Revisiting Output Employment Relationship in Pakistan: An Empirical Investigation of Okun’s Law Using Rolling Regression

Abstract

Economists have proven the negative relationship between GDP growth in the economy and the unemployment rate changes over time. This study uses the empirical application of Okun’s Law using time varying coefficients to test the relationship between economic growth and rate of unemployment over time. The study used time series data for the period from 1991 to 2023 from Pakistan, which was sourced from World Bank. In empirical analysis, the augmented dickey fuller test is employed to assess the unit root of the variables. Based on unit root results, Autoregressive Distributed Lag (ARDL) bounds testing approach followed by Error Correction Model (ECM) utilized to investigate short term and long-term significance of Okun’s law in Pakistan. The Okun’s law with time varying effects are estimated using the rolling regression approach. The ECM results demonstrates that there is a significant and negative relationship between GDP growth and unemployment in Pakistan in the long run, but the time varying coefficients reveals that Okun’s Law is not consistent over the analysis period. This work contributing to the corpus of knowledge in Pakistan by estimating Okun’s law using rolling regression. According to the study’s results, the Okun’s law in Pakistan is not stable over the study period. There is a need to develop employment generating policies other than only focusing to economic growth. The policy intuitions can consider FDI, Trade Openness, and financial development as key indicators for reducing unemployment in Pakistan.