Medienanfragen richten Sie bitte an:
Telefon: +49 345 7753-720
Email: presse@iwh-halle.de
Team Kommunikation
Gottvertrauen? Kirchenzugehörigkeit kann Wiederaufbau nach Naturkatastrophen verbessernFelix NothMitteldeutscher Rundfunk, 20. August 2025
The establishment of the European Banking Union constitutes a major change in the regulatory framework of the banking system. Main parts are implemented via directives that show staggered transposition timing across EU member states. Based on the newly compiled Banking Union Directives Database, we assess how banks’ funding costs responded to the Capital Requirements Directive IV (CRD IV). Our findings show an upward trend in funding costs which is driven by an increase in cost of equity and partially offset by a decline in cost of debt. The diverging trends are most present in countries with an ex-ante lower regulatory capital stringency, which is in line with banks’ short-run adjustment needs but longer-run benefits from increased financial stability.
We study the corporate-loan pricing decisions of a major, systemic bank during the Greek financial crisis. A unique aspect of our data set is that we observe both the actual interest rate and the “break-even rate” (BE rate) of each loan, as computed by the bank’s own loan-pricing department (in effect, the loan’s marginal cost). We document that low-BE-rate (safer) borrowers are charged significant markups, whereas high-BE-rate (riskier) borrowers are charged smaller and even negative markups. We rationalize this de facto cross-subsidization through the lens of a dynamic model featuring depressed collateral values, impaired capital-market access, and limit pricing.
We use data from the Annual Survey of Manufactures to study the characteristics and geographic distribution of investments in robots across US manufacturing establishments. Robotics adoption and robot intensity (the number of robots per employee) cluster in "robot hubs." Establishments that report having robotics are larger and have a larger production worker share, lower pay per worker, lower labor share, and higher capital expenditures, including higher IT capital expenditures. Notably, establishments are more likely to have robots if other establishments in the same core-based statistical area and industry also report having robotics, suggestive of agglomeration and peer effects.
The European Commission’s growth forecasts play a crucial role in shaping policies and provide a benchmark for many (national) forecasters. The annual forecasts are built on quarterly estimates, which do not receive much attention and are hardly known. Therefore, this paper provides a comprehensive analysis of multi-period ahead quarterly GDP growth forecasts for the European Union (EU), euro area, and several EU member states with respect to first-release and current-release data. Forecast revisions and forecast errors are analyzed, and the results show that the forecasts are not systematically biased. However, GDP forecasts for several member states tend to be overestimated at short-time horizons. Furthermore, the final forecast revision in the current quarter is generally downward biased for almost all countries. Overall, the differences in mean forecast errors are minor when using real-time data or pseudo-real-time data and these differences do not significantly impact the overall assessment of the forecasts’ quality. Additionally, the forecast performance varies across countries, with smaller countries and Central and Eastern European countries (CEECs) experiencing larger forecast errors. The paper provides evidence that there is still potential for improvement in forecasting techniques both for nowcasts but also forecasts up to eight quarters ahead. In the latter case, the performance of the mean forecast tends to be superior for many countries.
We investigate how a state's political corruption affects a resident firm's debt contracting and how a change in anti-corruption regulation alters the relation between corruption and loan contracting. Firms in more corrupt states are associated with significantly higher loan spreads and tighter loan covenants than firms in less corrupt states. Furthermore, the passage of the Dodd–Frank whistleblowing provision amplifies the conhcerns of banks about the detrimental impact of corruption due to the increased exposure of firms to whistleblowing threats. The detrimental impact of corruption is further amplified when a state has a higher level of whistleblowing involvement, when firms are located in more corrupt states or closer to the SEC office, and when the bank's state is less corrupt than the firm's state. In general, we document the externality of corruption in the debt financing of firms and the response of banks to changes in regulation.
Wage mobility reduces the persistence of wage inequality. We develop a framework to quantify the contribution of employer-to-employer movers to aggregate wage mobility. Using three decades of German social security data, we find that inequality increased while aggregate wage mobility decreased. Employer-to-employer movers exhibit higher wage mobility, mainly due to changes in employer wage premia at job change. The massive structural changes following German unification temporarily led to a high number of movers, which in turn boosted aggregate wage mobility. Wage mobility is much lower at the bottom of the wage distribution, and the decline in aggregate wage mobility since the 1980s is concentrated there. The overall decline can be mostly attributed to a reduction in wage mobility per mover, which is due to a compositional shift toward lower-wage movers.
In this paper, we study champions of corporate social responsibility (CSR) performance among the U.S. publicly traded firms and their common characteristics by utilizing machine learning algorithms to identify predictors of firms’ CSR activity. We contribute to the CSR and leadership determinants literature by introducing the first comprehensive framework for analyzing the factors associated with corporate engagement with socially responsible behaviors by grouping all relevant predictors into four broad categories: corporate governance, managerial incentives, leadership, and firm characteristics. We find that strong corporate governance characteristics, as manifested in board member heterogeneity and managerial incentives, are the top predictors of CSR performance. Our results suggest policy implications for providing incentives and fostering characteristics conducive to firms “doing good.”
Mutual fund families increasingly hold bonds and stocks from the same firm. We present evidence that dual ownership allows firms to increase valuable investments and refinance by issuing bonds with lower yields and fewer restrictive covenants, especially when firms face financial distress. Dual holders also prevent overinvestment by firms with entrenched managers. Overall, our results suggest that mutual fund families internalize the agency conflicts of their portfolio companies, highlighting the positive governance externalities of intra-family cooperation.
The Roy-Borjas model predicts that international migrants are less educated than nonmigrants because the returns to education are generally higher in developing (migrant-sending) than in developed (migrant-receiving) countries. However, empirical evidence often shows the opposite. Using the case of Mexico-U.S. migration, we show that this inconsistency between predictions and empirical evidence can be resolved when the human capital of migrants is assessed using a two-dimensional measure of occupational skills rather than by educational attainment. Thus, focusing on a single skill dimension when investigating migrant selection can lead to misleading conclusions about the underlying economic incentives and behavioral models of migration.
We investigate the predictive power of loan spreads for forecasting business cycles, specifically focusing on more constrained, intermediary-reliant firms. We introduce a novel loan-market-based credit spread constructed using secondary corporate loan-market prices over the 1999 to 2023 period. Loan spreads significantly enhance the prediction of macroeconomic outcomes, outperforming other credit-spread indicators. We also explore the underlying mechanisms and differentiate between borrower fundamentals and financial frictions. Evidence suggests that supply-side frictions are a decisive factor in the forecasting ability of loan spreads.