The Relation between Unemployment Rate and Economic Growth in USA
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1 The Relation between Unemployment Rate and Economic Growth in USA by Iulia Roșoiu, Andreea Roșoiu The Bucharest University of Economic Studies Faculty of Finance, Insurance, Banks and Stock Exchanges, Romania The Bucharest University of Economic Studies Faculty of Finance, Insurance, Banks and Stock Exchanges, Romania Abstract: The relation between unemployment rate and gross domestic product for the economy of United States of America is important to be analyzed, especially in the context of the current financial crisis. The relation between these two variables is known in the economic literature as Okun's Law. According to this law, during recession periods, the unemployment rate has a stronger reaction to a certain variation in gross domestic product evolution. On the other hand, the unemployment rate keeps its value around a natural level during economic upswings periods. The results obtained from the regression between unemployment rate and economic growth over the period show that these variables respect the relation described by Okun's Law. Moreover, the evolution of the unemployment rate is also influenced by other factors which are not included in the analysis. Key words: economic growth, Okun's Law, regression analysis, unemployment rate, United States of America JEL classification: E23, E24, O51 1 Introduction Okun s law was analyzed by economists over different periods of time and for different countries. Although different econometric methods were used, at the end, same conclusion was drawn: that unemployment rate variation is influenced, in the opposite way, by gross domestic product evolution. The relation between these two variables was estimated, for the first time, by Okun in The purpose of this paper is to analyze this relation for the economy of United States of America over the period , considering annual data. This research is organized as follows: first section, Literature review, offers some information regarding several other results that were obtained in different studies regarding the relation between the two above mentioned variables. The following section, Case study, is organized in three subsections and offers details about the data set that is used for investigation, details about the methodology and also details about the results of this study. And the final section, Conclusions, makes a summary and also some proposals for future research. 2 Literature review In his article, Ledesma (2002), explains the difference between the hysteresis phenomenon and persistence phenomenon. The unemployment rate can be characterized by one of these. The existence of hysteresis should not be confused with persistence. Persistence implies that, although the speed of adjustment towards the equilibrium level is slow, unemployment shows mean reversion. Under hysteresis, macroeconomic policy would have permanent effects on unemployment. Under persistence phenomenon the situation is the opposite one, macroeconomic policy would not have permanent effects on unemployment anymore. The author applied a panel unit root test to test for the existence of hysteresis in unemployment rates of 51 US states and 12 European Union countries over the period , using quarterly data. The results show a higher degree of persistence in the USA unemployment series 162
2 than in that of the European Union. This is still the case even after the period of the two oil shocks that affected adversely the more developed economies and may be a result of the higher degree of labor mobility in the US states. Yazgan and Yilmazkuday (2003) concluded in their research that the values recorded by the Okun s coefficient, for each USA state, over the period , are influenced by the geographical position of each state. This can be explained by people migration between states. 3 Case study The objective of the study is to analyze the relation between unemployment rate and real gross domestic product for the economy of United States of America. Okun s law describes this relation. According to this law, during recession periods, the unemployment rate has a stronger reaction to a certain variation in gross domestic product evolution. On the other hand, the unemployment rate keeps its value around natural level during economic upswings periods. 3.1 Database In the analysis of the relation between unemployment rate and economic growth in USA, annual data over the period is being used. The time series are: unemployment rate which is published by Bureau of Labor Statistics and economic growth. Real rate series are computed using real gross domestic product published by Bureau of Economic Analysis. Due to the fact that annual data is considered, it is not necessary to analyze the two series in terms of seasonality. Seasonal adjustment can only be applied on series with a frequency lower than one year: daily, weekly, monthly, quarterly data. Real gross domestic product is used in logarithm and is also checked for the existence of unit roots using Augmented Dickey Fuller (ADF) test and Kwiatkowski Phillips Schmidt Shin (KPSS) test. Figure 1 shows the relation between unemployment rate and real economic growth rate. There are recession periods when real economic growth rate decreases and unemployment rate increases. This evolution can be seen during , , and During some other periods, the relation between these variables is inverted, the real economic growth rate increases and unemployment rate decreases Unemployment rate Economic growth real rate Figure 1. The evolution of unemployment rate and economic growth real rate over the period Over the period and there are big differences between the values of the two time series that are analyzed. Blanchard and Summers (1986) concluded that unemployment rate was characterized by persistence, over the period , in USA. This means that economic growth didn t have so much influence on unemployment rate evolution. The financial crisis had a very important impact on the relation between these two variables. Because the USA economy started to decrease, the unemployment rate recorded an uptrend. This event could be seen in Figure 1 over the period
