienced (65.6%). However, the lowest recorded labor force participation rate was in 1986. EDSA People Power Revolution in 1986 can be a factor why the labor force participation rate had its lowest in this time series data. But the post-revolution gives an increasing trend in the labor force participation, this can be attributed to the increasing participation of women in the labor force in the National Capital Region (NCR).

University of Santo Tomas – Economics Society 17 | P a g e

Figure 4: Real Gross Domestic Product: National Capital Region (percentage contribution to total Gross Domestic Product, in %)

RGRDPR

22 86 88 90 92 94 96 98 00 02 04 06 08 10

The extent to which the size and contribution of one‟s regional economy to the economic growth of the national economy can be measured is presented in Table 3. Generally, National

Capital Region experienced a fluctuating trend. Having a high contribution of real gross regional domestic product to the total gross domestic product could infer that the regional economy is vital for the economy growth and progress of the whole country. The highest recorded contribution of National Capital Region‟s real gross regional domestic product (RGRDP) to total real gross domestic product was achieved during 2007 at 37.14%. In contrast, the lowest contribution of National Capital Region to the Philippines‟ real gross domestic product was

23.54% during 1985. On the other hand, the National Capital Region‟s contribution to the total real gross domestic product suffered a severe drop from 33.85% in 2009 to 29.86% in 2010. The reason behind this could be the US financial crisis during 2009-2010, where most of the business process outsourcing (BPO) companies was dominated by US firms.

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Figure 5: Real Wage: National Capital Region (in pesos)

RWAGE

280

270

260

250

240

230

220

210

200

190 86 88 90 92 94 96 98 00 02 04 06 08 10

After taking consideration the effects of inflation on purchasing power, Table 4 showed the level of real income of an individual or legislated in a certain region or country. National

Capital Region perceived to have an inconsistent trend. In 2002, the National Capital Region experienced the highest real wage. The second highest real wage was achieved in 2003. The lowest recorded real wage was during 1987. There was a time when the National Capital Region experienced a decreasing trend of real wages. The first era of decreasing real wages was experienced from 1985-1987. This was followed by during 1993-1995, 2002-2005 and 2007-

2009. However, a sudden increase of wages was recorded several times from the timetable of

1985-2010. The first wave of huge increase of real wages was achieved in the year 1989, followed by years 1991, 1993, 1997, 2000, and 2002. This fluctuating trend of real wages is affected by the changes in purchasing power, inflation, and consumption pattern of the people from the NCR that occurred during the time series that is used in this study.

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4.2 Results and Discussions

4.2A. Long-Run and Short-Run Relationship

Table 1: Johansen Cointegration Test (Trace Test)

Unrestricted Cointegration Rank Test (Trace)

Hypothesized Trace 0.05 No. of CE(s) Eigenvalue Statistic Critical Value Prob.**

None * 0.867160 89.66072 47.85613 0.0000 At most 1 * 0.663081 43.23264 29.79707 0.0008 At most 2 * 0.422077 18.21062 15.49471 0.0190 At most 3 * 0.216083 5.599392 3.841466 0.0180

Trace test indicates 4 cointegrating eqn(s) at the 0.05 level * denotes rejection of the hypothesis at the 0.05 level **MacKinnon-Haug-Michelis (1999) p-values

Before the authors conduct the Johansen Co-integration Test, the unit root test was conducted first because the test requires that all the quantitative data are stationary or an absence of unit root. Also, unit root test was employed because the vector error correction model requires that the data should be at the first difference and also the quantitative data should be stationary or doesn‟t have a unit root (see Appendix). Using the Trace Test, the first hypothesis is that there is no co-integration among the variables. Having 5% as the level of significance, the null hypothesis that there is no co-integration among the variables should be rejected since the probability is less than 5% (Prob 0.0000). The second hypothesis under the Trace Test states that there is at least one co-integrated variables. Since the probability is less than 5% (Prob. 0.0008), the null hypothesis of at least one co-integrated variable should be rejected. The third hypothesis under the Trace Test states that there is at least two co-integrated variables and since the probability is less than 5% (Prob. 0.0190), the null hypothesis that there are at least two co- integrated variables should be rejected. The fourth hypothesis under the Trace Test states that University of Santo Tomas – Economics Society 20 | P a g e there are at least three co-integrated variables and since the probability is still less than 5%, the null hypothesis that there are at least three co-integrated variables should also be rejected.

Therefore, the statistics from trace test, indicates that there are more than three co-integrating variables in the model. Another implication of the results of trace test is that there is a long-run relationship between the variables in this study, which are employment rate and labor force participation rate, real gross regional domestic product, and real wage.

Table 2: Johansen Cointegration Test (Maximum-Eigen Value Test)

Unrestricted Cointegration Rank Test (Maximum Eigenvalue)

Hypothesized Max-Eigen 0.05 No. of CE(s) Eigenvalue Statistic Critical Value Prob.**

None * 0.867160 46.42808 27.58434 0.0001 At most 1 * 0.663081 25.02202 21.13162 0.0134 At most 2 0.422077 12.61122 14.26460 0.0897 At most 3 * 0.216083 5.599392 3.841466 0.0180

Max-eigenvalue test indicates 2 cointegrating eqn(s) at the 0.05 level * denotes rejection of the hypothesis at the 0.05 level **MacKinnon-Haug-Michelis (1999) p-values

Another test to determine if there is long-run relationship between the variables is the

Maximum EigenValue Test. Using this test, the first hypothesis is that there is no co-integration among the variables and no error correction in the model. Having 5% as the level of significance, the null hypothesis of no co-integration among the variables and no error correction term should be rejected since the probability is less than 5%, (Prob 0.0001). The second hypothesis under the

Maximum EigenValue Test states that there is at least one co-integrated variable and at least one error correction term in the model. Since the probability is less than 5%, (Prob. 0.0134) the null hypothesis of at least one co-integrated variable and at least one error correction term should be rejected. The third hypothesis under the Maximum Eigen Value Test states that there is at least University of Santo Tomas – Economics Society 21 | P a g e two co-integrated variables and at least two error correction term in the model since the probability is greater than 5%, (Prob. 0.0897) the null hypothesis that there are at least two co- integrated variables and at least two error correction terms in the model must be accepted. The fourth hypothesis under the Maximum Eigen Value Test states that there are at least three co- integrated variables and at least three error correction terms in the model and since the probability is less than 5%, (Prob. 0.0180) the null hypothesis that there is at least three co- integrated variables and at least three error correction terms should be rejected. Based from the results of Maximum EigenValue test, there are at least two co-integrating variables and at least two error correction terms in the model as indicated by the Maximum Eigen Value Test. It implies that there is a long-run relationship and a possible long-run causality between employment rate and labor force participation rate, real gross regional domestic product, and real wage.

