Using the adoption of Zombie Property Laws (ZL) across several US states, we show that requiring lenders to maintain properties in the foreclosure process affects mortgage lending decisions and standards. Difference-in-differences estimations using a state border design show that ZL incentivizes lenders to screen mortgage applications more carefully: they deny more applications and impose higher interest rates on originated loans, especially risky loans. In turn, these loans exhibit higher ex post performance. ZL also affects lender behavior after borrowers become distressed, causing them to strategically keep delinquent mortgages alive. Our findings inform the debate on policy responses to foreclosure crises.

This paper provides theory and evidence on micro-level pricing behavior needed to model an aggregate New Keynesian Phillips Curve. We start with individual firms that are heterogeneous in their production technology and in the demand curves they face. We estimate the parameters of supply and demand curves by utilizing prices and quantities of outputs and factor inputs of firms along with exogenous downstream demand instruments from global input-output and trade data. The research addresses model heterogeneity using a clustering method to classify firms according to their production technology and observed price pass-through. The results show that more productive firms exhibit a lower price response to changes in demand. We find that the aggregate price response to demand shocks will be smaller when more productive firms absorb a larger portion of demand shocks, which generally is the case. At the same time, our results imply that idiosyncratic shifts in demand to clusters of firms with more rapidly rising marginal cost curves, or cost shocks to clusters of firms with high pass-through, will result in a higher aggregate price response. Finally, this paper provides a framework to incorporate heterogeneous pricing behavior into an estimate of the slope of the aggregate Phillips Curve.

We document a global reallocation of pollutive assets as a response to investor pressure: large firms facing increased investor pressure divest foreign-located pollutive assets to firms that are less in the limelight. There is no evidence of increased engagement in any other emission reduction activities. We estimate that 369 million metric tons (mt) of CO2e are reallocated via divestments in the post-Paris Agreement period. Our results indicate that investor pressure to decarbonize reshapes the global conglomerate structure of large firms.

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.

This study employs synthetic control methods to estimate the effect of the Iberian exception mechanism on wholesale electricity prices and consumer inflation, for both Spain and Portugal. We find that the intervention led to an average reduction of approximately 40% in the spot price of electricity between July 2022 and June 2023 in both Spain and Portugal. Regarding overall inflation, we observe notable differences between the two countries. In Spain, the intervention has an immediate effect, and results in an average decrease of 3.5 percentage points over the twelve months under consideration. In Portugal, however, the impact is small and generally close to zero. Different electricity market structures in each country are a plausible explanation.

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.

Syndicated loan data provided by DealScan is an essential input in banking research to answer urging questions on bank lending, e.g., in the presence of financial or geopolitical shocks or climate change. However, many data options raise the question of how to choose the estimation sample. We employ a standard regression framework analyzing bank lending during the financial crisis of 2007/08 to study how conventional but varying usages of DealScan affect the estimates. The key finding is that the direction of coefficients remains relatively robust. However, statistical significance depends on the data and sampling choice, and we provide guidelines for applied research.

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.

I estimate management opposition to unions in terms of hiring discrimination in the German labor market. By sending 13,000 fictitious job applications, revealing union membership in the CV and pro-union sentiment via social media accounts, I provide evidence for hiring discrimination against union supporters. Callback rates are on average 15% lower for union members. Discrimination is strongest in the presence of a high sectoral share of union members and large firm size. I further explore variation in regional and sectoral strike intensity over time and find suggestive evidence that discrimination increases if a sector is exposed to an intense strike. Discrimination is positively associated with the sectoral share of firms that voluntarily orientate wages to collective agreements. These results indicate that hiring discrimination can be explained by union threat effects.