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.

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.

Der Einsatz von Robotern verändert die Arbeitswelt grundlegend – doch welche spezifischen Effekte hat dies auf die Beschäftigungsstruktur? Unsere Analyse untersucht die Folgen des Robotereinsatzes anhand neuartiger Mikrodaten aus deutschen Industriebetrieben. Diese Daten verknüpfen Informationen zum Robotereinsatz mit Sozialversicherungsdaten und detaillierten Angaben zu Arbeitsaufgaben. Auf Basis eines theoretischen Modells leiten wir insbesondere positive Beschäftigungseffekte für Berufe mit wenig repetitiven, programmierbaren Aufgaben ab, sowie für jüngere Arbeitskräfte, weil diese sich besser an technologische Veränderungen anpassen können. Die empirische, mikroökonomische Analyse des Robotereinsatzes auf Betriebsebene bestätigt diese Vorhersagen: Die Beschäftigung steigt für Techniker, Ingenieure und Manager und junge Beschäftigte, während sie bei geringqualifizierten Routineberufen sowie bei Älteren stagniert. Zudem steigt die Fluktuation bei geringqualifizierten Arbeitskräften signifikant an. Unsere Ergebnisse verdeutlichen, dass der Verdrängungseffekt von Robotern berufsabhängig ist, während junge Arbeitskräfte neue Tätigkeiten übernehmen.

In Chapter 1, I combine longitudinal administrative firm-level data from Germany with 8,000 local tax changes for identification to show that local tax hikes (cuts) increase (decrease) the local manufacturing share. Firm-level results reveal that this is due to wage, employment, firm entry, and labor productivity in the service sector being more responsive to a tax shock than in manufacturing. With this evidence in mind, I calibrate a two-sector model with heterogeneous firms and profit tax to show that, owing to different structural parameters, a corporate tax cut disproportionately benefits service firms, contributing to the sectoral reallocation from manufacturing to service. In Chapter 2, we derive a European Herfindahl-Hirschman concentration index from 15 micro-aggregated country datasets. We show that European concentration rose due to a reallocation of economic activity towards large and concentrated industries. Over the same period, productivity gains from an increasing allocative efficiency of the European market accounted for 50% of European productivity growth while markups stayed constant. Using country-industry variation, we show that changes in concentration are positively associated with changes in productivity and allocative efficiency. This holds across most sectors and countries and supports the notion that rising concentration in Europe reflects a more efficient market environment rather than weak competition and rising market power. In chapter 3, We study the consequences of the Covid-19 pandemic and related policy support on productivity. We employ an extensive micro-distributed exercise to access otherwise unavailable individual data on firm performance and government subsidies. Our cross-country evidence for five EU countries shows that the pandemic led to a significant short-term decline in aggregate productivity and the direct support to firms had only a limited positive effect on productivity developments.

Firm training is widely regarded as crucial for protecting workers from automation, yet there is a lack of empirical evidence to support this belief. Using internationally harmonized data from over 90,000 workers across 37 industrialized countries, we construct an individual-level measure of automation risk based on tasks performed at work. Our analysis reveals substantial within-occupation variation in automation risk, overlooked by existing occupation-level measures. To assess whether firm training mitigates automation risk, we exploit within-occupation and within-industry variation. Additionally, we employ entropy balancing to re-weight workers without firm training based on a rich set of background characteristics, including tested numeracy skills as a proxy for unobserved ability. We find that training reduces workers’ automation risk by 3.8 percentage points, equivalent to 8% of the average automation risk. The training-induced reduction in automation risk accounts for 15% of the wage returns to firm training. Firm training is effective in reducing automation risk and increasing wages across nearly all countries, underscoring the external validity of our findings. Training is similarly effective across gender, age, and education groups, suggesting widely shared benefits rather than gains concentrated in specific demographic segments.