We study the interaction of expansionary rate-based monetary policy and quantitative easing, despite their concurrent implementation, by exploiting heterogeneous banks and the introduction of negative monetary-policy rates in a fragmented euro area. Quantitative easing increases credit supply less, translating into weaker employment growth, when banks’ funding costs do not decrease. Using administrative data from Germany, we uncover that among banks selling their securities, central-bank reserves remain disproportionately with high-deposit banks that are constrained due to sticky customer deposits at the zero lower bound. Affected German banks lend relatively less to firms while increasing their interbank exposure in the euro area.

We revisit the employer size wage effect (ESWE) – arguably the most basic and influential departure from the law of one price for labor. Our main result is that this canonical fact disappears completely across establishments within the same firm, even though they operate in different local labor markets. We uncover and dissect this fact by including a firm fixed effect in otherwise standard cross-sectional regressions of wages on establishment size. We implement this demanding specification in population-wide triple-linked firm-establishment-employee data in Germany. This result is new in the ESWE literature (for which our paper also provides the first systematic meta-analysis). This wage-size decoupling is hard to square with the view that employment is determined along a finitely elastic employerspecific labor supply curve – i.e., employers pay exactly the minimum needed for the quantity of labor, but no more – the foundation of the monopsony view. By contrast, large multi-establishment firms (MEF) appear to hire off their labor supply curves (or those curves are very elastic), pay wage premia above the monopsonistic minimum, and leave excess labor supply. We find some evidence for a reemergence of the ESWE within low-premium MEFs. Overall, at least for the 25% of German employment in large firms for which the ESWE disappears, wage setting and employment determination may be better accounted for by alternative models, namely accommodating above-market-clearing wage premia and rationing of labor supply, such as efficiency wage theories.

In this study, establishment-level employment effects of investment grants in Germany are estimated. In addition to the quantitative effects, I provide empirical evidence of funding effects on different aspects of employment quality (earnings, qualifications, and job security) for the period 2004 to 2020. The database combines project-level treatment data, establishment-level information on firm characteristics and employee structure, and regional information at the district level. For the estimations, I combine the difference-in-differences approach of Callaway and Sant’Anna (J Econom 2252: 200–230, 2021) with ties matching at the cohort level. The estimations yield positive effects on the number of employees, but point to contradicting effects of investment grants on different aspects of employment quality.

Many countries and regions remain below the level of economic activity of the world’s most advanced economies. Some countries form growth clubs, some are stuck in the middle-income trap, and some stay on a very low level of economic activity. Although this situation is well documented on the country level, there is less evidence at the sub-national level within countries. We estimate county-level capital stocks and price indices and provide a comprehensive county-level data set for Germany. We find no evidence of convergence across all counties even if we condition on important drivers of long-term growth such as physical and human capital accumulation. Instead, we identify five convergence clubs, using endogenous clustering. We analyze differences in growth paths and describe the identified clusters based on variations in contributions of capital, labor, and total factor productivity to economic growth. Additionally, we examine the role of migration for regional development and find that net migration has in particular contributed to growth in richer regions.

Spatial segregation of low- and high-wage workers is a persistent economic issue with broad social implications. Using social security data and an AKM wage decomposition, this paper examines spatial wage inequality in West Germany. Spatial inequality in log wages rose sharply between 1998 and 2008, mainly due to increased variance in worker pay premiums across regions (48%) and stronger positive spatial assortative matching of workers and establishments (40%), i.e. colocation. Changes in establishment wage premia are mostly unrelated to rising colocation whereas labor mobility even reduced it. Instead, growth in worker pay premiums among stayers was concentrated in regions where high-wage workers and high-wage establishments were overrepresented already in the 1990s and, thus, magnified pre-existing colocation leading to ‘colocation without relocation’. Germany’s rising trade surplus, especially with Eastern Europe, boosted stayers’ worker pay premiums in those ex-ante high-wage regions and fully explains rising colocation.

This study estimates the firm-level employment effects of investment grants in Germany. In addition to the average treatment effect on the treated, we examine discrimination in the funding rules as a potential source of effect heterogeneity. We combine a staggered difference-in-differences approach with a matching procedure at the cohort level. The findings reveal a positive effect of investment grants on employment development. The subsample analyses yield strong evidence for heterogeneous effects based on firm characteristics and the economic environment. They highlight the responsibility of the local funding authorities to clarify ex ante which goals of a funding programme are most important in their regions.

IFR statistics show that Germany has consistently been a global top 5 robotics market for many years. They also provide distribution by industry. But what it does not show is who exactly is installing these robots and what distinguishes a robot user from a non-user. Data collected from nearly 16,000 plants by the Institute for Employment Research (IAB) of the Federal Employment Agency helps us to learn more about robot users in Germany.

In this study, establishment-level employment effects of investment grants in Germany are estimated. In addition to the quantitative effects, I provide empirical evidence of funding effects on different aspects of employment quality (earnings, qualifications, and job security) for the period 2004 to 2020. The database combines project-level treatment data, establishment-level information on firm characteristics and employee structure, and regional information at the district-level. For the estimations, I combine the difference-in-differences approach of Callaway and Sant’Anna (2021) with ties matching at the cohort level. The estimations yield positive effects on the number of employees, but point to contradicting effects of investment grants on different aspects of employment quality.

Why are children with lower socioeconomic status (SES) substantially less likely to be enrolled in child care? We study whether barriers in the application process work against lower-SES children — the group known to benefit strongest from child care enrollment. In an RCT in Germany with highly subsidized child care (N = 607), we offer treated families information and personal assistance for applications. We find substantial, equity-enhancing effects of the treatment, closing half of the large SES gap in child care enrollment. Increased enrollment for lower-SES families is likely driven by altered application knowledge and behavior. We discuss scalability of our intervention and derive policy implications for the design of universal child care programs.

Accurate macroeconomic forecasts are essential for effective policy decisions, yet their precision depends on the accuracy of the underlying assumptions. This paper examines the extent to which assumption errors affect forecast accuracy, introducing the average squared assumption error (ASAE) as a valid instrument to address endogeneity. Using double/debiased machine learning (DML) techniques and partial linear instrumental variable (PLIV) models, we analyze GDP growth forecasts for Germany, conditioning on key exogenous variables such as oil price, exchange rate, and world trade. We find that traditional ordinary least squares (OLS) techniques systematically underestimate the influence of assumption errors, particularly with respect to world trade, while DML effectively mitigates endogeneity, reduces multicollinearity, and captures nonlinearities in the data. However, the effect of oil price assumption errors on GDP forecast errors remains ambiguous. These results underscore the importance of advanced econometric tools to improve the evaluation of macroeconomic forecasts.