Automation, robots and wage inequality in Germany: A decomposition analysis - Franziska Brall; Ramona Schmid (Universität Hohenheim, Fakultät Wirtschafts- und Sozialwissenschaften, 2020)
We analyze how and through which channels wage inequality is affected by the rise in automation and robotization in the manufacturing sector in Germany from 1996 to 2017. Combining rich linked employer-employee data accounting for a variety of different individual, firm and industry characteristics with data on industrial robots and automation probabilities of occupations, we are able to disentangle different potential causes behind changes in wage inequality in Germany. We apply the recentered influence function (RIF) regression based Oaxaca-Blinder (OB) decomposition on several inequality indices and find evidence that besides personal characteristics like age and education the rise in automation and robotization contributes significantly to wage inequality in Germany. Structural shifts in the workforce composition towards occupations with lower or medium automation threat lead to higher wage inequality, which is observable over the whole considered time period. The effect of automation on the wage structure results in higher inequality in the 1990s and 2000s, while it has a significant decreasing inequality effect for the upper part of the wage distribution in the more recent time period.
urn:nbn:de:bsz:100-opus-18163
Keywords: J31; C21; D63; O30; 330; Wage Inequality; Automation; Robots; Decomposition Method; RIFregression; Linked employer - employee data; Germany