Estimating the liaison between Unemployment and GDP beyond the Mean of the Distribution
Abstract
Okun law postulates a negative relationship between the movements of unemployment rate and the real gross domestic product. This study applied Quantile regression analysis to estimate the relationship between unemployment and its predictor GDP, and compared the results to parameter estimates using OLS regression. Conditional mean has been used as a solution to minimize the error variance. Time series annual data has been used from period 1973 to 2010. Predictor of unemployment used was GDP. Empirical Results of quantile regression analysis showed that for GDP parameter estimates were significant only for certain quantiles. Parameters for GDP were significant only for 5%, 10%, 95%. The GDP parameter had non- significant on OLS but not on all quantile from quantile regression.References
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