Why do cities differ so much in productivity? A long literature has sought out systematic sources, such as inherent productivity advantages, market access, agglomeration forces, or sorting. We document that up to three quarters of the measured regional productivity dispersion is spurious, reflecting the “luck of the draw” of finite counts of idiosyncratically heterogeneous plants that happen to operate in a given location. The patterns are even more pronounced for new plants, hold for alternative productivity measures, and broadly extend to European countries. This large role for individual plants suggests a smaller role for places in driving regional differences.

Using a newly collected dataset at the plant level from 2014 to 2018, we provide the first microscopic portrait of robotization in Germany and study the correlates of robot adoption. Our descriptive analysis uncovers five stylized facts: (1) Robot use is relatively rare. (2) The distribution of robots is highly skewed. (3) New robot adopters contribute substantially to the recent robotization. (4) Robot users are exceptional. (5) Heterogeneity in robot types matters. Our regression results further suggest plant size, high-skilled labor share, exporter status, and labor shortage to be strongly associated with the future probability of robot adoption.

We study how connections to German federal parliamentarians affect firm dynamics by constructing a novel dataset linking politicians and election candidates to the universe of firms. To identify the causal effect of access to political power, we exploit (i) new appointments to the company leadership team and (ii) discontinuities around the marginal seat of party election lists. Our results reveal that connections lead to reductions in firm exits, gradual increases in employment growth without improvements in productivity. Adding information on credit ratings, subsidies and procurement contracts allows us to distinguish between mechanisms driving the effects over the politician’s career. 

The substantial fluctuations in oil prices in the wake of the COVID-19 pandemic and the Russian invasion of Ukraine have highlighted the importance of tail events in the global market for crude oil which call for careful risk assessment. In this paper we focus on forecasting tail risks in the oil market by setting up a general empirical framework that allows for flexible predictive distributions of oil prices that can depart from normality. This model, based on Bayesian additive regression trees, remains agnostic on the functional form of the conditional mean relations and assumes that the shocks are driven by a stochastic volatility model. We show that our nonparametric approach improves in terms of tail forecasts upon three competing models: quantile regressions commonly used for studying tail events, the Bayesian VAR with stochastic volatility, and the simple random walk. We illustrate the practical relevance of our new approach by tracking the evolution of predictive densities during three recent economic and geopolitical crisis episodes, by developing consumer and producer distress indices that signal the build-up of upside and downside price risk, and by conducting a risk scenario analysis for 2024.

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.