“The impact of economic growth on unemployment in South Africa: 1994-2012”

One of the most pressing problems facing the South African economy is unemployment, which has been erratic over the past few years. This paper analyzed the impact of economic growth on unemployment, using quarterly South African time series data from 1994-2012. The results of Johansen cointegration reflected that a long run equilibrium or relationship exists among the variables. In ascertaining the effects of macroeconomic variables thus REER, LP, GDP and BUG on unemployment in South Africa, the study utilized vector error correction model (VECM). The results of VECM indicated that GDP, BUG and REER have positive long run impact on unemployment whilst LP negatively impact unemployment. The study resulted in the following policy recommendation: South African government should redirect its spending towards activities that directly and indirectly promote creation of employment and decent jobs, a conducive environment and flexible labor market policies or legislations without impediments to employment creation should be created, and lastly government should prioritize industries that promote labor intensive. All this will help in absorbing large pools of the unemployed population thereby reducing unemployment in South Africa.


Introduction ©
South Africa is one of the African countries that is endowed with a lot of resources, both human and minerals.However, due to activities such as increase in corruption, gross mismanagement and adverse policies of various governments, these resources have not been optimally utilized.For instance, Faul (2013) points out the controversial scenario of the misuse of taxpayer's money and government funds worth almost 250 million rands on the upgrade of President Zuma's private house in his home village.Osinubi (2005) adds that resources should be fully utilized and channelled to profitable investments so as to bring about maximum economic benefits.As a result of not fully utilising and channelling resources in the right direction then a nation will end up having continual problems of unemployment and poverty (Osinubi, 2005).This is true of South Africa which is facing the greatest challenge of chronic unemployment which has maintained a rising trend over the past years (Berkowitz, 2011).Unemployment is undesirable and it significantly contributes to widespread of poverty and income inequality in South Africa.Furthermore, unemployment and poverty have led to tremendous increases in crime rates, morbidity and unrests, just mentioning few.
The issue of unemployment in South Africa is well pronounced as evidenced by many schools leavers and even graduates who cannot find jobs and many engage in jobs in which their potentials are not fully utilized.Isobel (2006) highlights that the chronic nature of unemployment in South Africa is reflected by the fact that many unemployed people have never worked before.In addition, many people who are unemployed and still actively looking for work have been looking for employment in excess of 3 years.The total labor force or economically active population in South Africa is comprized of all individuals of working age (between 15-64 years) who are either employed or unemployed.The youths consist of the large fraction of the unemployed population in South Africa.According to Lings (2012), the released first quarter for 2012 of Labor Force survey (FLS) by Stats SA reflects that there were 32.786 million people aged between 15 and 64 years in South Africa (up by 116 000 relative to Q4 2011 and up by 472 000 year on year).The number of economically active people was 17.948 million for comparison purposes with 2011 reflecting an increase by 207 000 relative to Q4 2011 and up by 466 000 on year to year.From this group, 13.497 million were employed, reflecting a decrease of 75 000 of employed people relative to Q4 2011 and up by 304 000 year on year.On the hand 4.526 million were unemployed, reflecting an increase of 282 000 relative to Q4 2011 and up by 162 000 year on year (Lings, 2012).
In order for someone to comprehend the term unemployment, there is a need to look at different types of unemployment namely: seasonal, structural, frictional and cyclical.Put differently, unemployment is mainly defined according to its causes.The main type of unemployment experienced in South Africa is structural unemployment.Structural unemployment occurs when there is a change in the structure of an industry or the economic activities of the country (Njoku and Ihugba, 2011).Some of the factors that contribute to increased unemployment rates are rapid changes in technology, inflation, recession and changes in taste, among others.Smit, Mostert and Oosthuizen (2006) note that the South Africa economy experienced rapid technological advancements which led to most industries to be more capital intensive, resulting in structural unemployment as human labor is no longer required.In addition, structural unemployment is associated with the mismatch between the skills of the workers and the skills requirements of available jobs.
