The world price of oil is determined by the interactions of multiple producers and consumers who face different constraints and shocks. We show how this feature of the oil market can be used to estimate local and global elasticities of supply and demand and provide a rich set of testable restrictions. We develop a novel approach to estimation based on full-information maximum likelihood that generalizes the insights from granular instrumental variables. We conclude that the supply responses of Saudi Arabia and adjustments of inventories have historically played a key role in stabilizing the price of oil. We illustrate how our structural model can be used to analyze how individual producers and consumers would dynamically adapt to a geopolitical event such as a major disruption in the supply of oil from Russia.

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.

Climate change and inequality are critical and interrelated defining issues for this century. Despite growing empirical evidence on the economic incidence of climate policies and impacts, mainstream model-based assessments are often silent on the interplay between climate change and economic inequality. For example, all the major model comparisons reviewed in IPCC neglect within-country inequalities. Here we fill this gap by presenting a model ensemble of eight large-scale Integrated Assessment Models belonging to different model paradigms and featuring economic heterogeneity. We study the distributional implications of Paris-aligned climate target of 1.5 degree and include different carbon revenue redistribution schemes. Moreover, we account for the economic inequalities resulting from residual and avoided climate impacts. We find that price-based climate policies without compensatory measures increase economic inequality in most countries and across models. However, revenue redistribution through equal per-capita transfers can offset this effect, leading to on average decrease in the Gini index by almost two points. When climate benefits are included, inequality is further reduced, but only in the long term. Around mid-century, the combination of dried-up carbon revenues and yet limited climate benefits leads to higher inequality under the Paris target than in the Reference scenario, indicating the need for further policy measures in the medium term.

In statistics, samples are drawn from a population in a datagenerating process (DGP). Standard errors measure the uncertainty in sample estimates of population parameters. In science, evidence is generated to test hypotheses in an evidencegenerating process (EGP). We claim that EGP variation across researchers adds uncertainty: non-standard errors. To study them, we let 164 teams test six hypotheses on the same sample. We find that non-standard errors are sizeable, on par with standard errors. Their size (i) co-varies only weakly with team merits, reproducibility, or peer rating, (ii) declines significantly after peer-feedback, and (iii) is underestimated by participants.

This paper analyzes the effects of bank capital regulation on the link between bank size and volatility. Using bank-level data for 27 advanced economies over the 2000–2014 period, we estimate a power law that relates the volume of a bank’s loan portfolio to the volatility of loan growth. Our analysis reveals, first, that more stringent capital regulation weakens the size-volatility nexus. Hence, in countries with more stringent capital regulation, large banks show, ceteris paribus, lower loan portfolio volatility. Second, the effect of tighter capital requirements on the size-volatility nexus becomes stronger for the upper tail of the bank size distribution. This is in line with capitalization decreasing with bank size, such that larger banks tend to be more affected by increasing capital requirements. Third, in countries with higher sectoral capital buffers, the size-volatility nexus is weaker.

Competition in the U.S. appears to have declined. One contributing factor may have been heterogeneity in the availability of credit during the financial crisis. I examine the impact of product market peer credit constraints on long-run competitive outcomes and behavior among non-financial firms. I use measures of lender exposure to the financial crisis to create a plausibly exogenous instrument for product market credit availability. I find that credit constraints of product market peers positively predict growth in sales, market share, profitability, and markups. This is consistent with the notion that firms gained at the expense of their credit constrained peers. The relationship is robust to accounting for other sources of inter-firm spillovers, namely credit access of technology network and supply chain peers. Further, I find evidence of strategic investment, i.e. the idea that firms increase investment in response to peer credit constraints to commit to deter entry mobility. This behavior may explain why temporary heterogeneity in the availability of credit appears to have resulted in a persistent redistribution of output across firms.

We propose a novel mechanism through which established firms contribute to the startup ecosystem: the allocation of R&D tax credits to startups via the M&A channel. We show that when established firms become eligible for R&D tax credits, they increase their R&D and M&A activity. In particular, they acquire more venture capital (VC)-backed startups, but not non-VC-backed firms. Moreover, the impact of R&D tax credits on firms’ R&D is increasing with their acquisition of VC-backed startups. The results suggest that established firms respond to R&D tax credits by acquiring startups rather than solely focusing on increasing their R&D intensity in-house. We also highlight evidence that startups do not appear to benefit from R&D tax credits directly, perhaps because they typically lack the taxable income necessary to directly benefit from the tax credits. In this context, established firms can play an intermediary role by acquiring startups and reallocating R&D tax credits, effectively relaxing the financial constraints faced by startups.