Using the two tests (Trace Test and Maximum Eigen Value Test), it was found out that there is long run association among the four variables. In addition, using the Johansen Long Run Co- integrating Technique, the authors were able to determine the corresponding coefficients of the variables and whether the independent variables have positive or negative relationship with the dependent variable.

Table 3: Coefficient result of Johansen Long Run Co-integrating Technique

1 Cointegrating Equation(s): Log likelihood -167.9571

Normalized cointegrating coefficients (standard error in parentheses) EMPR LFPR RGRDPR RWAGE 1.000000 0.660078 -2.454748 0.259191 (0.31763) (0.26413) (0.04949)

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The result showed that labor force participation rate (LFPR) indicated a positive relationship with employment rate (EMPR) in the long run with the least coefficient of

0.660078%. This means that one percent increase in the labor force participation rate will increase employment rate of National Capital Region by 0.660078% in the long run, all other things constant. This could also mean that one percent decrease in the labor force participation rate will decrease the employment rate of National Capital Region by 0.660078 % in the long run, all other things constant.

The result also showed that real gross regional domestic product rate (RGRDPR) portrayed a negative relationship with employment rate (LFPR) in the long run with a coefficient of -2.454748. This means that one percent increase of NCR‟s real gross regional domestic product rate will decrease NCR‟s employment rate by -2.454748% in the long run, ceteris paribus. This could also mean that one percent decrease in National Capital Region‟s real gross domestic product rate will increase the employment rate of the National Capital Region by -

2.454748% in the long run, ceteris paribus.

Lastly, the regression result showed that real wage (RWAGE) has a positive relationship with employment rate (EMPR) in the long run with a coefficient of 0.259191%. The results can be interpreted that a one peso increase in real wage in the NCR will increase employment rate in of NCR by 0.259191% and that a percent decrease in real wage in NCR will decrease employment rate of NCR by 0.259191% in the long run, assuming all other things constant.

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Table 4: Regression of the Vector Error Correction Model

Dependent Variable: D(EMPR) Method: Least Squares Date: 11/15/12 Time: 09:33 Sample (adjusted): 1988 2010 Included observations: 23 after adjustments D(EMPR) = C(1)*( EMPR(-1) + 0.660077523625*LFPR(-1) - 2.45474829206 *RGRDPR(-1) + 0.259190987763*RWAGE(-1) - 110.058960317 ) + C(2)*D(EMPR(-1)) + C(3)*D(EMPR(-2)) + C(4)*D(LFPR(-1)) + C(5) *D(LFPR(-2)) + C(6)*D(RGRDPR(-1)) + C(7)*D(RGRDPR(-2)) + C(8) *D(RWAGE(-1)) + C(9)*D(RWAGE(-2)) + C(10)

Coefficient Std. Error t -Statistic Prob.

C(1) -0.355135 0.111550 -3.183643 0.0072 C(2) -0.303426 0.191433 -1.585026 0.1370 C(3) -0.087687 0.165447 -0.530004 0.6050 C(4) 0.429164 0.258158 1.662406 0.1203 C(5) -0.057172 0.198637 -0.287824 0.7780 C(6) 0.337896 0.626723 0.539147 0.5989 C(7) -0.596177 0.416459 -1.431538 0.1759 C(8) -0.011665 0.034337 -0.339729 0.7395 C(9) -0.040348 0.027905 -1.445935 0.1719 C(10) 0.776092 0.342870 2.263514 0.0414

R-squared 0.654004 Mean dependent var 0.295652 Adjusted R-squared 0.414468 S.D. dependent var 1.688592 S.E. of regression 1.292112 Akaike info criterion 3.649453 Sum squared resid 21.70419 Schwarz criterion 4.143146 Log likelihood -31.96871 Hannan-Quinn criter. 3.773616 F-statistic 2.730297 Durbin-Watson stat 2.315343 Prob(F-statistic) 0.049045

In Table 4, the researchers used vector error correction term (VECM) to determine the short run and long run relationships of the independent variables (Labor Force Participation Rate,

Regional Output, and Real Wage) to the dependent variable (Employment Rate) used in this study. The researchers set the vector error correction term (VECM) at two period lag because this was the optimal lag according to the value of the Akaike Information Criteria (AIC). University of Santo Tomas – Economics Society 24 | P a g e

The C(1) in the regression model represents the long-run relationship of the independent variables in the employment rate which is the dependent variable. The probability of C(1) is less than 5% level of significance (Prob, 0.0072). Therefore, there is a long-run relationship between the dependent variable (Employment Rate) and to the independent variables (Labor Force

Participation Rate, Regional Output and Real Wage). Moreover, it also implies that the long-run coefficients of the independent variables that was indicated in the Johansen Co-integration test are simultaneously affecting the employment rate in the National Capital Region (NCR) in the long-run.

Furthermore, C(4) to C(9) represents the short-run coefficients of the independent variables in the regression model. C(4) and C(5) represents the coefficients of labor force participation rate, C(6) and C(7) represents the coefficients of regional output and lastly, C(8) and C(9) represents the coefficients of real wage. All of the coefficients are set at the optimal lags of two years according to the value of Akaike Information Criteria (AIC). All of the coffeicients have the probability greater than 5% significance level. This implies that the independent variables are insignificantly affecting the employment rate of the National Capital

Region in the short-run (period of two years).

Finally, C(10), which is the intercept in the model. The coefficient C(10) is also significant (Prob, 0.414) because it is less than 5% level of significance. C(10) coefficient implies to us that there is 0.776092% employment rate in the absence of labor force participation rate, real gross regional domestic product and real wage.

The results of the regression showed that labor force participation rate and employment rate exhibited the long-run relationship. Therefore as labor participation rate increases, employment rate will also increase in the case of National Capital Region and it will be University of Santo Tomas – Economics Society 25 | P a g e significant in the long-run (after two years). The result was in line with the findings of Balleer

Et. Al., (2009); Weerakoon and Arunatilake, (2011); Carrasco Et. Al., (2004); Montalvo, (2006) and Hüfner and Klein, (2012). Specifically, the long-run relationship between labor force participation rate and employment rate is positive according to the coefficient of Johansen Co- integration Test. In the perspective of the authors, the behavior of labor force participation rate and employment rate can be attributed to the role of women in the labor market of the National

Capital Region (NCR). In the past, women‟s work was limited because of traditions and culture.

But currently, women become more active in the labor market, attained higher levels of education, spent more time working, and achieving an increase of level of income. The explanation behind it can be explained by the study of Balleer et.al., (2009). According to the authors, age job openings, and acceptance of female workers in the labor market can increase the labor supply that will increase the employment rate in the long-run.

