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.

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.

There is growing evidence on the role of economic conditions in the recent successes of populist and extremist parties. However, little is known about the role of over-indebtedness, even though debtor distress has grown in Europe following the financial crisis. We study the unique case of the Czech Republic, where by 2017, nearly one in ten citizens had been served at least one debtor distress warrant even though the country consistently features low unemployment. Our municipality-level difference-in-differences analysis asks about the voting consequences of a rise in debtor distress following a 2001 deregulation of consumer-debt collection. We find that debtor distress has a positive effect on support for (new) extreme right and populist parties, but a negative effect on a (traditional) extreme-left party. The effects of debtor distress we uncover are robust to whether and how we control for economic hardship; the effects of debtor distress and economic hardship are of similar magnitude, but operate in opposing directions across the political spectrum.

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 use secondary corporate loan-market prices to construct a novel loan-market-based credit spread. This measure has considerable predictive power for economic activity across macroeconomic outcomes in both the U.S. and Europe and captures unique information not contained in public market credit spreads. Loan-market borrowers are compositionally different and particularly sensitive to supply-side frictions as well as financial frictions that emanate from their own balance sheets. This evidence highlights the joint role of financial intermediary and borrower balance-sheet frictions in understanding macroeconomic developments and enriches our understanding of which type of financial frictions matter for the economy.

Banks have been operating in a low interest rate environment paired with booming housing markets. For the largest banks in the euro area and the period 2015-2022, we assess whether banks reallocate their foreign loan portfolio backed by real estate as a response to differences in local lending spreads across the home and destination country and conditional on reduced information frictions due to borrowing-country exposures. The main result is that the relative share of foreign real estate backed lending increases in case of return opportunities, and this sensitivity depends on local exposures towards the borrowing country. The result is driven by subsamples for which neither the home nor the borrowing country have implemented macroprudential regulation targeting real estate lending, or for which there is a misalignment in macroprudential policies. Nevertheless, we find limited evidence that the riskiness of real estate backed loans goes up during our sample period, and we discuss potential reasons for this result including the possibility of hidden losses.

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.

Climate change and inequality are critical and interrelated issues. Despite growing empirical evidence on the distributional implications of climate policies and climate risks, mainstream model-based assessments are often silent on the interplay between climate change and economic inequality. Here we fill this gap through an ensemble of eight large-scale integrated assessment models that belong to different economic paradigms and feature income heterogeneity. We quantify the distributional implications of climate impacts and of the varying compensation schemes of climate policies compatible with the goals of the Paris Agreement. By 2100, climate impacts will increase inequality by 1.4 points of the Gini index on average. Maintaining global mean temperature below 1.5 °C reduces long-term inequality increase by two-thirds but increases it slightly in the short term. However, equal per-capita redistribution can offset the short-term effect, lowering the Gini index by almost two points. We quantify model uncertainty and find robust evidence that well-designed policies can help stabilize climate and promote economic inclusion.

Choosing a university and field of study is a key life decision that influences one’s lifelong earnings trajectory. Data shows that the share of individuals going to university is unequally distributed, and is lower among disadvantaged students. High-achieving students who are low income are less likely to opt for ambitious education paths, despite the high returns of education. Even among those students who decide to apply for college, the likelihood of whether they will apply to prestigious colleges or renowned study programs differs along the distribution of socioeconomic background. It does not only matter if you study, but also what and where you study, as there is a large variation in long-run outcomes, such as earnings, both between universities as well as between fields of study. Part of this mismatch can be attributed to unequal starting points for children, in terms of both institutional settings and the quality of information available within their close networks.

This paper provides a comprehensive analysis of the forecastability of the real price of natural gas in the United States at the monthly frequency considering a universe of models that differ in their complexity and economic content. Our key finding is that considerable reductions in mean-squared prediction error relative to a random walk benchmark can be achieved in real time for forecast horizons of up to two years. A particularly promising model is a six-variable Bayesian vector autoregressive model that includes the fundamental determinants of the supply and demand for natural gas. To capture real-time data constraints of these and other predictor variables, we assemble a rich database of historical vintages from multiple sources. We also compare our model-based forecasts to readily available model-free forecasts provided by experts and futures markets. Given that no single forecasting method dominates all others, we explore the usefulness of pooling forecasts and find that combining forecasts from individual models selected in real time based on their most recent performance delivers the most accurate forecasts.