3 3.2 Stationarity analysis Figure 2. Descriptive statistic for Economic Growth Figure 3. Descriptive statistic for Unemployment Rate Figure 2 and Figure 3 show the descriptive statistic for both variables. The average recorded over the analyzed period for real economic growth rate is and it fluctuates between (the minimum value) and (the maximum value). The unemployment rate average is Standard deviation shows whether the series are volatile or not over this period of time. The real economic growth rate is more volatile than unemployment rate, even if the average of the two series is almost equal. The values recorded by Skewness coefficient, Kurtosis coefficient and Jarque-Bera probability show that real economic growth rate and unemployment rate are not normally distributed time series. For a normal distribution skewness coefficient is equal to zero and kurtosis coefficient is equal to three. It is important to see whether the influence of the real economic growth rate on unemployment rate evolution is significant or not. First of all, the presence of hysteresis in unemployment rate for USA is tested. This subject was investigated in several studies, for developed countries (Mitchell, 1993 or Brunello, 1990). In general, the results do not show the acceptance of the null hypothesis of a unit root for most of the European countries, but the results for the USA are mixed. Before verifying whether these time series are stationary or not, Hodrick-Prescott filter is used first, with the purpose of removing the trend from the series. It is important to mention that only real economic growth rate was de-trended. This is an expected result since there is no reason to expect a trend in the unemployment rate evolution. As mentioned before, it is not necessary to check for seasonal adjustment, because annual data are used. ADF test and KPSS test are applied afterwards. If according to ADF test, the investigated variable is not stationary and it is integrated of first order, the series need to be differentiated once in order to become stationary. The results obtained after ADF test is applied for real economic growth rate and for unemployment rate are shown in Figure 4 and Figure 5. The purpose of the analysis is to conclude whether there is a higher degree of hysteresis or persistence in unemployment time series. The null hypothesis of the ADF test characterizes the series as non-stationary or unit root process. This hypothesis is accepted if p-value associated to the statistic of the test is higher than five percent. If the test result indicates that we cannot reject the null of a unit root, the unemployment series is characterized by hysteresis, otherwise the series is characterized by persistence. 164
4 Figure 4. Stationary analysis with ADF test for Real Economic Growth Rate Figure 7. Stationary analysis with KPSS test for Unemployment Rate Due to the fact that unemployment rate series is not stationary, it can be said that hysteresis phenomenon is the process underlying the dynamics of unemployment in the USA. In other words, stabilization policy measures can have permanent effects on the unemployment rates for the USA. This aspect is very important for the interpretation of final results. Figure 5. Stationary analysis with ADF test for Unemployment Rate It can be seen that the probability computed by ADF test is smaller than five percent, therefore it can be concluded that economic growth is stationary. The ADF probability for unemployment rate is higher than five percent, but not too high. Therefore, it can be concluded that, at a significance level of five percent this series is not stationary. Same results are returned by KPSS test, as illustrated by Figure 6 and Figure 7. Figure 6. Stationary analysis with KPSS test for Real Economic Growth Rate 3.3 Okun s law testing The targets of macroeoconomic policy measures are economic growth and unemployment and inflation diminuation. As mentioned before, the relation between economic growth rate and unemployment rate is described by Okun s law. According to this law, during recession periods, the unemployment rate has a stronger reaction to a certain variation in gross domestic product evolution. On the other hand, the unemployment rate keeps its value around a natural level during economic upswings periods. Figure 8 shows the results obtained after analyzing the relation between real economic growth rate and unemployment rate. This relation is investigated by estimating a regression with a constant and one explanatory variable, which is the economic growth. The dependent variable is considered to be the unemployment rate. Several statistics and the associated probabilities are described, such as: t-statistic, R-squared, adjusted R-squared and F-statistic. 165