Furthermore, the results of the regression showed that regional output and employment rate are associated the long-run. However, it showed a negative long-run relationship. It contradicts the study of Massimiliano et.al., (2000); Krolzig and Toro, (1998); Caporale and

Skare, (2011); Yusop et.al., (2005); Caporale and Skale, (2011). This long-run negative relationship between regional output and employment rate in NCR can be attributed to its relationship with total productivity. Usually, economic or regional growth is positively correlated to the share of productivity and therefore, will lead to negative relationship between regional growth and employment rate. Moreover, economic or regional growth is affected by higher capital-labor ratio, giving a higher total productivity. Hence, it implies that a certain country or region will srtrive for higher economic or regional growth, it will hard for the people to seek employment. This analysis can be supported by the study of United Nations Research Institute University of Santo Tomas – Economics Society 26 | P a g e for Social Development (UNRISD). In their study, they stated that there is quantity-quality trade off as over time, the impact of productivity growth seems to slow down employment growth and in 1960‟s, a 1% increase in output per worker was associated with a reduction in employment growth of 0.07%, and in the first decade of 21st century, the same productivity increase implies reduced employment growth by 0.54% (UNRISD, 2010).

Moreover, the vector error regression revealed that there is significant long-run relationship between real wage and employment rate. This is aligned with the studies of Apergis and Theodosiu, (2008); Yusop et. al. (2005); Rath and Madheswaran, (2008); Mitsis, (2012);

Dickens et.al., (1999). Specifically, there is a direct or positive significant long-run relationship between the two variables. The results of the regression suggested that the implementation of complement policies in the labor market will sustain the employment rate in the long run.

Furthermore, any adjustments in both labor demand and prices will positively affect the employment rate in the National Capital Region (NCR) in the long-run as long as there is policy complementaries in the labor market. Apergis and Theodosiu, (2008) can support the analysis of the authors. Their study supported the Keynes‟s view that, labor demand increases that will affect the level of wages that will also have an effect on employment in the long-run.

But in the regression results, it was found out that the relationship between labor force participation rate, regional output, real wage are insignificant in affecting the employment rate in the short-run at lag of two years (optimal lag selection for short-run as indicated by Akaike information criteria).

In the case of labor force participation rate and employment rate, there is an insignificant relationship in the short-run. This rejects our proposition that the relationship between labor force participation rate and employment rate are significant in the short-run. The authors University of Santo Tomas – Economics Society 27 | P a g e perceived that the effect of labor force participation will not immediately affect employment rate whether it will give a negative or positive impact. This may be attributed to the level of competition to the employment opportunities in the National Capital Region (NCR). Also, other labor indicators that may affect the insignificance of labor force participaton in affecting employment rate have also showed insignificance in affecting employment. Some authors also analyzed the same way n their respective studies. (Bartik, 2002; Elmeskov and Pichelmann,

1993) found that there is an insignificant relationship between labor force participation rate and employment in the short-run. Elmeskov and Pichelmann, (1993) asserted that the insignificance of the relationship between labor force participation and employment can be explained by the low responsiveness of employment to labor force participation rate. Also, according to them, the responsiveness depends on unemployment variability, output variability, and the flexibility of real wages in the face of cyclical variations of activity.

On the other hand, the results of the regression showed that regional output and employment rate are not associated with each other in the long-run. Hence, it contradicts our proposition that there is a relationship between real gross regional domestic product and employment is significant in the short-run. This result came out in the regression due to some factors that the authors of this paper have analyzed. Firstly, in reality, regional output will significantly have an impact to employment, but if there are changes in the economy, or economic shocks, it may affect the significance of relationship between output and employment.

So secondly, the authors also studied the impact of the factors outside the model that will affect the impact of independent variables (Labor Force Participation Rate, Regional Output and Real

Wage) to the employment rate which is the dependent variable using the impulse-response function. Lastly, rural-urban migration may not result to employment immediately in the short- University of Santo Tomas – Economics Society 28 | P a g e run, hence it will not be translated or transmitted into contribution of final output for the National

Capital Region (NCR). This analysis was also in line with several studies in our review of related literature. Akcoraoglu, (2010); Hanusch, (2012) found that there is an insignificant relationship between real gross regional domestic product and employment. Furthermore, Akcoraoglu (2010) identified that the insignificant relationship occurred between real GDP and employment in the short-run is because of structural change in the economy, (population shift out of agriculture) therefore, migration from rural to urban areas, relatively high non-wage labor costs and the rigid regulatory framework in the labor market could cause this insignificant relationship.

Lastly, it was also found out in the regression results that real wage and employment rate are insignificantly related to each other in the short-run.

Again, this is inconsistent with the proposition that the relationship between real wage and employment is significant in the short-run. The result occurred because wage changes, particularly in the National Capital Region (NCR), can lead to layoff or permanent unemployment of employees. Since layoff is an issue of unemployment, it can be concluded in this analysis that, real wage have more significant effect in unemployment compared to employment. Nonetheless, Apergis and Theodosiu, (2008); Yusop et. al., (2005) concluded that there is an insignificant relationship between real wage and employment. In the study of Apergis and Theodosiu (2008), the insignificant relationship between real wage and employment in the short-run is because of increase in the aggregate demand for workers, therefore, increasing the probability to fight unemployment. Hence, real wages and unemployment are actually associated in the short-run.

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4.2B. Impulse-Response Analysis

Impulse-response functions describe how the economy reacts over time to exogenous impulses, which is called “shocks”, and are often modeled in the context of a vector autoregression. Impulse-response functions describe the reaction of endogenous macroeconomic variables such as output, consumption, investment, and employment at the time of the shock and over subsequent points in time. In this study, the authors used Cholesky degrees of freedom (dof) was used to estimate the effects when there is a one standard deviation of employment shocks to employment rate. Also, the authors set the impulse-response function from short-run which is 2 years (based from the value of Akaike

Information Criteria or AIC) up to 50 years of occurrence of economic shocks.

Figure 6: Impulse-Response Function Graph (Employment Shocks to Employment Rate)

Response of EMPR to Cholesky One S.D. EMPR Innovation

1.3

1.2

1.1

1.0

0.9

0.8 5 10 15 20 25 30 35 40 45 50

Figure 6 showed the impulse-response function graph between employment shocks

(EMPR) and employment rate (EMPR). The impulse-response graph showed that there is a positive impulse of employment shocks to employment rate. In the short-run, particularly two years after its occurrence, the effect of employment shocks have a positive effect, however when University of Santo Tomas – Economics Society 30 | P a g e compared to the first year after its effect, there is a sudden decline of positive effect on employment rate. But, after this period towards the long-run, the effect of this employment shocks to employment rate will increase and it will stabilize up to its equilibrium level, and it was estimated that it will start eighteen years after the employment shocks occurred, giving an increase to employment rate for an average of 1.16%.