As stated above, another type of unemployment is seasonal unemployment.Njoku et al. (2011) explains that seasonal unemployment is due to seasonal variations in the activities of particular industries caused by climate changes, changes in taste or by the inherent nature of such industries.For instance in agriculture sector in South Africa, farm workers in vineyards in the Western Cape are classified as seasonal workers.They tend to be on high demand during the harvesting period and are unemployed during off period season.Frictional unemployment however exists when there is unsatisfied demand for labor, because unemployed workers may be unable to fill the unsatisfied demand either because they do not possess the necessary skills or workers are not aware of the existence of jobs in question.This type of unemployment is very common in South Africa, mostly amongst unemployed unskilled laborers as they move from one place to another because there is lack of communication facilities such as telephones, internet and employment stations (Mafiri, 2002).Cyclical unemployment is also known as Keynesian unemployment and it is due to deficiency of aggregate effective demand.During the times of recession, business activities are low, most people lose their jobs and the economy faces higher levels of unemployment.Mafiri (2002) elucidates that in South Africa, cyclical unemployment has a dimension that makes it uneasy to address successfully: it is superimposed on large scale structural unemployment.As a result, the unemployment problem becomes severe, complex and difficult to alleviate.
The problems that were inherited from apartheid to a greater extent had and continue to have an influence on the nature of development in South Africa in terms of post-apartheid policies to subdue problems such as of unemployment, poverty and income inequality.The advent of democracy in 1994 created hope for better living standards and other expectations among previously disadvantaged population.Chikulo (2003) states that in an effort to reduce not only socio-economic imbalances in South Africa but also to meet these high expectations among the majority of the black population.The new government pledged rapid socio-economic development by prioritizing reduction in unemployment, poverty alleviation and income inequality in its development strategy agenda.In the early years of a democratically elected government entering into power, the issue of unemployment, poverty and income inequality needed immediate attention.The South African government thus introduced various development polices and strategies namely: (1) Redistribution Development Program (RDP), (2) Growth Employment and Redistribution Policy (GEAR), (3) Accelerated and Shared Growth Initiative of South Africa (ASGISA), and (4) Joint Initiative for Priority Skills Acquisition (JIPSA).These policies were introduced to combat challenges of chronic unemployment, poverty and income inequality.
Theoretically, economic growth is viewed as the most prominent instrument for reducing unemployment, poverty and to help improve the living standards of people.Kreishan (2011) states that an increase in the growth rate of GDP of an economy is expected to increase employment levels thus reducing unemployment.This is a widely accepted view in economics theory, hence the theoretical proposition relating output and unemployment is known as Okun's Law.Okun's law describes one of the famous empirical relationships of output and unemployment in macroeconomics theory and has been found to hold for several countries mainly in developed countries (Lee, 2000;Fariso & Quade, 2003;Daniels & Ejara, 2009).Osinubi (2005) observed that although economic growth is necessary for trimming down unemployment and poverty alleviation.However, it is not sufficient since economic growth alone cannot overcome all the crucial factors that contribute to poverty and unemployment.Therefore, there is a need to adopt more policies that help to construct investment programs which enable job creation, thus, spurring economic growth and eradicating of poverty.

Statement of the problem
The transition from apartheid to democracy in South Africa led to the era of economic redressing, in order to deal with inherited economic and social legacies of apartheid which includes high unemployment, income inequality and poverty level.Soon after the first elections of 1994, a crisis of expectations was created among the majority of previously disadvantaged South African citizens and they became optimistic that the new government might be able to subdue the levels of unemployment, income inequality and poverty (Chikulo, 2003).Now, it is more than a decade after the first democratic elections of 1994, unemployment levels still remain high, and a major concern in South Africa.One of the most pressing problems facing South African economy is unemployment which has been erratic over the past few years, and official statistics of unemployment are currently at 24.5% according to Quantec (2015).Without doubt high unemployment is reality within the South African economy and most of unemployed group consist of the black population.Kingdon and Knight (2007) highlight some of the economic and social implications of unemployment in any nation and they state that it results in erosion of human capital, social exclusion, unrests, increases in crime rates and morbidity.Unemployment also contributes to widespread poverty and increases income inequality, thus, widening the gap or difference between the haves and the have-nots in a country.The South African government is therefore in a continual battle against unemployment and it is looking for policies that promote employment.By engaging in those policies that creates conducive environment for employment, the unemployment problem in the country will be alleviated.
Most developing and under-developing countries experience persistent problems of job shortage and unemployment.Over the past years the rate of job creation in South Africa has not matched the growth in the labor force.When a country is experiencing declines in employment creation associated with rising or positive economic growth this phenomenon is called "jobless growth."Biyase and Bonga-Bonga (2010) allege that there were hot debates and many concerns raised by policymakers and economists suggested that South Africa experienced "jobless growth."This reflects on the inability of the domestic economy to create jobs.Hence the influence of economic growth in South Africa requires to be investigated.