Promoting green product consumption is one important element in building a sustainable society. Yet green products are usually more costly. In times of high inflation, not only budget constraints but also the fear that prices will continue to rise might dampen green product consumption and, hence, limit the effectiveness of exerted efforts to promote sustainable behaviors. To test this suggestion, we conducted a Germany-wide survey with almost 1,200 respondents, followed by a framed field experiment (N=500) to confirm causality. In the survey, respondents’ stated “green” purchasing behavior is, as to be expected, positively correlated with concerns about climate change. It is also negatively correlated with concerns about future inflation and energy costs, but after controlling for observable characteristics such as income and educational level only the correlation with concerns about future prices remains significant. This result is driven by individuals with below-median environmental attitude. In the framed field experiment, we use the priming method to manipulate the saliency of inflation concerns. Whereas sizably relaxing the budget constraint (i.e., by 50 percent) has no impact on the share of organic products in participants’ baskets, the priming significantly decreases the share of organic products for individuals with below-median environmental attitude, similar to the survey data.

Finanzmarktkrisen verursachen in der Regel hohe Kosten. Banken müssen stabilisiert werden, um einen Zusammenbruch des Bankensystems zu verhindern, was immense Kosten für den Staat bedeuten kann. Ebenso kommt es im Zuge von Finanzmarktkrisen zu einem starken Rückgang der wirtschaftlichen Aktivität, der im Vergleich zu gewöhnlichen Rezessionen länger anhält. Die Finanzmarktkrise hat dies ein weiteres Mal verdeutlicht und eine Phase der signifikanten Verschärfung der Regulierung und Aufsicht von Banken eingeleitet. Die Legislative hat das »Window of Opportunity« gut genutzt, und sowohl auf nationaler als auch auf europäischer Ebene wurden neue gesetzliche Grundlagen für eine stärkere Regulierung des Bankensystems erfolgreich eingeführt. Ein erster Erfolg des neuen regulatorischen Umfelds zeigte sich während der Corona-Pandemie, in der das Bankensystem stabil blieb. Dies wird auch durch die aktuell steigenden Eigenkapitalquoten und vergleichsweise niedrigen Ausfallraten im Kreditportfolio der Banken deutlich. Hervorzuheben ist außerdem, dass nicht nur auf nationaler Ebene Anstrengungen unternommen wurden, das regulatorische Umfeld für Banken zu verbessern, sondern dass es auch auf Ebene der Europäischen Union (EU) gelungen ist, mit dem »Single Rulebook« einen einheitlichen regulatorischen Rahmen zu schaffen. Dies wirkt Verschiebungen von Risiken innerhalb der EU entgegen. Trotz dieser Erfolge und positiven Entwicklungen darf nicht übersehen werden, dass sich durch staatliches Eingreifen und die Einführung neuer Regulierungsvorschriften nicht nur der betroffene Sektor, also die Banken, anpassen. Es kann auch zu Auswirkungen auf verschiedenste Akteure kommen, die direkt oder indirekt mit dem Bankensystem interagieren. Zudem kann es im Anpassungsprozess zu dynamischen Effekten kommen. Im Beitrag gehen wir auf zwei ausgewählte Aspekte ein, welche in diesem Zusammenhang von der Legislative zu beachten sind. 

Der Beitrag ist Teil des Artikels “Die Zukunft des europäischen Finanzsystems – zwischen Risiken und mangelnder Wettbewerbsfähigkeit?“, erschienen in: ifo Schnelldienst, 2024, 77, Nr. 07, 03-36.

We investigate whether lenders employ sustainability pricing provisions to manage borrowers’ environmental risk. Using unexpected negative environmental incidents of borrowers as exogenous shocks that reveal information on environmental risk, we find that lenders manage borrowers’ environmental risk by conventional tools such as imposing higher interest rates, utilizing financial and net worth covenants, showing reluctance to refinance, and demanding increased collateral. In contrast, the inclusion of sustainability pricing provisions in loan agreements for high environmental risk borrowers is reduced by 11 percentage points. Our study suggests that sustainability pricing provisions may not primarily serve as risk management tools but rather as instruments to attract demand from institutional investors and facilitate secondary market transactions.