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The market for inflation risk

Author

Listed:
  • Bahaj, Saleem

    (University College London and Bank of England)

  • Czech, Robert

    (Bank of England)

  • Ding, Sitong

    (London School of Economics)

  • Reis, Ricardo

    (London School of Economics)

Abstract

This paper uses transaction-level data on the universe of traded UK inflation swaps to characterise who buys and sells inflation risk, when, and with what price elasticity. This provides measures of expected inflation cleaned from liquidity frictions. We first show that this market is segmented: pension funds trade at long horizons while hedge funds trade at short horizons, with dealer banks as their counterparties in both markets. This segmentation suggests three identification strategies – sign restrictions, granular instrumental variables, and heteroskedasticity – for the demand and supply functions of each investor type. Across the three strategies, we find that (i) prices absorb new information within three days; (ii) the supply of long-horizon inflation protection is very elastic; and (iii) short-horizon price movements are unreliable measures of expected inflation as they primarily reflect liquidity shocks. Our counterfactual measure of long-horizon expected inflation in the absence of these shocks suggests that the risk of a deflation trap during the pandemic and of a persistent rise in inflation following the energy shocks were overstated, while since Autumn of 2022, expected inflation has been lower and falling more rapidly than conventional measures.

Suggested Citation

  • Bahaj, Saleem & Czech, Robert & Ding, Sitong & Reis, Ricardo, 2023. "The market for inflation risk," Bank of England working papers 1028, Bank of England.
  • Handle: RePEc:boe:boeewp:1028
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    References listed on IDEAS

    as
    1. Meredith J. Beechey & Benjamin K. Johannsen & Andrew T. Levin, 2011. "Are Long-Run Inflation Expectations Anchored More Firmly in the Euro Area Than in the United States?," American Economic Journal: Macroeconomics, American Economic Association, vol. 3(2), pages 104-129, April.
    2. Xavier Gabaix, 2016. "Power Laws in Economics: An Introduction," Journal of Economic Perspectives, American Economic Association, vol. 30(1), pages 185-206, Winter.
    3. Koijen, Ralph & Yogo, Motohiro, 2020. "Exchange Rates and Asset Prices in a Global Demand System," CEPR Discussion Papers 14874, C.E.P.R. Discussion Papers.
    4. Xavier Gabaix & Ralph S. J. Koijen, 2024. "Granular Instrumental Variables," Journal of Political Economy, University of Chicago Press, vol. 132(7), pages 2274-2303.
    5. Joseph Haubrich & George Pennacchi & Peter Ritchken, 2012. "Inflation Expectations, Real Rates, and Risk Premia: Evidence from Inflation Swaps," The Review of Financial Studies, Society for Financial Studies, vol. 25(5), pages 1588-1629.
    6. Ralph S J Koijen & Robert J Richmond & Motohiro Yogo, 2024. "Which Investors Matter for Equity Valuations and Expected Returns?," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 91(4), pages 2387-2424.
    7. Ralph S. J. Koijen & Motohiro Yogo, 2019. "A Demand System Approach to Asset Pricing," Journal of Political Economy, University of Chicago Press, vol. 127(4), pages 1475-1515.
    8. James H. Stock & Mark W. Watson, 2018. "Identification and Estimation of Dynamic Causal Effects in Macroeconomics Using External Instruments," Economic Journal, Royal Economic Society, vol. 128(610), pages 917-948, May.
    9. Covi, Giovanni & Brookes, James & Raja, Charumathi, 2022. "Measuring Capital at Risk in the UK banking sector: a microstructural network approach," Bank of England working papers 983, Bank of England.
    10. Jushan Bai, 2009. "Panel Data Models With Interactive Fixed Effects," Econometrica, Econometric Society, vol. 77(4), pages 1229-1279, July.
    11. Lihong McPhail & Philipp Schnabl & Bruce Tuckman, 2023. "Do Banks Hedge Using Interest Rate Swaps?," NBER Working Papers 31166, National Bureau of Economic Research, Inc.
    12. Jonas E. Arias & Juan F. Rubio‐Ramírez & Daniel F. Waggoner, 2018. "Inference Based on Structural Vector Autoregressions Identified With Sign and Zero Restrictions: Theory and Applications," Econometrica, Econometric Society, vol. 86(2), pages 685-720, March.
    13. Xiang Fang & Yang Liu & Nikolai Roussanov, 2022. "Getting to the Core: Inflation Risks Within and Across Asset Classes," NBER Working Papers 30169, National Bureau of Economic Research, Inc.
    14. Ricardo Reis, 2020. "The People versus the Markets: A Parsimonious Model of Inflation Expectations," Discussion Papers 2033, Centre for Macroeconomics (CFM).
    15. Czech, Robert & Della Corte, Pasquale & Huang, Shiyang & Wang, Tianyu, 2022. "FX option volume," Bank of England working papers 964, Bank of England.
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    Cited by:

    1. Xavier Gabaix & Ralph S J Koijen & Robert Richmond & Motohiro Yogo, "undated". "Artificial intelligence and big holdings data: Opportunities for central banks," BIS Working Papers 1222, Bank for International Settlements.
    2. Barria, Rodrigo & Pinter, Gabor, 2023. "Mispricing in inflation markets," Bank of England working papers 1034, Bank of England.

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    More about this item

    Keywords

    Asset demand system; monetary policy; anchored expectations; identification of demand and supply shocks.;
    All these keywords.

    JEL classification:

    • C30 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - General
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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