Has Automation Changed the Response of Unemployment Rate to GDP Growth?
School of Business
Debate over the effect of technology and automation on job creation or job destruction has been an ongoing debate in economics for some time. The recent developments in automation and the speed with which machine is replacing labor in some industries has worried many economists (Krugman, 2013, Graetz, G & G Michaels, 2015). While a number of recent studies present evidence on the negative effect of automation on employment by occupations (Oschinski M & R Wyonchi, 2017), none presents empirical evidence on the effect of automation on jobs at the macroeconomics level. This study utilizes the traditional model of the relationship between the real GDP growth and unemployment rate, estimated for US economy in 1962 and publicized as Okun’s Law. The relationship implies that a one percent increase in GDP growth above the normal growth of GDP results in .4 percent decrease in unemployment rate. Although the relationship between GDP growth and unemployment rate may be affected by other economic variables in the short-run, a variable that may result in structural change in this relationship in the long-run is technology and its effect on unemployment. Technological advancement may lead to substitution of capital for labor, resulting in less response of GDP growth to unemployment rate than what Okun’s law proposed. The main objective of this paper is to test whether such a structural change in the relationship has occurred or not. Using data for the last sixty years for eight industrialized countries, this paper compares the average response of unemployment rate to real GDP growth in three decades of 1955-1985, with the recent three decades of 1986-2015
Journal of Emerging Issues in Economics, Finance and Banking