Research objectives
The main objective of the study is to investigate the impact of economic growth on unemployment in South Africa.This broad objective is explored through the following sub-objectives: ♦ To review the trends of economic growth and unemployment in South Africa since 1994.♦ To examine the relationship between economic growth and unemployment in South Africa.♦ To make policy recommendations to foster growth and reduce unemployment levels in South Africa.

Research hypothesis
The study hypothesised that: ♦ H 0 : Economic growth does not have a significant negative impact on unemployment in South Africa.♦ H 1 : Economic growth has a significant negative impact on unemployment in South Africa.

Review of the related literature
Plethora of literature on the issue of unemployment and economic growthis available.This study is underpinned by several unemployment theories (Classical and Keynesian) and economic growth theories (Neoclassical and Endogenous).Classical theory postulated that any unemployment that exists in the economy would be short lived and the operation of the free market forces automatically restores full employment in the economy.
where t is time trend, UR t , GDP t , EXP t , FDI t are unemployment rate, gross domestic product, exports and foreign direct investment respectively.
In modifying the model in equation 1, this study adds three variables which are government deficit, labor productivity and real effective exchange rate.equation 2 below is modelled with variables adjusted to suit this study, where unemployment is modelled as a function of gross domestic product, budget deficit, real effective exchange rate and labor productivity.The empirical model of the study, therefore, is specified as follows: All the variables used in this study are converted to natural logarithms so as to minimize the impact of outliers and to obtain elasticity coefficients of these variables.Therefore, the model to be estimated is as follows: Failure to reject the null hypothesis (failing to pass units tests) implies that the variables are nonstationary at level and this requires first or higher order differencing in order to make them stationary.
The other variables: GDP, LP and UN only became stationary after the first differencing.This reflected that null hypothesis was rejected in favor of alternative hypothesis and making the series to be stationary.Therefore, all the variables used are integrated in the same order I(1).

Cointegration tests results.
After establishing that variables are stationary, the next procedure is to perform cointegration tests so as to determine whether there exists long run relationship amongst the variables.The purpose of performing cointegration in this study is to examine the longrun equilibrium or relationship between unemployment and the explanatory variables (GDP, REER, LP and BUG) and this can also help in attaining feasible economic conclusions based on the outcomes or results obtained.For testing for cointegration, this study employed the Johansen's (1991, 1995) maximum likelihood method.Before establishing the long-and short-run coefficients, the Johansen technique utilized in this study also requires an indication of lag of the lag order and the deterministic trend assumption of the VAR.In order to select the lag order for the VAR, this study applied the information criterion approach as a direction to choose the lag order.Table 2

