Browsing by Person "Brall, Franziska"

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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.
Technical change, task allocation, and labor unions
(2022) Marczak, Martyna; Beißinger, Thomas; Brall, Franziska
We propose a novel framework that integrates the task approach" for a more precise production modeling into the search-and-matching model with low- and high-skilled workers, and wage setting by labor unions. We establish the relationship between task reallocation and changes in wage pressure, and examine how skill- biased technical change (SBTC) affects the task composition, wages of both skill groups, and unemployment. In contrast to the canonical model with a fixed task allocation, low-skilled workers may be harmed in terms of either lower wages or higher unemployment depending on the relative task-related productivity profile of both worker types. We calibrate the model to the US and German data for the periods 1995-2005 and 2010-2017. The simulated effects of SBTC on low-skilled unemployment are largely consistent with observed developments. For example, US low-skilled unemployment increases due to SBTC in the earlier period and decreases after 2010.
Three essays on the labor market effects of technological change and unemployment benefits
(2023) Brall, Franziska; Beißinger, Thomas
The dissertation essentially contributes to the discourse on how technological change and a reduction in unemployment benefits affect the labor market. The thesis incorporates an empirical analysis of the influence of automation technologies on wage inequality in Germany. Additionally, the dissertation introduces a novel general equilibrium model to analyze the impact of technological change on the wage setting behavior of labor unions and reevaluate the labor market effects of a cut in unemployment benefits. The first essay contributes to the existing literature in examining the relative importance of automation technologies on wage inequality in the German manufacturing sector between 1996 and 2017. The analysis introduces a novel measure of automation threat, combining occupation- and requirement-specific scores of automation risk with sector-specific robot densities. Using the RIF-based Oaxaca–Blinder decomposition method, the analysis demonstrates that automation threat significantly contributes to wage inequality, in addition to the commonly used demographic factors. On the one hand, there is an observable trend towards occupations with medium automation threat, accompanied by decreasing shares of occupations with high and low automation threat. Due to the fact that within-group wage inequality is the lowest in the group with the highest automation threat, those compositional changes contribute to increasing wage inequality. On the other hand, an increasing wage dispersion between occupations with low automation threat (containing especially non-routine tasks) and occupations with high automation threat (containing especially routine tasks) contributes to rising wage inequality. This is in line with the predictions of routine-biased technical change, where technology particularly substitutes routine tasks. The second essay develops a novel modeling framework for the analysis of skill-biased technical change (SBTC), combining the task approach, wage setting by labor unions, as well as search and matching frictions. The important insight from this analysis is that changes in the firm’s assignment of tasks to low- and high-skilled workers have an impact on the wage setting power of labor unions. The effect of such a change in the task allocation on the labor demand elasticity, and consequently on the labor union’s wage markup, is ambiguous. This has consequences for the effects of SBTC. Unlike the conventional result that SBTC has a positive impact on employment and wages of low-skilled workers, the task-based matching model presents the possibility that low-skilled workers may instead experience either higher unemployment or lower real wages. The model is calibrated to German and French data for the periods 1995-2005 and 2010-2017 to illustrate that the impact of SBTC may even change its sign over time. The results depend on the shape of the task productivity schedule, which reflects the substitutability of high-and low-skilled workers. The third essay revisits the labor market effects of a reduction in unemployment benefits using a modified version of the previously developed task-based matching model. The analysis demonstrates that a cut in low-skilled unemployment benefits triggers a reallocation of tasks towards low-skilled workers. This leads to additional effects on labor market outcomes that are disregarded in the prevailing literature. To highlight the importance of endogenous task allocation, the task-based matching model with exogenous and constant task allocation is considered. Both model variants are calibrated to analyze the effects of the Hartz IV reform in Germany, which involved a substantial cut in unemployment benefits. The calibration reveals a remarkable decrease in the low-skilled unemployment rate by 4 percentage points resulting from Hartz IV. In the case of exogenous and constant task allocation, the decline is limited to 3.4 percentage points, but there are stronger effects on low- and high skilled wages, causing wage inequality to rise more sharply. The results emphasize the importance of considering endogenous task allocation in the evaluation of labor market reforms.