美联储-供应链约束与通货膨胀（英）-2023.11-82页_798kb

Summary of "Supply Chain Constraints and Inflation"

Contributions

• Develops a multisector, open-economy New Keynesian DSGE model with input-output linkages and occasionally binding capacity constraints for domestic and foreign firms.
• Documents that binding capacity constraints explain approximately half (two percentage points) of the 4 percentage point rise in headline inflation during 2021-2022.
• Highlights that supply chain constraints amplified the impact of expansionary monetary policy and demand shocks during the post-pandemic recovery.

Key Findings

1. Role of Constraints: Binding constraints in supply chains imposed an additional markup shock (or "quasi-markup shock") in both domestic and import price Phillips curves when constraints bind.
2. Counterfactual Analysis:
   • Relaxing constraints reduces inflation by up to 1 percentage point during the peak inflation period of 2021-2022.
   • Inflation declined faster in 2022 when constraints eased due to monetary policy tightening.
3. Demand vs. Supply:
   • Demand shocks and capacity shocks both contribute to binding constraints, with monetary policy playing a key role in 2021.
   • Adverse constraint shocks lead to negative comovement between inflation and output/imports, while demand shocks lead to positive comovement.
4. Labor Market Extension: Incorporating labor supply constraints confirmed that binding capacity constraints remain primary drivers of inflation, while labor supply shocks were less influential post-pandemic.

Policy Implications

• Scarcity in supply chains increases price-setting firms' markups, creating persistent inflationary pressure distinct from traditional New Keynesian markup shocks.
• Optimal policy requires distinguishing between markup shocks from market power and binding constraints, as the latter complicates standard models.
• Monetary policy effectiveness was constrained by supply chain tightness, limiting its ability to manage inflation without addressing supply-side factors.

Model Innovations

• Framework features occasionally binding constraints at firm-level production capacity constraints that affect downstream firms and consumers.
• Uses Bayesian maximum likelihood estimation to handle endogenous constraint durations and price adjustment frictions.
• Develops quantitative identification for supply constraints using patterns of inflation and output comovement.

Data Considerations

• Excludes energy prices to isolate supply chain effects.
• Uses import price inflation for industrial materials as key indicator of binding input supply constraints.
• Focuses on post-pandemic period (starting 2020:Q2) due to dogmatic priors.

Methodology

• Piecewise linear solution technique to handle occasionally binding constraints.
• Estimation uses Bayesian maximum likelihood with state space representation.
• Combines standard DSGE estimation with duration-based parameters.