Vector error correlation model (VECM).
Variables can either have short-or long-run effects, this study utilized a vector error correction model (VECM) to disaggregate these effects.The purpose of VECM technique is that it allows us to distinguish between long-and short-run impacts of variables for the unemployment model.Using the results obtained from cointegration tests, the VECM was specified and the results of VECM are reported in Table 5 and 6 below.
The equation 4 reflects that GDP, REER and BUG have a positive long-run relationship with unemployment.It is worth mentioning that REER and BUG are statistically significantas displayed above in explaining unemployment since their absolute t-statistic values are greater 2. The results, therefore, suggest that a one percent unit increase in REER (an appreciation) increases unemployment by approximately 0.446 thus appreciation leads to reduction on job creation in the long run.The results also suggest that a one percent unit increase in GDP increases unemployment by approximately 19.497.Usually an increase in economic growth is accompanied by reduction in unemployment level.However when growth is not accompanied with job creations, this is regarded as a "jobless growth" phenomenon.Mahadea (2003) produced similar results and mentioned that South Africa experienced positive economic growth rates which have been associated with shrinking job creation.The results confirm the jobless growth hypothesis that states South African GDP growth is failing to create jobs.
Equation 4 also reflects that only LP has a negative long-run relationship with unemployment.Consequently the results suggest that a one percent unit increase in LP reduces unemployment by approximately -0.289.This relationship is compatible with the economics theory.Marginal productivity theory, specify that as long as the marginal product of the extra worker is increasing this induces firms or businesses to hire more workers hence reflecting a negative relationship between LP and unemployment.Furthermore, the results also suggest that a percent unit increase in BUG increases unemployment by approximately 0.609.The results in Table 7 show that there is no serial correlation, no conditional heteroskedasticity and there is a normal distribution in the unemployment model.

Impulse response analysis.
The impulse response analysis in Figure 1 (see in Appendix) reflect the dynamic response of unemployment to a one-period standard deviation shock to the innovations of the system and also point out the directions and persistence of the response to each shock over a 10 year period.The analysis suggests that the shocks to all the variables are significant although they are not persistent.A single period standard deviation shock to GDP and REER marginally diminished the level of unemployment from a period 2 years and 2 years respectively but the impact dies off in a period of about 3 and 4 years respectively.A one-period standard deviation shock to LP appreciates unemployment from period 2.5 until it reaches 5 years and gradually levels off.The one-period standard deviation shock to BUG reflects a very turbulent nature, for instance in the period 1 BUG appreciates unemployment up to period 2, thereafter from period 2 up to 4 BUG diminished unemployment and this kind of sequence keeps on continuing until it gradually levels out during the period of 8 years.These results suggest that an increase in both GDP and REER imply diminishing unemployment.

Variance decomposition analysis.
The results of the variation decomposition analysis are presented in Table 8 and the results reflect that the proportion of the forecast error variance in unemployment explained by its own innovations and innovations in macroeconomic variables.
For the purpose of ascertaining the effects of macroeconomic variables on unemployment for a relatively longer time, this study performed variance decomposition for 10 years period.The results in Table 8 revealed that in the 1 st year, all of the variance in unemployment is explained by its own innovations (shocks).In the 5 th year, unemployment itself explains 89.9 percent of its variation, while macroeconomic variables explain the remaining 10.1 percent.Of this 10.1 percent, GDP explains 2.2 percent, REER explains 6.3 percent, LP explains 0.8 and BUG explains 0.8.However, in the 10 th year, unemployment explains 82.6 percent of its own variation, while other macroeconomic variables explain the remaining 17.4 percent.The influence of GDP increased to 3.90, while REER increased to 11.4 percent, LP increased to 1.4 percent and also BUG decreased to about 0.76 percent.These results are compatible with the economics theory as shocks to macroeconomic variables thus GDP, REER, LP and BUG continue to explain a significant proportion of variations in unemployment.

