Many wonder whether teacher gender plays an important role in higher education by influencing student achievement and subject interest. The data used in this paper help identify average effects from male and female college students assigned to male or female teachers. We find instructor gender plays only a minor role in determining college student achievement. Nevertheless, the small effects provide evidence that gender role models matter to some college students. A same-sex instructor increases average grade performance by at most 5 percent of its standard deviation and decreases the likelihood of dropping a class by 1.2 percentage points.

In jeder arbeitsteiligen Gesellschaft ist Wirtschaftspolitik erforderlich. Im Rahmen der Wirtschaftspolitik wird versucht, ein komplexes Geflecht von Zielen zu erreichen. Es kann auch vorkommen, dass mit dem Erreichen eines Ziels ein anderes geschwächt wird. Dies ist Gegenstand des vorliegenden Beitrags. Konkret geht es um das Ziel Verbesserung der Wirtschaftsstruktur und das Umweltziel. Das Strukturziel wird in der Bundesrepublik Deutschland unter anderem über die Investitionszuschüsse im Rahmen der Gemeinschaftsaufgabe ‚Verbesserung der regionalen Wirtschaftsstruktur‘ verfolgt, die über die Länder ausgereicht werden. Einige Länder sind dazu übergegangen, die Gewährung von Investitionszuschüssen an Sekundärziele, zum Beispiel auch den Umweltschutz, zu knüpfen. Der vorliegende Beitrag beschreibt einen aktuellen Fall aus dem politischen Diskussionsprozess, in dem die Höhe des Fördersatzes an die Einführung von so genannten Umweltmanagementsystemen gebunden wird. Der Beitrag zeigt, dass unter bestimmten Konstellationen die Investitionstätigkeit gebremst wird und gleichzeitig Umweltmanagementsysteme nicht eingeführt werden. Damit hätte man beide Ziele nicht erreicht. Der bessere Weg bestünde in der direkten Unterstützung von Unternehmen, bei denen ein Umweltmanagementsystem sinnvoll ist, wie es bereits durch Programme auf Landesebene praktiziert wird.

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.

This study provides new evidence on the impact of the EU Cohesion Policy on income growth in less developed regions. Our panel includes data from all European regions for the years 1989-2020. Using a fuzzy Regression Discontinuity Design, we model treatment dynamics by applying a random effects estimator. Based on digitized historical data, we precisely replicate the policy rule and correctly classify the regions’ eligibility status. Results show that the policy has a moderate positive effect on GDP per capita growth in the targeted regions.

This paper documents substantial fiscal waste in the context of one the world’s largest regional development programs – the EU Cohesion Policy. We study Italy, and find that 20% of funding commitments are never paid out and funneled into unfinished or never-started projects. In our setting, this happens for reasons unrelated to fiscal constraints – municipalities appear to simply leave money on the table. Foregone spending is more prevalent in Southern regions, but there is also stark variation across municipalities within regions. We show that such under-utilization of available funds is strongly associated with limited administrative capacity of local governments.

We study the effects of place-based policies on aggregate productivity using administrative data on projects co-financed by the EU in Italy linked to balance sheet data. We exploit quasi-experimental variation in funding for a large place-based policy stemming from measurement error in regional GDP estimates. Results show that the policy likely decreases productivity. Decompositions reveal that aggregate declines are driven by reallocation of labor to low-productivity firms. Mechanism analysis using firm-level event studies reveals that negative reallocation effects are caused by high-productivity firms taking up the funds and subsequently becoming more liquidity constrained, leading to slowdowns in employment growth.

We study the granular wage and employment effects of a German place-based policy using a research design that leverages conditionally exogenous EU-wide rules governing 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. Spatial spillovers of the program linked to changing commuting patterns can be assessed using information on place of work and place of residence, a unique feature of the data. 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 economic spillover effects. On the other hand, spatial spillovers are large as over half of the employment increase comes from commuters. 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.

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.