5 Figure 8. Okun s law If p-value for the independent variable included in the model is higher than five percent, the null hypothesis which says that the variable is not significant for the dependent variable evolution, should be accepted and therefore, it should be eliminated from the model. Otherwise, the null hypothesis is rejected and the independent variable is considered to have a significant impact for the evolution of the dependent one. The probability associated to t-statistic computed for the coefficient corresponding to the independent variable is equal to and it is smaller than the significance level of five percent, therefore the null hypothesis is accepted. According to it, this coefficient is significantly different than zero, so the evolution of the unemployment rate is influenced by the evolution of economic growth. If this coefficient is negative, it is suggested that the independent variable growth will determine a decrease of the dependent variable. The value recorded by this coefficient is It is negative, therefore it can be concluded that economic growth rate influences indirectly the unemployment rate evolution. It can be also seen that this regression was estimated with a constant. This constant should be kept in the model, because the probability associated to the t-statistic is 0.00 and it is smaller than the significance level of five percent. Therefore, there is no need to reestimate the model without this constant. R-Squared value shows the proportion of the dependent variable explained by the independent variable evolution. In order to accept that the model is a valid one and that the interpretation of R-Squared value makes sense for the analysis, the F-probability value should be smaller than five percent. R-Squared statistic for this model is equal to and the associated F-probability is We can conclude that the model is valid, so Okun s law is available in United States of America over the period The value of R-Squared statistic is not very high, which means that there are also other variables than economic growth that might explain the evolution of the unemployment rate. Same conclusion can be drown when interpreting Adjusted R-squared statistic. The difference between this statistic and R-squared is that the first one is computed by considering also the degrees of freedom. 4 Conclusions The result obtain after estimating the regression of the unemployment rate using real economic growth rate as explanatory variable, for United States of America economic, confirms the theoretical view expressed by Okun s law. The relative small value recorded by R-Squared shows that unemployment rate evolution might be also influenced, by other factors not included in this regression. Also, the results confirm the findings of other economic analysts regarding a high degree of hysteresis in the USA unemployment rate, which means that macroeconomic policy would have permanent effects or long term effects on this series. For further research, each USA state instead of the entire USA economy could be analyzed. Of course, a comparative analysis between USA economy and European Union economy could be also done. For a better understating of the evolution of unemployment rate, it is important to include in the model other factors that might have an impact, such as the financial crisis from The entire period investigated in the current 166
6 study could be split into two periods: before and after the crisis and the impact of the crisis could be emphasized. An analysis regarding the relation between unemployment rate and economic growth in Romania could be also done in order to highlight the specific features of the Romanian economy. References Blanchard, O. J. and Summers, L. H. (1986), Hysteresis and the European unemployment problem, Social Science Research Network: Brooks, C. (2002), Introductory econometrics for finance, Cambridge University Press. Gordon, R. J. (2004), Productivity, Growth, Inflation and Unemployment, Cambridge University Press. Leon-Ledsma, M. A. (2000), Unemployment hysteresis in the US and the EU: a panel data approach, Social Science Research Network: Knotek, E. S. (2007), How Useful Is Okun's Law, Economic Review, Federal Reserve Bank of Kansas City, Fourth Quarter 2007, : df. McBride, B. (2010), Real GDP Growth and the Unemployment Rate, Calculated Risk: Prachowny, M. F. J. (1993), Okun's Law: Theoretical Foundations and Revised Estimates, The Review of Economics and Statistics, vol. 75, no. 2, Song, F. M. and Wu, Y. (1997), Hysteresis in unemployment: evidence from 48 U.S. states, Economic Inquiry, vol. 35, Yazgan, M. E. and Yilmazkuday H. (2003), Okun s convergence within the US, Social Science Research Network: Authors description Iulia Roşoiu graduated the Faculty of Finance, Insurance, Banks and Stock Exchanges in 2009 and has just graduated Financial Management and Stock Exchange (DAFI) Master Program and Department of Teacher Training (second level) at the Academy of Economic Studies, Bucharest. The following are research interest: macroeconomics, monetary economics, financial econometrics. Andreea Roşoiu graduated the Faculty of Finance, Insurance, Banks and Stock Exchanges in 2009 and the Faculty of Cybernetics, Statistics and Informatics in She graduated Doctoral School of Finance and Banking Master Program in 2011 and she is currently a PhD student in the second year of Finance PhD Program at the Academy of Economic Studies, Bucharest. The following are research interest: macroeconomics, monetary economics, financial econometrics. 167
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