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Demand versus Supply: Which is More Important for Inflation?

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  • Kevin J. Lansing

Abstract

I use Phillips curve type regressions to assess the relative contributions of demand and supply forces to U.S. inflation during the pandemic era from February 2020 onward and the decade following the end of the Great Recession. In the first specification (Model 1), demand and supply forces are measured using the vacancy-unemployment ratio and the New York Fed’s Global Supply Chain Pressure Index, respectively. In the second specification (Model 2), demand and supply forces are measured using the demand-driven and supply-driven components of PCE inflation from Shapiro (2025). The results derived from the two models are largely in agreement. For both models, variance decompositions imply that demand forces became more important for inflation during the pandemic era and dominated the influence of supply forces. In counterfactual simulations, both models imply that supply forces, together with the endogenous response of expected inflation, were the primary drivers of persistently low inflation after the Great Recession. Given that monetary policy operates to influence demand-driven inflation, this result helps to account for the Fed’s difficulty in achieving its 2% inflation goal during these years.

Suggested Citation

  • Kevin J. Lansing, 2024. "Demand versus Supply: Which is More Important for Inflation?," Working Paper Series 2025-08, Federal Reserve Bank of San Francisco.
  • Handle: RePEc:fip:fedfwp:99904
    DOI: 10.24148/wp2025-08
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    More about this item

    Keywords

    Phillips Curve; demand; supply; expected inflation;
    All these keywords.

    JEL classification:

    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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