The Effect of Information Technology on the Unemployment Rate: Evidence From the United States Economy

This study contributes to the literature by providing an empirical analysis on the impact of information technology on the U.S. unemployment rate using macroeconomic data level. It develops a theoretical framework and uses three complementary econometric methods: Traditional ARDL, Dynamic ARDL, and the Frequency Domain Causality Test, to ensure robustness and reliability of the findings over the period 1990: Q1 to 2020: Q1. The results show that information technology and economic growth have a statistically significant negative effect on unemployment in both the short and long run, suggesting that information technology generally contributes to job creation or reduction in joblessness. However, this study also finds that the interaction between information technology and economic growth has a positive and significant effect on unemployment rate, implying that information technology may still displace certain job types, even during periods of economic expansion. These findings align with prior survey-based studies, reinforcing the dual nature of technological progress: while it drives productivity and growth, it can also lead to structural job shifts or losses in specific sectors. From a policy perspective, this study emphasizes the importance of strategic planning and workforce adaptation to fully join the benefits of innovation without exacerbating unemployment. Simultaneously, policymakers can mitigate the adverse effects of information technology by focusing on a national strategy for workforce reskilling and strengthen unemployment insurance. JEL Classification: C22, D83, O33, O47.