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'Rust in peace': Why are Germany’s bridges and schools falling apart?Oliver HoltemöllerThe Guardian, June 3, 2025
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.
Is there a multicultural neighborhood price premium? We exploit plausibly exogenous variation in British colonization patterns in Northern Ireland during the early 1600s which created neighborhoods of varying religious composition that persists until today. These religious groups are culturally distinct, but are observationally equivalent ethnically and socioeconomically. A standard deviation increase neighborhood-level multiculturalism raises house prices by 9.6%. Multiculturalism raises property prices by increasing asset liquidity and housing demand as a wider spectrum of society demand houses in these areas. The findings and mechanism contrast sharply with prior evidence showing negative relationships due to homophily, social networks, and identification challenges.
Using the universe of high school and college admissions data in Croatia, we geocoded nearly half a million students’ residential addresses to investigate how their college and major choices are influenced by older neighbors and peers. Using an RDD to exploit time and program variation in admission cutoffs, we find that having an older neighbor who was admitted to and enrolled in a program increases a student’s probability of applying to the program by about 20%. We find that this effect consistently holds only for the closest neighbors, both in terms of distance and age difference. Female students are more likely to be influenced by older neighbors’ choices, and male older neighbors’ admission has a larger impact on both male and female students compared to female older neighbors. The effect is stronger if the student-neighbor pair lives in a region that does not have its own university, implying that the value of information in rural areas is higher. We find evidence that students don’t follow their older neighbors to less competitive programs; instead, they are more likely to apply for the same programs their older neighbors were admitted to when the program is more prestigious. Next, we utilize the variation in weight scheme of Croatia’s college study programs to show evidence, beyond college choices, of how older neighbors affect the human capital formation of their younger peers. The main channel through which we observe this effect is during high school, through specialization in the subjects needed to gain admittance to older neighbors’ college programs. These findings shed light on the intricate dynamics shaping educational decisions and underscores the significant role older neighbors play in guiding younger peers toward specific academic pathways.
How do beliefs on admission probability influence application choices? In this study, we empirically investigate whether and how admission probability is reflected in application choices in a centralized admission system. We exploit a novel setting of a dynamic deferred acceptance mechanism as employed in Croatia with hourly information updates and simultaneous application choices. This setting allows us to explore within-applicant strategic adjustments as a reaction to changing signals on admission probability. We show in an RDD analysis that applicants react to negative signals on admission probability with an increased propensity to adjust their application choices by 11-23%. Additionally, we show how application strategies evolve over time, while applicants learn about their admission probability. The group most-at-risk to remain unmatched improves their application choices by applying to programs with a higher admission probability towards the application deadline. Yet, we also identify a popular and potentially harmful strategy of applying to safer programs before applying to more risky “reach” programs. About a quarter of applicants have the potential to improve their application choices by resorting their application choices.
We investigate how global banks’ macroeconomic expectations for borrower countries influence their credit supply. Utilizing granular data on varying expectations among banks lending to the same firm at the same time, combined with an instrumental variable approach, we find that more optimistic GDP growth expectations for a borrower country are strongly linked to increased credit supply. Specifically, a one standard deviation increase in a lender’s GDP growth expectation for the borrower’s country corresponds to an increase of 8.46 percentage points in the loan share, equivalent to approximately 0.75 standard deviations of the loan share and $75.35 million in loan amount. In contrast, global banks’ short-term inflation expectations do not show a significant impact on their credit supply.
Institutional common ownership of firm pairs in the same industry increases the likelihood of a preexisting social connection among their CEOs. We establish this relationship using a quasi-natural experiment that exploits institutional mergers combined with firms’ hiring events and detailed information on CEO biographies. In addition, for peer firms, gaining a CEO connection from a hiring firm’s CEO appointment correlates with higher returns on assets, stock market returns, and decreasing product similarity between companies. We find evidence consistent with common owners allocating CEO connections to shape managerial decisionmaking and increase portfolio firms’ performance.
Accurate macroeconomic forecasts are essential for effective policy decisions, yet their precision depends on the accuracy of the underlying assumptions. This paper examines the extent to which assumption errors affect forecast accuracy, introducing the average squared assumption error (ASAE) as a valid instrument to address endogeneity. Using double/debiased machine learning (DML) techniques and partial linear instrumental variable (PLIV) models, we analyze GDP growth forecasts for Germany, conditioning on key exogenous variables such as oil price, exchange rate, and world trade. We find that traditional ordinary least squares (OLS) techniques systematically underestimate the influence of assumption errors, particularly with respect to world trade, while DML effectively mitigates endogeneity, reduces multicollinearity, and captures nonlinearities in the data. However, the effect of oil price assumption errors on GDP forecast errors remains ambiguous. These results underscore the importance of advanced econometric tools to improve the evaluation of macroeconomic forecasts.
Utilizing near real-time QuickBooks data from over 1.6 million small businesses and a targeted survey, this paper highlights the critical role credit card financing plays for small business activity. We examine a two year period beginning in January of 2021. A turbulent period during which, credit card usage by small U.S. businesses nearly doubled, interest payments rose by 60%, and delinquencies reached 2.8%. We find, first, monthly credit card payments were up to three times higher than loan payments during this time. Second, we use targeted surveys of these small businesses to establish credit cards as a key financing source in response to firm-level shocks, such as uncertain cash flows and overdue invoices. Third, we establish the importance of credit cards as an important financial transmission mechanism. Following the Federal Reserve’s rate hikes in early 2022, banks cut credit card supply, leading to a 15.75% drop in balances and a 10% decline in revenue growth, as well as a 1.5% decrease in employment growth among U.S. small businesses. These higher rates also rendered interest payments unsustainable for many, contributing to half of the observed increase in delinquencies. Lastly, a simple heterogeneous firm model with a cash-in-hand constraint illustrates the significant macroeconomic impact of credit card financing on small business activity.
We study whether and how EU banks comply with tighter macroprudential policy (MPP). Observing contractual details for more than one million securitized loans, we document an elusive risk-shifting response by EU banks in reaction to tighter loan-to-value (LTV) restrictions between 2009 and 2022. Our staggered difference-in-differences reveals that banks respond to these MPP measures at the portfolio level by issuing new loans after LTV shocks that are smaller, have shorter maturities, and show a higher collateral valuation while holding constant interest rates. Instead of contracting aggregate lending as intended by tighter MPP, banks increase the number and total volume of newly issued loans. Importantly, new loans finance especially properties in less liquid markets identified by a new European Real Estate Index (EREI), which we interpret as a novel, elusive form of risk-shifting.
This paper examines how firms’ exposure to supply chain disruptions (SCD) affects firm outcomes in the European Union (EU). Exploiting heterogeneous responses to workplace closures imposed by sourcing countries during the pandemic as a shock to SCD, we provide empirical evidence that firms in industries relying more heavily on foreign inputs experience a significant decline in sales compared to other firms. We document that external finance, particularly bank financing, plays a critical role in mitigating the effects of SCD. Furthermore, we highlight the unique importance of bank loans for small and solvent firms. Our findings also indicate that highly diversified firms and those sourcing inputs from less distant partners are less vulnerable to SCD.