Based on the figure above, an employment shock can lead to an increase in employment rate in the National Capital Region. This can be attributed to the level of investment, it could be from domestic or foreign that is injected on the said region that can increase the level of employment. This argument can be supported by the study of Villa (2010). According to the author‟s study, and investment subsidy can boost capital accumulation and have a sizable impact since an increase in employment has a positive effect on the growth of employment. Also, this can be done if an economy will show a favourable environment for local and foreign investors to generate employment. Therefore, having this investment subsidy in the National Capital Region

(NCR) can increase employment and also to prevent or fight the spell of unemployment.

Moreover, confidence of investors in the institutions of an economy is important.

Jayaraman and Singh (2007) also supported this claim. In their study in Fiji, they found unidirectional long run causality running from foreign direct investment to employment. They affirmed that foreign direct investment (FDI) contributed to the economic growth of Fiji because it enabled the country to step up its export-related activities by specifically focusing on resource development, employment creation and skills development. The gains from FDI include not only creation of employment in garment sector, which attracted overseas investors, but also of additional employment opportunities in ancillary sectors, which are supportive to all production oriented activities in the economy of Fiji. Hence, an innovation or shock in investment could increase employment in the different sectors in the National Capital Region (NCR). University of Santo Tomas – Economics Society 31 | P a g e

Figure 7: Impulse-Response Function Graph (Labor Force Participation Shocks to

Employment Rate)

Response of EMPR to Cholesky One S.D. LFPR Innovation

0.0

-0.2

-0.4

-0.6

-0.8

-1.0

-1.2

-1.4

-1.6 5 10 15 20 25 30 35 40 45 50

Figure 7 showed the impulse-response function graph between labor force participation shocks (LFPR) and employment rate (EMPR). The impulse-response graph revealed that there is a negative response of employment for every additional standard deviation of labor force participation shocks in the short- and the long-run. In the short-run (period of two years) there is a sudden decrease in employment rate by more or less 1.5% when labor force participation shocks occurred. However, after this period, there is a fluctuating but still a negative effect of labor force participation shocks on employment rate at estimation from three years up to twelve years. And after twelve years, the negative effect of labor force participation shocks or innovations on employment rate could become stationary that will give an average of 1.05% decrease to employment rate.

In the case of the National Capital Region in the Philippines, massive rural-urban migration into the region by most people who are endowed with less human capital could be the reason why labor force participation rate will lead to decrease in employment rate. This claim University of Santo Tomas – Economics Society 32 | P a g e can be supported by the study of Kahanec and Zimmerman (2008). In their study, the authors said that across OECD counties, the share of labour force with upper secondary or higher educational attainment is a predominantly positive function of the share of foreign labour force in the economy, while the same relationship is monotonously increasing in case of post- secondary or higher education. Since then, it can be inferred that higher educational attainment of those who will migrate to National Capital Region will increase the quality of education that will increase employment rate. Otherwise, low investment of human capital of those who will migrate in the National Capital Region will decrease the quality of labor force, that may lead to decrease in employment rate and increase in employment rate.

Figure 8: Impulse-Response Function Graph (Regional Output Shocks to Employment

Rate)

Response of EMPR to Cholesky One S.D. RGRDPR Innovation

-.1 5 10 15 20 25 30 35 40 45 50

Figure 8 showed the impulse-response function graph between regional output shocks

(RGRDPR) and employment rate (EMPR). The impulse-response graph revealed that generally, there is a positive effect of regional output shocks on employment rate. However, in the transition from short-run to long-run, (between two to three years), there is a negative effect of regional output shocks on employment rate. But after this sudden negative effect, the regional University of Santo Tomas – Economics Society 33 | P a g e output shocks will eventually give a positive effect on employment rate in a fluctuating manner and this will continue more or less until the twenty-fifth year. The effect of these regional output shocks on employment rate might attain its equilibrium after the twenty-fifth year onwards after its occurrence and it will increase the employment rate by more or less at 0.16%.

The regional output shocks that will affect the employment rate can also be attributed to innovation or improvement in technology because it can be inferred in the figure that technology will lead to a direct or positive relationship between the real gross regional domestic product rate and of employment rate in the aforesaid region. Again, this claim can be supported and confirmed by the study of Gali and Rabanal (2004). In their study, a very limited contribution of positive technology shocks or innovations to the variance of GDP and employment. However, to explain the technology shocks that will lead to a negative response of employment rate to regional output shocks after three years of its occurrence, the authors analyzed that it may happen if the National Capital Region (NCR) will focus solely on capital formation or improvements in technology in the long-run, because doing so may lead to a decline in employment. Gali, (1999), and Basu et. Al.(1998) have identified technology shocks or innovations based on plausible identification schemes and have found that in response to a positive technology shock or innovation, output rises while employment shows a persistent decline. Hence, the empirical correlation between employment and output conditional on technology shocks or innovations is negative.

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Figure 9: Impulse-Response Function Graph (Real Wage Shocks to Employment Rate)

Response of EMPR to Cholesky One S.D. RWAGE Innovation

0.0

-0.2

-0.4

-0.6

-0.8

-1.0

-1.2

-1.4

-1.6 5 10 15 20 25 30 35 40 45 50

Figure 9 showed the impulse-response function graph between real wage shocks

(RWAGE) and employment rate (EMPR). The impulse-response graph showed that there is a negative impulse of real wage shocks to employment rate. In the short-run, particularly from two to three years, the magnitude of the negative effect of real wage shocks or innovations could further decline the employment rate. However, the negative effect will be lessened after this period but real wage shocks still have a negative effect on employment rate. In the start of the long-run, there is fluctuating but negative effect of real wage shocks to employment rate. But this negative effect will reach its equilibrium level towards the twenty-fifth year onwards giving a decline on the employment rate at more or less at 1.14%.

This real wage shocks can be pointed out to migration-related supply that can affect the relationship between the real wage and employment rate in the National Capital Region (NCR).

Based on the figure above, an economic shock can lead to a negative relation between real wage and employment. This can be attributed to migration-related supply, specifically the immigration of employed people in rural areas to the National Capital Region (NCR). It may result to more stringent or severe employment opportunities and the quality of labor force in the region might University of Santo Tomas – Economics Society 35 | P a g e decline. This analysis can be supported by Calderon and Ibanez (2009). In their study, they concluded that immigration flows produce large negative impacts on the wages and employment opportunities of all workers, and are particularly large for low skill workers. Moreover, education and skill mismatches could be a reason that may affect the real wage that can eventually decrease the employment rate. This argument can be supported by the study of Allen and Verden (2001). The mentioned authors stated that both kinds of mismatches have a significant negative effect on wages. However, about half of the effect of skill underutilization disappears when educational mismatches are taken into account. By contrast, only small part of the effects of over- and under-education are accounted for by skill mismatches. The authors also emphasized that education mismatches have been found to affect a broad range of labor market outcomes such as job satisfaction and on-the-job search are important not only to individual workers, but also from the point of view of the workings of the labor force market. Therefore, skill matches and education mismatches in particular can affect the motivation of individuals to seek employment better suited to their own capabilities. Hence, education and skill mismatch could have a negative impulse between real wage and employment that can possibly diminish the level employment in the National Capital Region (NCR).

