This paper surveys recent advances in drawing structural conclusions from vector autoregressions (VARs), providing a unified perspective on the role of prior knowledge. We describe the traditional approach to identification as a claim to have exact prior information about the structural model and propose Bayesian inference as a way to acknowledge that prior information is imperfect or subject to error. We raise concerns from both a frequentist and a Bayesian perspective about the way that results are typically reported for VARs that are set-identified using sign and other restrictions. We call attention to a common but previously unrecognized error in estimating structural elasticities and show how to correctly estimate elasticities even in the case when one only knows the effects of a single structural shock.

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.

The international co-movement of interest rates reflects correlated business-cycle fluctuations, largely driven by demand shocks. Monetary policy in advanced economies follows domestic mandates – inflation and the output gap – and does not respond to foreign policy shocks. We derive this result from a Bayesian structural panel vector autoregression with informative priors, homogeneity restrictions on contemporaneous relations, a hierarchical Minnesota prior with cross-sectional shrinkage, and a factor structure for structural shocks.

Die mittelfristige Projektion der gesamtwirtschaftlichen Lage in Deutschland beinhaltet, dass das Wirtschaftswachstum mit 1% pro Jahr in den kommenden sechs Jahren in etwa genauso hoch ausfällt wie in den vergangenen sechs Jahren. Der Staatshaushalt bleibt im Defizit, aber der Schuldenstand geht relativ zum Bruttoinlandsprodukt ab dem Jahr 2024 wieder zurück. Bei diesem Tempo der wirtschaftlichen Expansion werden die Emissionen mittelfristig zwar weiter zurückgehen, aber deutlich langsamer als nötig, um die nationalen Klimaschutzziele zu erreichen.

We evaluate alternative indicators of global economic activity and other market funda-mentals in terms of their usefulness for forecasting real oil prices and global petroleum consumption. World industrial production is one of the most useful indicators. However, by combining measures from several different sources we can do even better. Our analysis results in a new index of global economic conditions and measures for assessing future energy demand and oil price pressures. We illustrate their usefulness for quantifying the main factors behind the severe contraction of the global economy and the price risks faced by shale oil producers in early 2020.

Despite their importance, the discussion of spillover effects in empirical research often misses the rigor dedicated to endogeneity concerns. We analyze a broad set of workhorse models of firm interactions and show that spillovers naturally arise in many corporate finance settings. This has important implications for the estimation of treatment effects: i) even with random treatment, spillovers lead to a complicated bias, ii) fixed effects can exacerbate the spillover-induced bias. We propose simple diagnostic tools for empirical researchers and illustrate our guidance in an application.