With the world financial crisis came the rediscovery of the active role fiscal policy could play in remedying the situation. More recently, the Euro Crisis, with its mounting funding costs facing governments of a number of Southern EU member states and Ireland, has called this strategy into question. Opposing this view, the main point of this contribution is to elaborate on the link between rising sovereign risk premia in the Eurozone and a major feature of the financial crisis - elevated uncertainty after the Lehman collapse. Theoretically, this link is developed with reference to Keynes' liquidity preference theory. The high explanatory power of rising uncertainty in financial markets and the detrimental effects of fiscal austerity on the evolution of sovereign risk spreads are demonstrated empirically by means of panel regressions and supplementary correlation analyses.

Distortionary effects of inflation on relative prices are the main argument for inflation stabilization in macro models with sticky prices. Under indexation of non-optimized prices, those models imply a nonlinear and dynamic impact of inflation on the cross-sectional price dispersion (relative price or inflation variability, RPV). Using US sectoral price data, we estimate such a relationship between inflation and RPV, also taking into account the endogeneity of inflation by using two- and three-stage least-squares and GMM techniques, which turns out to be relevant. We find an effect of (expected) inflation on RPV, and our results indicate that average (“trend”) inflation is important for the RPV-inflation relationship. Lagged inflation matters for indexation in the CPI data, but is not important empirically in the PPI data.

European authorities and scholars published proposals on which indicators of macroeconomic imbalances might be used to uncover risks for the sustainability of public debt in the European Union. We test the ability of four proposed sets of indicators to send early-warnings of debt crises using a signals approach for the study of indicators and the construction of composite indicators. We find that a broad composite indicator has the highest predictive power. This fact still holds true if equal weights are used for the construction of the composite indicator in order to reflect the uncertainty about the origin of future crises.

This case study explores the contribution of universal banking to financial stability in Germany during the recent financial crisis. Germany is a prototype for universal banking and has suffered from a rather small number of banking crises in the past. We review the banking literature and analyze the major institutional and regulatory features of the German financial system to establish a nexus between universal banking and stability.

<p>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.</p>

This paper studies the interaction between fiscal policy and bondholders against the backdrop of high sovereign debt levels. For our analysis, we investigate the case of Italy, a country that has dealt with high public debt levels for a long time, using a Bayesian structural VAR model. We extend a canonical three variable macro mode to include a bond market, consisting of a fiscal rule and a bond demand schedule for long-term government bonds. To identify the model in the presence of political uncertainty and forward-looking investors, we derive an external instrument for bond demand shocks from a novel news ticker data set. Our main results are threefold. First, the interaction between fiscal policy and bondholders’ expectations is critical for the evolution of prices. Fiscal policy reinforces contractionary monetary policy through sustained increases in primary surpluses and investors provide incentives for “passive” fiscal policy. Second, investors’ expectations matter for inflation, and we document a Fisherian response of inflation across all maturities in response to a bond demand shock. Third, domestic politics is critical in the determination of bondholders’ expectations and an increase in the perceived riskiness of sovereign debt increases inflation and thus complicates the task of controlling price growth.

This paper compares macroeconomic effects of Knightian uncertainty and risk using policy shocks for the case of Italy. Drawing on the ambiguity literature, I use changes in the bid-ask spread and mid-price of government bonds as distinct measures for uncertainty and risk. The identification exploits the quasi-pessimistic behavior under ambiguity-aversion and the dealer market structure of government bond markets, where dealers must quote both sides of the market. If uncertainty increases, ambiguity-averse dealers will quasi-pessimistically quote higher ask and lower bid prices – increasing the bid-ask spread. In contrast, a pure change in risk shifts the risk-compensating discount factor which is well approximated by the change in bond mid-prices. I evaluate economic effects of the two measures within an instrumental variable local projection framework. The main findings are threefold. First, the resulting shock time series for uncertainty and risk are uncorrelated with each other at the intraday level, however, upon aggregation to monthly level the measures become correlated. Second, uncertainty is an important driver of economic aggregates. Third, macroeconomic effects of risk and uncertainty are similar, except for the response of prices. While sovereign risk raises inflation, uncertainty suppresses price growth – a result which is in line with increased price rigidity under ambiguity.

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. <br />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.

<p>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.</p>