4.2C Variance Decomposition

Period S.E. EMPR LFPR RGRDPR RWAGE

11 6.484729 33.93406 30.51302 1.314767 34.23816 12 6.757598 34.21694 30.39722 1.282816 34.10303 13 7.033228 34.32536 30.12948 1.218227 34.32694 14 7.293892 34.40806 30.10787 1.172434 34.31164 15 7.544448 34.47013 30.02395 1.143984 34.36193 16 7.794152 34.49213 29.95754 1.108028 34.44230 17 8.032786 34.53928 29.95399 1.089138 34.41759 18 8.267219 34.57962 29.90062 1.070899 34.44885 19 8.496223 34.62341 29.87688 1.053232 34.44648 20 8.717545 34.67808 29.84999 1.041837 34.43009 21 8.934758 34.72528 29.80897 1.027944 34.43781 22 9.145847 34.77415 29.78398 1.016025 34.42585 23 9.351771 34.81936 29.75076 1.005199 34.42468 24 9.553589 34.85767 29.72102 0.993662 34.42765 25 9.750565 34.89381 29.69742 0.983823 34.42495 26 9.943847 34.92452 29.67153 0.974208 34.42974 27 10.13346 34.95187 29.65117 0.965179 34.43178 28 10.31945 34.97725 29.63218 0.957213 34.43336 29 10.50239 34.99984 29.61388 0.949545 34.43674 30 10.68214 35.02134 29.59846 0.942616 34.43758 31 10.85895 35.04158 29.58309 0.936216 34.43911 32 11.03301 35.06060 29.56891 0.930141 34.44035 33 11.20431 35.07893 29.55578 0.924557 34.44073 34 11.37307 35.09621 29.54285 0.919245 34.44170 35 11.53934 35.11261 29.53092 0.914225 34.44224 36 11.70323 35.12821 29.51949 0.909504 34.44280 37 11.86486 35.14287 29.50857 0.904990 34.44357 38 12.02430 35.15677 29.49837 0.900725 34.44414 39 12.18166 35.16991 29.48858 0.896672 34.44484 40 12.33701 35.18234 29.47934 0.892810 34.44551 41 12.49042 35.19416 29.47060 0.889150 34.44610 42 12.64198 35.20538 29.46223 0.885659 34.44673 43 12.79175 35.21608 29.45431 0.882333 34.44728 44 12.93978 35.22630 29.44673 0.879165 34.44780 45 13.08614 35.23606 29.43949 0.876135 34.44831 46 13.23088 35.24542 29.43257 0.873240 34.44877 47 13.37405 35.25438 29.42593 0.870467 34.44922 48 13.51571 35.26297 29.41958 0.867810 34.44965 49 13.65590 35.27121 29.41348 0.865262 34.45005 50 13.79466 35.27912 29.40761 0.862814 34.45045

Table 8 showed the variance decomposition of employment rate. Variance decomposition indicates the amount of information each variable contributes to the other variables in the University of Santo Tomas – Economics Society 37 | P a g e autoregression. It also determines how much of the forecast error variance of each variables can be explained by shock or innovation to the other variables. The authors based the timeframe of variance decomposition analysis from the impulse-response function. Short-run which is up to 2 years and long-run that will last until 50 years.

The table showed that after the in the short-run (period of 2 years), the employment shocks played a biggest influence in affecting employment rate at more or less 52%. It was followed by real wage shocks, particularly at roughly 28%, labor force participation shocks innovation at an average of 15% influence and regional output shocks at a more or less 3%.

Based on the table above, after one year of occurrence of the shocks or innovations on employment rate, labor force participation rate, regional output and real wage, it revealed that the employment rate shocks affect the employment rate by 100%. Hence, only employment shocks affect the level of employment in the National Capital Region (NCR). But in the 2nd period, the influence of employment rate shocks starts to decrease and the labor force participation shocks, regional output shocks and real wage shocks starts to have an influence on employment rate.

In the long-run (two to fifty years), the employment rate shocks or innovations still has the biggest influence on employment rate at an average of 35%. It was still followed by real wage shocks, at an average of 34% but at this period, it almost surpassed the influence of employment shocks on employment rate. It was followed by labor force participation shocks at roughly 15% and finally, the regional output shocks at almost 1% influence on employment rate.

Referring to the table above, as these shocks moved toward long-run, the influence of employment shocks to employment rate starts to decrease and the influence of labor force participation rate shocks, regional output shocks and real wage shocks on employment rate will start to increase. Also, it can be inferred that in the long-run, the shocks of employment rate, University of Santo Tomas – Economics Society 38 | P a g e labor force participation rate, and real wage have an almost equal share of influencing the employment rate in the long-run, having an influence that will range to 29% to 38% on the dependent variable. However, in the case or regional output shocks, it has decreased towards the long-run and only influenced the employment rate from 3% in the short-run, to almost 1% influence on the dependent variable which is employment rate.

5. Conclusion, Policy Implications and Recommendations for Further Studies

5.1 Conclusion

The identification of the short-run and long-run relationship between selected labor and macroeconomic indicators (labor force participation rate, regional output and real wage) and employment rate is important because these selected factors can play a significant role in determining the level of employment in the National Capital Region (NCR) and it has been recognized by most of the researchers. Also, it is important to determine the possible shocks or innovations that can affect the short- and long-run relationship of the said indicators to employment rate in the case of the National Capital Region (NCR) because these unexpected events can play a vital role in sustaining the level of employment in the aforementioned region in the short- and the long-run.

The main purpose of the study is to find evidence whether there is a significant short-run and long-run relationship between the labor force participation rate, regional output, and the employment rate in the National Capital Region (NCR). The researchers would also want to determine the possible economic shocks or innovations, that could affect the employment rate and its relationship with the aforesaid selected labor and macroeconomic indicators and as well the degree of their short-run and long-run influence that could make a significant change or effect on the endogenous variables used in this study. This study is significant because there are University of Santo Tomas – Economics Society 39 | P a g e few studies that are conducted for addressing sustainable employment in the Philippines particularly in the National Capital Region (NCR). This paper therefore provides new evidence and more comprehensive study regarding on the short-run and long-run relationship of selected labor and macroeconomic indicators and employment rate in the case of the National Capital

Region (NCR).

The results from the vector error correction model regression showed that labor force participation rate, regional output and real wage have are significant determinants of employment rate in the long-run. However, the results showed an insignificant relationship between the variables in the short-run. The authors of this study also found out based on impulse-response analysis that shocks or innovations on employment rate, and regional output will generally increase the employment rate. But the shocks or innovations on labor force participation rate and real wage will decrease the employment rate. Lastly, variance decomposition showed that in the short-run, employment rate shocks or innovations has the most influence on employment rate but in the long-run, it showed that shocks on employment rate, labor force participation rate, and real wage almost shared the same influence on employment rate.

