Economic growth and unemployment dynamics in the United States: An empirical assessment of Okun’s Law

Abstract

This study examines the relationship between economic growth and unemployment in the United States by empirically reassessing Okun’s Law. Using quarterly data spanning several decades, the analysis examines whether the traditional inverse relationship between output growth and unemployment remains stable amid structural and cyclical changes. The study employs a range of econometric techniques, including baseline regression models, cointegration analysis, error correction modeling, vector autoregression, and structural break tests, to capture both short-run dynamics and long-run equilibrium relationships. The findings confirm a negative relationship between real GDP growth and changes in unemployment, consistent with Arthur Okun's original formulation. However, the results also reveal that the magnitude of this relationship is not constant over time. Evidence of structural breaks and subsample variation indicates that the responsiveness of unemployment to economic growth has weakened in recent decades, particularly following major economic disruptions. Additionally, the analysis identifies asymmetric adjustment patterns, with unemployment responding more strongly during economic downturns than during expansions. These results suggest that Okun’s Law should be interpreted as a time-varying and context-dependent relationship rather than a fixed empirical rule. The study contributes to the literature by incorporating up-to-date data and employing flexible econometric frameworks that capture evolving macroeconomic dynamics. The findings carry important implications for policy design and forecasting, underscoring the need for adaptive models that account for structural changes in the labor market.