Structural Interpretation of Vector Autoregressions with Incomplete Identification: Revisiting the Role of Oil Supply and Demand Shocks

2019/05/01 by Christiane Baumeister, James D. Hamilton · 893 citations
Economics, Econometrics and Finance · Energy · #Bayesian inference #Bayesian probability #Bayesian vector autoregression #Computer science #Demand shock #Econometrics #Economics #Energy, Environment, and Transportation Policies #Identification (biology) #Inference #Lag #Macroeconomics #Market Dynamics and Volatility #Microeconomics #Monetary Policy and Economic Impact #Monetary economics #Monetary policy #Oil price #Structural vector autoregression #Supply and demand #Supply shock #Vector autoregression

paper · doi:10.1257/aer.20151569

published in American Economic Review 109(5), 1873-1910 (American Economic Association)

openalex publication_date 2019/05/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05

Abstract

Traditional approaches to structural vector autoregressions (VARs) can be viewed as special cases of Bayesian inference arising from very strong prior beliefs. These methods can be generalized with a less restrictive formulation that incorporates uncertainty about the identifying assumptions themselves. We use this approach to revisit the importance of shocks to oil supply and demand. Supply disruptions turn out to be a bigger factor in historical oil price movements and inventory accumulation a smaller factor than implied by earlier estimates. Supply shocks lead to a reduction in global economic activity after a significant lag, whereas shocks to oil demand do not. (JEL C32, L71, Q35, Q43)

Citations

• Bayesian Methods for Dynamic Multivariate Models

Cited by

• The Macroeconomic Effects of Oil Supply News: Evidence from OPEC Announcements
• Measuring labor supply and demand shocks during COVID-19
• Interconnectedness among supply chain disruptions, energy crisis, and oil market volatility on economic resilience
• Agentic AI Orchestration of Heterogeneous Economic Models for Rapid, Multi-scenario Analysis of Energy Crises
• Supply and demand components of Philippine inflation, 2001–2024
• Natural gas prices, inflation expectations, and the pass-through to euro area inflation
• Foreign Labor and Dutch Disease: Evidence from GCC economies
• The fuel security and climate policy nexus
• The causal interpretation of panel vector autoregressions
• Asymmetric markup responses to monetary shocks over the business cycle
• Media Sentiment and Oil Price Expectations
• Getting to the Core: Inflation Risks Within and Across Asset Classes
• Gas supply shocks, uncertainty and price setting: evidence from Italian firms
• Understanding the global drivers of inflation: How important are oil prices?
• Burn now or never? Climate policy exposure and investment of fossil fuel firms
• Fiscal policy and inflation in the Euro Area
• RETRACTED: Applying Theorem of Ross to Transition Probability Matrix in Energy Options Pricing after Political Tensions and Russia-Ukraine Conflict
• Becoming Green: Decomposing the Macroeconomic Effects of Green Technology News Shocks
• Demand for safe assets and spillovers from the global dollar cycle
• Uncertainty before and during COVID‐19: A survey
• Discretionary Tax Changes and Macroeconomic Activity: New Narrative Evidence from Australia*
• Here Comes the Change: The Role of Global and Domestic Factors in Post-Pandemic Inflation in Europe
• Drivers of the global financial cycle
• U.S. Monetary Policy and the Global Financial Cycle
• The role of income and substitution in commodity demand
• Clustered Local Projections for Short and Ultra-Short Time Series -- A Hierarchical Bayesian Framework
• What information is most relevant for estimating output gaps in emerging economies?
• Dynamic interactions between oil price and exchange rate. [europepmc]
• A shock like no other: coronavirus rattles commodity markets. [europepmc]
• A framework to predict the price of energy for the end-users with applications to monetary and energy policies. [europepmc]
• The U.S. Nonfarm Payroll and the out-of-sample predictability of output growth for over six decades. [europepmc]
• Oil price shocks and China's consumer and entrepreneur sentiment: a Bayesian structural VAR approach. [europepmc]
• New Findings Regarding the Out-of-Sample Predictive Impact of the Price of Crude Oil on the United States Industrial Production [europepmc]
• Non-renewable resource extraction over the long term: empirical evidence from global copper production [europepmc]
• Pandemics and Oil Shocks [europepmc]
• Pandemics and Oil Shocks [europepmc]

Related

• Uncertain Short-Run Restrictions and Statistically Identified Structural Vector Autoregressions
• A new algorithm for structural restrictions in Bayesian vector autoregressions
• The Effects of Oil Price Uncertainty on Global Real Economic Activity
• Partially identified heteroskedastic SVARs
• Identification of one independent shock in structural VARs