5.2 Policy Implications

Since the vector error correction model regression results revealed that there is a significant relationship in the long-run between labor force participation rate, regional output and real wage and employment rate. It implies that any short-term policies that are proposed will be insignificant to sustain employment. However, authors would want to recommend that short- term policies that will be implemented in the labor market of though insignificant to sustain employment, should not decline the employment of the region. Rather, it is suggested that University of Santo Tomas – Economics Society 40 | P a g e policies should be long-term in order to ensure that the employment will be sustained in the

National Capital Region (NCR).

The authors of this study would want to recommend having investment or resources allocated to increase employment, while at the same time, forming capital not only allocated for advancements in technology. This could make a favorable business environment for local and foreign investors and enable them to generate and sustain employment. It is also important to ensure a competitive and fair business atmosphere with the coordination of the local government units in every cities and also with the private business firms in order to ensure that the current local and foreign investors will continue to invest and at the same time, to attract potential investors in order to provide more employment opportunities for the labor force of the National

Capital Region (NCR). A competitive and fair business atmosphere may be done though implementing taxes that will not distort the profit of the firms and having an organization of private firms with a goal of maximizing profit and at the same time having a social responsibility of caring for their employees and to sustain the level of employment within their business atmosphere. Moreover, the injection of investments should be allocated to generate employment that will be available to all industries around the region given that they will give significant increase in employment in the long-run or must be based according to the demand of labor force of a certain industry. Another proposal is to give attention to small- and medium-scale enterprises. These groups of enterprises can increase the wages, and eventually increase employment given that there is a certainty that it will develop and sustain in the long-run.

Moreover, technology innovations can be one of the programs that can be implemented to sustain employment. But these innovations on technology must not deprive the opportunities for employment. The authors of this paper do not want to substitute labor for capital or making University of Santo Tomas – Economics Society 41 | P a g e capital substitute for labor, but the other way around, to make capital a complement for labor which is the employees. In other words, labor or employees should still have significance on producing an output. The firm should still maximize the use of labor by making them to step on a bigger role in the organization in a microeconomic perspective given the technology advances in a certain industry or sector and this will be possible, if there is are ties or linkages between the policy-maker and to every individual firm. Therefore as technology advances, employment will also increase. For instance, the business processing industry (BPO), this industry rely not only on technology advancements but also to the number of people that will be using the technology, hence, capital and labor complement each other which is currently evident in the National

Capital Region (NCR) and needs to be sustained in the long-run in order for this industry to continue generate employment.

Also, the authors of this study would want to suggest to policy-makers make policies that will provide more employment opportunities for the labor force of the National Capital Region

(NCR). For instance, the labor and employment department of the government together with private sectors should help the labor force in their stages of their employment starting with giving useful information on how to select for employment after graduation, promoting sites that will give a list of all job listings available for those who seek employment and after having employment, track how people progress on their employment status. If this will happen, it will be possible that employment can be sustained in the long-run. Moreover, the author of this study would want to recommend the policy-makers to maintain the narrow gap between the employment rate of male and female. According to Bureau of Labor and Statistics (BLES), the average employment rate of male and female in the Philippines from 1998-2011 are 90.8% and

90.6% respectively. In order for the National Capital Region to contribute in this narrow gap University of Santo Tomas – Economics Society 42 | P a g e between the employment rate of males and females, the government must encourage male and female labor market participation and at the same time, maintain the narrow gap of their respective employment rates. This will show that employment opportunities are accessible to all people, regardless of gender and other aspects. Also, the authors would want to recommend equal employment opportunities not only for females, but also to persons with disabilities

(PWD‟s) and to lesbian, gay, bisexual, and transgender (LGBT) community and to have comprehensive labor and employment statistics to these group of persons in order to implement policies on how to provide equal and sustainable employment opportunities for them. Moreover, the authors of this study would want to advise the increase of investment of human capital through formal education and training not only in the National Capital Region (NCR) but to the areas outside the region. Because high investment in human capital through education and training will increase the quality of employment and if labor force coming outside the National

Capital Region (NCR) is endowed with high levels of human capital, the problem of underemployment and job mismatch will become less evident. So far, the government have

Technical Education and Skills Development Authority (TESDA) and its programs that will help people to invest in human capital through training. Also, the Department of Education (DepEd) and its programs also helps to develop the quality of education not only in the National Capital

Region (NCR), but also to the whole country. Currently, the K-12 was implemented to enhance the quality of education, this goal will be more realized if it will complemented with other policies that the authors would want to recommend. Firstly, K-12 will be successful if there is a budget allocated in improving public schools when it comes to its facilities and equipment.

Furthermore, this program will be efficient if there is continuous training and development of teaching staff and curriculum. Therefore, efforts to this program in order to be successful, is to University of Santo Tomas – Economics Society 43 | P a g e have continuous development of quality of education that will increase the quality of labor force that will eventually sustain employment in the long-run. If these proposals will be implemented, it will be possible that employment can be sustained in the long-run.

When it comes to the policies regarding on the output of the National Capital Region

(NCR), the authors of this study would want to recommend to policy-makers by having a proposal of structural reforms on the labor market, for instance, improving or make policies that will complement the Presidential Decree No. 442 or also known as, Labor Code of the

Philippines. The authors suggest that there are some articles that need to be improved in this law, specifically regarding contractualization. The authors believed that in order to maintain the employment in the long-run, contractual workers must be regularized or if not, they must find another work with the help of their current contractor before their contract expires. Moreover, the authors would want to recommend that the capital-intensive resources and labor-intensive resources should be complemented and efficient in order to achieve higher output for the

National Capital Region (NCR) while sustaining the employment in the long-run. It is possible if the region will not solely focus on capital formation on improving the level of technology.

Finally, in relation of real wages in policy-making, the researchers would want to recommend that the labor force within and outside the National Capital Region (NCR) should be given higher levels of education and training. Because of increasing demand of workers and migration of labor force coming from outside the National Capital Region (NCR), this will result to an increase of labor supply in the region, but it does not guarantee that this labor supply coming outside NCR are high quality or for the purpose of this study, skilled workers. As, the labor supply increases, given a fixed legislated wage can decrease employment because the firm‟s cost are increasing because there is no assurance that the cost of hiring workers will lead University of Santo Tomas – Economics Society 44 | P a g e to return for the firms which is measured by profit, this may lead to decrease returns to scale, assuming that labor is used as one of inputs to produce an output. Therefore, the authors of this paper recommend policy-makers to complement policies regarding on educating the labor force within and outside the National Capital Region (NCR), job creation and efficient allocation of capital and labor in order for the labor supply achieve true competition and to achieve more output not only in a microeconomic perspective but also more output in a macroeconomic view.

