Risky Oil: It's All in the Tails
Christiane Baumeister, Florian Huber, Massimiliano Marcellino
NBER Working Paper,
Nr. 32524,
2024
Abstract
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.
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Voting under Debtor Distress
Jakub Grossmann, Štěpán Jurajda
CERGE-EI Working Paper,
Nr. 744,
2023
Abstract
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.
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The Importance of Credit Demand for Business Cycle Dynamics
Gregor von Schweinitz
IWH Discussion Papers,
Nr. 21,
2023
Abstract
This paper contributes to a better understanding of the important role that credit demand plays for credit markets and aggregate macroeconomic developments as both a source and transmitter of economic shocks. I am the first to identify a structural credit demand equation together with credit supply, aggregate supply, demand and monetary policy in a Bayesian structural VAR. The model combines informative priors on structural coefficients and multiple external instruments to achieve identification. In order to improve identification of the credit demand shocks, I construct a new granular instrument from regional mortgage origination.
I find that credit demand is quite elastic with respect to contemporaneous macroeconomic conditions, while credit supply is relatively inelastic. I show that credit supply and demand shocks matter for aggregate fluctuations, albeit at different times: credit demand shocks mostly drove the boom prior to the financial crisis, while credit supply shocks were responsible during and after the crisis itself. In an out-of-sample exercise, I find that the Covid pandemic induced a large expansion of credit demand in 2020Q2, which pushed the US economy towards a sustained recovery and helped to avoid a stagflationary scenario in 2022.
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PhD Graduates of the Department of Financial Markets Eleonora Sfrappini: "Four Essays on Banking, Climate Risks and Financial Regulation" (2024) Willam McShane: "The Competitive…
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Brown Bag Seminar Financial Markets Department In der Seminarreihe "Brown Bag Seminar" stellten Mitarbeiterinnen und Mitarbeiter der Abteilung Finanzmärkte und deren…
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Market-implied Ratings and Their Divergence from Credit Ratings
Iftekhar Hasan, Winnie P. H. Poon, Jianfu Shen, Gaiyan Zhang
Journal of Financial Research,
Nr. 2,
2023
Abstract
In this article, we investigate the divergence between credit ratings (CRs) and Moody's market-implied ratings (MIRs). Our evidence shows that rating gaps provide incremental information to the market regarding issuers' default risk over CRs alone in the short horizon and outperform CRs over extended horizons. The predictive ability of rating gaps is greater for more opaque and volatile issuers. Such predictability was more pronounced during the 2008 financial crisis but weakened in the post-Dodd-Frank Act period. This finding is consistent with credit rating agencies' efforts to improve their performance when facing regulatory pressure. Moreover, our analysis identifies rating-gap signals that do (do not) lead to subsequent Moody's actions to place issuers on negative outlook and watchlists. We find that negative signals from MIR gaps have a real economic impact on issuers' fundamentals such as profitability, leverage, investment, and default risk, thus supporting the recovery-efforts hypothesis.
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