Conclusions and recommendations
This study was motivated by the growing importance of unemployment and growth relationship in developing countries.However, little has been done to explore the unemployment-growth nexus in developing countries especially in Africa.The South African economy is currently experiencing problems of job shortage and the rate of unemployment has been erratic over the past years.This led to policymakers and economists to construct sets of possible reasons why the level of unemployment rate in South Africa is so high, so as to find ways to curbing it.
In light of the above summary, the results suggest several policy recommendations that can be drawn in order to reverse the trend of erratic unemployment.These recommendations are expected to significantly contribute to employment generation in South Africa.
After apartheid the South African government promulgated several laws that have significantly changed the labor market institutions.Arora and Ricci (2006) argue that aspects of some labor practices and regulations such as laws governing collective bargaining processes, labor standards and working conditions have contributed to high unemployment by rendering the labor market inflexible.In addition changes in the labor market institutions consist of significant costs to employers and consequently deter employment creation.An important issue raised in this study was that government alone cannot combat high level of unemployment that is in South Africa.The government needs to create conducive environment and flexible labor market policies or legislations that entice many private sector and small businesses, thus consolidating the existing entrepreneurship with the new entrepreneurial so as to creates more employment and absorbing a large pool of unemployed group.
Attainment of high growth and creation of decent employment still remains a challenge in South Africa.The study revealed that economic growth plays a vital role in curtailing down unemployment levels.However, in order to achieve impressive growth rates that will help to boon the nation or economy and boost the demand for labor and decent employment creation.Policymakers should create policies that support and promotes accelerated and sustained economic growth.
The study revealed that a one percent increase in BUG increases unemployment by approximately 0.609.In contrary, some economists and policymakers acclaimed the use of adopting a budget deficit policy; when government spends more than the revenue it collects so as to promote and boost employment creation thus reduces unemployment levels.However to curtail down the unemployment levels, the study suggest that the South African government should redirect its spending towards activities that directly or indirectly promote the creation of employment through improving healthcare facilities, infrastructure development strategy, education and employment inducing programs.Even activities that help in crime fighting can assist in creating a good reputation for South Africa and to be a safe investment destination for many investors (whether they are domestic or international investors), consequently reducing unemployment levels.Unemployment has been persistent for quite some time.Samson, Quene and Niekerk (2001) elucidated that the technological production method employed within the South African economy is more capital intensity rather than labor intensity and also increasing the demanding for skilled labor.This tend to be a challenging factor since the most unemployed groups are unskilled and less skilled labor therefore job creation policies on sectors that employ these groups should be prioritized through engaging in labor intensive industries.

Table 1 .
InREER t is the natural logarithm of real effective exchange rate, measured in foreign currency terms; InBUG t is the natural logarithm of budget deficit; InLP t is the natural logarithm of labor productivity; β 0 = Intercept term, β 1 , β 2 , β 3 and β 4 are the parameter estimates or coefficients of explanatory variables and ε is the error term.The results show that most variables failed to pass both the ADF and P-P tests when they are in level expect the REER and BUG.
Gujarati (2004) the natural logarithm of unemployment in South Africa (strict definition of unemployment rate); InGDP t is the natural logarithm of gross domestic product and is used as a proxy for economic growth;3.3.Estimation techniques.3.3.1.Testing for stationary or unit root test.To test for the presence of unit roots in the series, the study used the Augmented Dickey-Fuller (ADF) test and the Phillips-Perron (PP).Gujarati (2004)stresses that regressing of a non-stationary time series on one or more non-stationary time series may produce

Table 1 .
Unit root tests results

Table 2 .
Lag selection criterion Notes: *indicates lag order selected by the criterion; LR: sequential modified LR test statistic (each test at 5% level); FPE: Final prediction error; AIC: Akaike information criterion; SC: Schwarz information criterion; HQ: Hannan-Quinn information criterion.

Table 4 .
Unrestricted cointegration rank test (maximum eigenvalue) results results of both tests reported in Table3and Table4showed that at least 1 cointegration equation exists at 5% significant level.For the trace test, the null hypothesis of no cointegrating vectors is rejected since the test statistic of 79.70581 is greater than the 5% critical value of approximately 68.81889.However on the null hypothesis of 1 cointegrating vectors, the trace test failed to reject since the test statistic of 42.92512 is less than the 5% critical value of 47.856143.

Table 5 .
Long-run cointegration equation results The results from Table5above illustrate the long run impact of explanatory variables (GDP, REER, LP, and BUG) on unemployment in South Africa in an equation form as follows: UN = -286.307+ 19.497GDP + 0.446REER --0.289LP + 0.609BUG.

Table 6 .
Error correction results

Table 7 .
Diagnostic checks results

Table 8 .
Variance decomposition analysis