Another point relating to real wage, the authors of this paper would want to recommend to mandate a wage according to law that is aligned to the purchasing power of the consumers in the region, to the profits of firms for every industry in the region and particularly to the status of workers in the aforesaid region. For instance, if a worker has a contractual status of employment, probably there is no increase in wage if that worker will engage in extra work or overtime.

Therefore, the real wage of the worker will decrease that will eventually affect the employment in the region because that worker has an uncertain status of employment. If the contract of that certain worker is finished and there is no opportunity for employment, this will lead to a decrease in employment, but if that worker was able to find another opportunity to work because the contract maybe extended or because that worker became a regular employee, this will lead to sustainable employment.

The proposals stated by the authors above can be achieved if there is a mutual cooperation between the public and private sector in the National Capital Region (NCR) and a mutual goal that will bind them, which is to sustain and provide employment opportunities in the long-run.

University of Santo Tomas – Economics Society 45 | P a g e

5.3 Recommendations for Further Studies

Based from the study undergone with its results and implications, the authors of this paper would recommend other researchers to study the causality between employment, labor force participation, output and wages. Using other labor or macroeconomic indicators would also be advisable for instance, the inflation rate, unemployment rate, migration, rate, foreign direct investment, educational attainment and other related indicators that can affect the sustainability of employment. Also, using other locus or setting would be also highly recommended. Like for example, using the same variables that the authors of this paper have, but in the case of Region

IV-A, or whole country like the Philippines. In relation to this, panel data would also be empirically feasible to analyze, for instance, determining the short-run and long-run relationship of employment, labor force participation, output and wages in the case of Association of South-

East Asian Nations (ASEAN) countries. Also, it is also highly suggested to apply theories related to employment. For example, an application of golden triangle internal equilibrium theory wherein there is a employment growth, output growth, and inflation rate causes one another.

These recommendations would also give another perspective on how different factors or indicators would really affect employment.

Furthermore, primary data would also be good for having an analysis on sustaining the employment. Due to limited timeframe of doing this paper, the authors of this paper used secondary data which is easier to gather because it was only came from the different statistical databases of government. Having a primary data as an empirical foundation of analysis might be time-consuming, but it could give new perspective, more deep analysis, and more meaningful and significant results on how to sustain employment.

University of Santo Tomas – Economics Society 46 | P a g e

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Appendix

Appendix A: Research Simulacrum

Figure 1: Proposed Model and Hypothesis

Labor Force P2.1A Participation P2.2A

Regional P2.1B Employment Output P2.2B Rate

Real P2.1C

Wage P2.2C

Appendix B: Historical Trends of the Variables

Figure 2: Employment Rate

EMPR

90.0

87.5

85.0

82.5

80.0

77.5

75.0

72.5

70.0 86 88 90 92 94 96 98 00 02 04 06 08 10

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Figure 3: Labor Force Participation Rate

LFPR

58 86 88 90 92 94 96 98 00 02 04 06 08 10

Figure 4: Real Gross Regional Domestic Product Ratio

RGRDPR

22 86 88 90 92 94 96 98 00 02 04 06 08 10

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Figure 5: Real Wage

RWAGE

280

270

260

250

240

230

220

210

200

190 86 88 90 92 94 96 98 00 02 04 06 08 10

Appendix C: Johansen Cointegration Tests

Table 1: Unrestricted Cointegration Rank Test (Trace Statistics)

Unrestricted Cointegration Rank Test (Trace)

Hypothesized Trace 0.05 No. of CE(s) Eigenvalue Statistic Critical Value Prob.**

None * 0.867160 89.66072 47.85613 0.0000 At most 1 * 0.663081 43.23264 29.79707 0.0008 At most 2 * 0.422077 18.21062 15.49471 0.0190 At most 3 * 0.216083 5.599392 3.841466 0.0180

Trace test indicates 4 cointegrating eqn(s) at the 0.05 level * denotes rejection of the hypothesis at the 0.05 level **MacKinnon-Haug-Michelis (1999) p-values

Table 2: Unrestricted Cointegration Rank Test (Maximum Eigenvalue Statistics)

Unrestricted Cointegration Rank Test (Maximum Eigenvalue)

Hypothesized Max-Eigen 0.05 No. of CE(s) Eigenvalue Statistic Critical Value Prob.**

None * 0.867160 46.42808 27.58434 0.0001 At most 1 * 0.663081 25.02202 21.13162 0.0134 At most 2 0.422077 12.61122 14.26460 0.0897 University of Santo Tomas – Economics Society 54 | P a g e

At most 3 * 0.216083 5.599392 3.841466 0.0180

Max-eigenvalue test indicates 2 cointegrating eqn(s) at the 0.05 level * denotes rejection of the hypothesis at the 0.05 level **MacKinnon-Haug-Michelis (1999) p-values

Table 3: Johansen Co-integration Long-run Coefficients

1 Cointegrating Equation(s): Log likelihood -167.9571

Normalized cointegrating coefficients (standard error in parentheses) EMPR LFPR RGRDPR RWAGE 1.000000 0.660078 -2.454748 0.259191 (0.31763) (0.26413) (0.04949)

Appendix D: VECM Regression Results

Table 4: Vector Error Correction Model (VECM) Regression Results

Coefficient Std. Error t -Statistic Prob.

R-squared 0.654004 Mean dependent var 0.295652 Adjusted R-squared 0.414468 S.D. dependent var 1.688592 S.E. of regression 1.292112 Akaike info criterion 3.649453 University of Santo Tomas – Economics Society 55 | P a g e

Sum squared resid 21.70419 Schwarz criterion 4.143146 Log likelihood -31.96871 Hannan-Quinn criter. 3.773616 F-statistic 2.730297 Durbin-Watson stat 2.315343 Prob(F-statistic) 0.049045

Appendix E: Impulse-Response Graph

Figure 6: Impulse-Response Function Graph (Employment Shocks to Employment Rate)

Response of EMPR to Cholesky One S.D. EMPR Innovation

1.3

1.2

1.1

1.0

0.9

0.8 5 10 15 20 25 30 35 40 45 50

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Figure 7: Impulse-Response Graph (Labor Force Participation Shocks to Employment

Rate)

Response of EMPR to Cholesky One S.D. LFPR Innovation

0.0

-0.2

-0.4

-0.6

-0.8

-1.0

-1.2

-1.4

-1.6 5 10 15 20 25 30 35 40 45 50

Figure 8: Impulse-Response Graph (Regional Output Shocks to Employment Rate)

Response of EMPR to Cholesky One S.D. RGRDPR Innovation

-.1 5 10 15 20 25 30 35 40 45 50

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Figure 9: Impulse-Response Graph (Real Wage Shocks to Employment Rate)

