The German government provides discretionary investment grants to structurally weak regions in order to reduce regional inequality. We use a regression discontinuity design that exploits an exogenous discrete jump in the probability of regional actors to receive investment grants to identify the causal effects of the policy. We find positive effects of the programme on district-level gross value-added and productivity growth, but no effects on employment and gross wage growth.

Public innovation subsidies in a regional environment are expected to unfold a positive economic impact over time. The focus of this paper is on an assessment of the long-run impact of innovation and innovation subsidies in German regions. This is scrutinized by an estimation approach combining panel model and time-series characteristics and using regional data for the years 1980–2014. The results show that innovation and innovation subsidies in the long run have a positive impact on the economic development of regions in Germany. This supports a long-term strategy for regional and innovation policy.

The existing empirical literature on the impact of vertical grants on local public-sector efficiency yields mixed results. Given the fact that vertical financial equalization systems often reduce differences in fiscal capacity, we argue that empirical studies based on cross-sectional data may yield a positive relationship between grants and efficiency of public service production even when the underlying causal effect is not. We provide a simple illustrative theoretical model to show the logic of our argument and illustrate its relevance by an empirical case study for the German state of Saxony-Anhalt. We show that our main argument of an inference-disturbing effect applies to those existing studies that are more optimistic about the impact of vertical grants. Finally, we argue that it may disturb the inference drawn from studies in a number of other countries where vertical grants—intended or not—concentrate in fiscally weak municipalities.

Interactive regional learning involving various actors is considered a precondition for successful innovations and, hence, for regional development. Diasporas as non-native ethnic groups are regarded as beneficial since they enrich the creative class by broadening the cultural base and introducing new routines. Using data on research and development (R&D) collaboration projects, the analysis provides tentative evidence that the size of diasporas positively affects the region’s share of outward R&D linkages enabling the exchange of knowledge. The empirical analysis further confirms that these interactions mainly occur between regions hosting the same diasporas, pointing to a positive effect of ethnic proximity rather than ethnic diversity.

In this paper, we investigate the impact of regional and technological innovation systems on innovation cooperation. We develop an indicator applicable to regions, which demonstrates the relative regional impact on innovation cooperation. Applying this method to German patent data, we find that regional differences in the degree of innovation cooperation do not only depend on the technology structure of a region but also on specific regional effects. High-tech oriented regions, whether east or west, are not automatically highly cooperative regions. East German regions have experienced a dynamic development of innovation cooperation since re-unification in 1990. Their cooperation intensity remains higher than in West German regions.

We study the wage and employment effects of a German place-based policy using a research design that exploits conditionally exogenous EU-wide rules governing the program parameters at the regional level. The place-based program subsidizes investments to create jobs with a subsidy rate that varies across labor market regions. The analysis uses matched data on the universe of establishments and their employees, establishment-level panel data on program participation, and regional scores that generate spatial discontinuities in program eligibility and generosity. These rich data enable us to study the incidence of the place-based program on different groups of individuals. We find that the program helps establishments create jobs that disproportionately benefit younger and less-educated workers. Funded establishments increase their wages but, unlike employment, wage gains do not persist in the long run. Employment effects estimated at the local area level are slightly larger than establishment-level estimates, suggesting limited spillover effects. Using subsidy rates as an instrumental variable for actual subsidies indicates that it costs approximately EUR 25,000 to create a new job in the economically disadvantaged areas targeted by the program.

This study estimates the establishment-level employment effects of investment grants in Germany. In addition to the average treatment effect for the treated, we focus on discrimination in the funding rules as potential source of effect heterogeneity. We combine the difference-in-differences approach of Callaway and Sant’Anna (2021) that explicitly models variation in treatment timing with a ties matching at the cohort level. We observe a positive effect of investment grants on employment development in the full sample. The subsample analysis yields strong evidence for effect heterogeneity due to firm characteristics and the economic environment.

The paper presents a modification of the matching and difference-in-differences approach of Heckman et al. (1998) for the staggered treatment adoption design and a Stata tool that implements the approach. This flexible conditional difference-in-differences approach is particularly useful for causal analysis of treatments with varying start dates and varying treatment durations. Introducing more flexibility enables the user to consider individual treatment periods for the treated observations and thus circumventing problems arising in canonical difference-in-differences approaches. The open-source flexpaneldid toolbox for Stata implements the developed approach and allows comprehensive robustness checks and quality tests. The core of the paper gives comprehensive examples to explain the use of the commands and its options on the basis of a publicly accessible data set.

The paper estimates the plant level employment effects of investment subsidies in one of the most strongly subsidized German Federal States. We analyze the treated plants as a whole, as well as the influence of heterogeneity in plant characteristics and the economic environment. Modifying the standard matching and difference-in-difference approach, we develop a new procedure that is particularly useful for the evaluation of funding programs with individual treatment phases within the funding period. Our data base combines treatment, employment and regional information from different sources. So, we can relate the absolute effects to the amount of the subsidy paid. The results suggest that investment subsidies have a positive influence on the employment development in absolute and standardized figures – with considerable effect heterogeneity.

The German government provides discretionary investment grants to structurally weak regions to reduce regional disparities. We use a regression discontinuity design that exploits an exogenous discrete jump in the probability of receiving investment grants to identify the causal effects of the investment grant on regional outcomes. We find positive effects for regional gross value-added and productivity growth, but no effects for employment and gross wage growth.