This paper analyzes the importance of teacher quality at the college level. Instructors are matched to objective and subjective characteristics of teacher quality to estimate the impact of rank, salary, and perceived effectiveness on student performance and subject interest. Student and course fixed effects, time of day and week controls, and students' lack of knowledge about first-year instructors help minimize selection biases. Subjective teacher evaluations perform well in measuring instructor influences on students, while objective characteristics such as rank and salary do not. Overall, the importance of college instructor differences is small, but important outliers exist.

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.

<p>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 potential source of effect heterogeneity. We combine a staggered difference-in-differences approach that explicitly models variations in treatment timing with a matching procedure at the cohort level. The findings reveal a positive effect of investment grants on employment development in the full sample. The subsample analysis yields strong evidence for heterogeneous effects based on firm characteristics and the economic environment. This can help to improve the future design of the program.</p>

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.