Response of EMPR to Cholesky One S.D. RWAGE Innovation

0.0

-0.2

-0.4

-0.6

-0.8

-1.0

-1.2

-1.4

-1.6 5 10 15 20 25 30 35 40 45 50

Appendix F: Variance Decomposition Table

Table 5: Variance Decomposition Table (Employment Rate)

Period S.E. EMPR LFPR RGRDPR RWAGE

1 1.292112 100.0000 0.000000 0.000000 0.000000 2 2.101313 52.76740 15.35211 3.030653 28.84983 3 3.057896 32.20676 31.24501 1.528865 35.01937 4 3.617297 32.08691 32.22496 1.498626 34.18950 5 4.238362 30.25164 30.52017 1.220149 38.00805 6 4.709584 30.45643 32.59408 1.270235 35.67925 7 5.104424 31.73759 31.84507 1.551457 34.86589 8 5.520337 32.33351 31.19683 1.425520 35.04414 9 5.854520 33.08567 31.35871 1.458527 34.09709 10 6.176385 33.63033 30.71571 1.405823 34.24813 11 6.484729 33.93406 30.51302 1.314767 34.23816 12 6.757598 34.21694 30.39722 1.282816 34.10303 13 7.033228 34.32536 30.12948 1.218227 34.32694 14 7.293892 34.40806 30.10787 1.172434 34.31164 15 7.544448 34.47013 30.02395 1.143984 34.36193 16 7.794152 34.49213 29.95754 1.108028 34.44230 17 8.032786 34.53928 29.95399 1.089138 34.41759 18 8.267219 34.57962 29.90062 1.070899 34.44885 19 8.496223 34.62341 29.87688 1.053232 34.44648 20 8.717545 34.67808 29.84999 1.041837 34.43009 21 8.934758 34.72528 29.80897 1.027944 34.43781 University of Santo Tomas – Economics Society 58 | P a g e

22 9.145847 34.77415 29.78398 1.016025 34.42585 23 9.351771 34.81936 29.75076 1.005199 34.42468 24 9.553589 34.85767 29.72102 0.993662 34.42765 25 9.750565 34.89381 29.69742 0.983823 34.42495 26 9.943847 34.92452 29.67153 0.974208 34.42974 27 10.13346 34.95187 29.65117 0.965179 34.43178 28 10.31945 34.97725 29.63218 0.957213 34.43336 29 10.50239 34.99984 29.61388 0.949545 34.43674 30 10.68214 35.02134 29.59846 0.942616 34.43758 31 10.85895 35.04158 29.58309 0.936216 34.43911 32 11.03301 35.06060 29.56891 0.930141 34.44035 33 11.20431 35.07893 29.55578 0.924557 34.44073 34 11.37307 35.09621 29.54285 0.919245 34.44170 35 11.53934 35.11261 29.53092 0.914225 34.44224 36 11.70323 35.12821 29.51949 0.909504 34.44280 37 11.86486 35.14287 29.50857 0.904990 34.44357 38 12.02430 35.15677 29.49837 0.900725 34.44414 39 12.18166 35.16991 29.48858 0.896672 34.44484 40 12.33701 35.18234 29.47934 0.892810 34.44551 41 12.49042 35.19416 29.47060 0.889150 34.44610 42 12.64198 35.20538 29.46223 0.885659 34.44673 43 12.79175 35.21608 29.45431 0.882333 34.44728 44 12.93978 35.22630 29.44673 0.879165 34.44780 45 13.08614 35.23606 29.43949 0.876135 34.44831 46 13.23088 35.24542 29.43257 0.873240 34.44877 47 13.37405 35.25438 29.42593 0.870467 34.44922 48 13.51571 35.26297 29.41958 0.867810 34.44965 49 13.65590 35.27121 29.41348 0.865262 34.45005 50 13.79466 35.27912 29.40761 0.862814 34.45045

Appendix G: Unit Root Test and Diagnostics Tests

Table 6: Unit Root Test on Employment Rate (EMPR)

Null Hypothesis: D(EMPR) has a unit root Exogenous: Constant Lag Length: 0 (Automatic based on AIC, MAXLAG=5)

t-Statistic Prob.*

Augmented Dickey -Fuller test statistic -6.101353 0.0000 Test critical values: 1% level -3.737853 5% level -2.991878 10% level -2.635542

*MacKinnon (1996) one-sided p-values. University of Santo Tomas – Economics Society 59 | P a g e

Table 7: Unit Root Test on Labor Force Participation Rate (LFPR)

Null Hypothesis: D(LFPR) has a unit root Exogenous: Constant Lag Length: 0 (Automatic based on AIC, MAXLAG=5)

t-Statistic Prob.*

Augmented Dickey -Fuller test statistic -6.425010 0.0000 Test critical values: 1% level -3.737853 5% level -2.991878 10% level -2.635542

*MacKinnon (1996) one-sided p-values.

Table 8: Unit Root Test on Real Gross Regional Domestic Product Ratio (RGRDPR)

Null Hypothesis: D(RGRDPR) has a unit root Exogenous: Constant Lag Length: 0 (Automatic based on AIC, MAXLAG=5)

t-Statistic Prob.*

Augmented Dickey -Fuller test statistic -5.000260 0.0005 Test critical values: 1% level -3.737853 5% level -2.991878 10% level -2.635542

*MacKinnon (1996) one-sided p-values.

Table 9: Unit Root Test on Real Wage (RWAGE)

Null Hypothesis: D(RWAGE) has a unit root Exogenous: Constant Lag Length: 0 (Automatic based on AIC, MAXLAG=5)

t-Statistic Prob.*

Augmented Dickey -Fuller test statistic -4.702522 0.0011 Test critical values: 1% level -3.737853 5% level -2.991878 10% level -2.635542

*MacKinnon (1996) one-sided p-values.

University of Santo Tomas – Economics Society 60 | P a g e

Figure 10: Normality Test (Jarque-Bera Test)

8 Series: Residuals 7 Sample 1988 2010 Observations 23 6 Mean -1.93e-16 5 Median 0.194589 Maximum 2.469944 4 Minimum -2.351935 Std. Dev. 0.993254 3 Skewness 0.139362 Kurtosis 3.752002 2 Jarque-Bera 0.616394 1 Probability 0.734771 0 -2 -1 0 1 2

Table 10: Serial Correlation Test (Breusch-Godfrey Serial Correlation LM Test)

Breusch-Godfrey Serial Correlation LM Test:

F-statistic 1.044471 Prob. F(2,11) 0.3843 Obs*R-squared 3.670708 Prob. Chi-Square(2) 0.1596

Table 11: Heteroskedasticity Test (Breusch-Pagan-Godfrey Test)

Heteroskedasticity Test: Breusch-Pagan-Godfrey

F-statistic 0.499022 Prob. F(12,10) 0.8731 Obs*R-squared 8.614446 Prob. Chi-Square(12) 0.7355 Scaled explained SS 3.786841 Prob. Chi-Square(12) 0.9870