Browsing by Subject "Decomposition method"

Now showing 1 - 2 of 2

Automation, robots and wage inequality in Germany : a decomposition analysis
(2020) Schmid, Ramona; Brall, Franziska
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.
Three essays on wage inequality in Germany : the impact of automation, migration and the minimum wage
(2023) Schmid, Ramona Elisabeth; Beißinger, Thomas
Economic inequality has increased in the majority of countries worldwide over the last three decades and is highly present in public discussion, political debate and scientific research. Due to the large number and complexity of driving forces behind changes in wage inequality, this cumulative dissertation focuses on three challenges of the German labour market. The first paper addresses the question to which extent automation and robotization impact wage inequality in the manufacturing sector in Germany between 1996 and 2017. Applying decomposition analyses along the entire wage distribution, driving factors behind changes in wage inequality are identified. On the basis of administrative data and a new introduced measure of automation threat, which combines occupation- and requirement-specific scores of automation risk with yearly sector-specific robot densities, the study provides new evidence to existing literature. Besides the traditional factors education and age, the detailed decomposition analysis provides evidence that automation threat contributes significantly to rising wage inequality. On the one hand, changes in the composition of the workforce that is exposed to automation and robotization led to significant increases in wage inequality in the German manufacturing sector during the last two decades. On the other hand, evidence of a growing wage dispersion between occupations with low automation threat (especially associated with non-routine tasks) and occupations with high automation threat (especially associated with routine tasks) is revealed. This trend contributes to rising wage inequality as predicted by routine-biased technological change. The second research study presents new evidence on immigrant-native wage differentials in consideration of regional differences between metropolitan and non-metropolitan areas between 2000 and 2019 in Germany. Since gaps in remuneration provide information on the effectiveness of immigration and labour market policies as well as identify the degree of economic integration of foreign workers, the analysis is currently of great importance. Using administrative data, aggregate decomposition results support the hypothesis that the majority of wage differentials can be explained by differences in observed characteristics. However, overall wage differentials at the median exhibit an increasing trend, and on average higher gaps in remuneration are revealed in urban areas. Detailed decomposition analyses show that the effects of explanatory factors not only change over time but the sources of gaps also vary along the wage distribution. Decisive explanatory variables in this context are the practised profession, the economic sector affiliation and labour market experience. Distinguishing between metropolitan and non-metropolitan areas provides evidence that especially differences in educational attainment impact immigrant-native wage gaps in urban areas. The third paper evaluates the effects of the introduced national minimum wage in 2015 on the gender wage gap in Germany. Being confronted with a low-wage sector of considerable extent and comparably high wage differentials between men and women, this study on Germany provides necessary new insights in this area of research. On the basis of administrative data and counterfactual difference-in-differences analyses significant decreases of wage gaps between men and women that can be traced back to the introduced statutory wage floor are revealed. Especially at the lowest observed wage level and in the East of Germany the highest decreases are observable. The analysis, differentiated by educational level, age and occupational activity, provides detailed information on the effectiveness of the wage floor for different target groups. In particular, at lower wage levels for the least educated and middle aged workers the introduction of the minimum wage is the driving factor that significantly lowers group-specific gender wage gaps. Counterfactual decomposition analyses finally provide first evidence that in the West of Germany possible discrimination against women at the lowest wages is restricted by the wage floor.