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What Can Stockouts Tell Us About Inflation? Evidence from Online Micro Data

In: NBER International Seminar on Macroeconomics 2022

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  • Alberto Cavallo
  • Oleksiy Kryvtsov

Abstract

We use a detailed micro dataset on product availability and stockouts to construct a direct high-frequency measure of consumer product shortages during the 2020–2022 pandemic. We document a widespread multi-fold rise in stockouts in nearly all sectors early in the pandemic. Over time, the composition evolved from temporary to more permanently discontinued products, concentrated in fewer sectors. We show that unexpected shocks to stockout levels have significant inflationary effects within three months. These effects are larger and more persistent for imported goods and import-intensive sectors. We develop a model of inventories in a sector facing both demand and cost disturbances, and use the observed joint dynamics of stockouts and prices to show that these effects can be associated with elevated costs of replenishing inventories and higher exposure to trade.
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Suggested Citation

  • Alberto Cavallo & Oleksiy Kryvtsov, 2022. "What Can Stockouts Tell Us About Inflation? Evidence from Online Micro Data," NBER Chapters, in: NBER International Seminar on Macroeconomics 2022, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberch:14899
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    as
    1. Oleksiy Kryvtsov & Virgiliu Midrigan, 2013. "Inventories, Markups, and Real Rigidities in Menu Cost Models," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 80(1), pages 249-276.
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    4. Oleksiy Kryvtsov & Virgiliu Midrigan, 2010. "Inventories and Real Rigidities in New Keynesian Business Cycle Models," NBER Chapters, in: Sticky Prices and Inflation Dynamics (NBER-TCER-CEPR), pages 259-281, National Bureau of Economic Research, Inc.
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    9. Alberto Cavallo & Gita Gopinath & Brent Neiman & Jenny Tang, 2021. "Tariff Pass-Through at the Border and at the Store: Evidence from US Trade Policy," American Economic Review: Insights, American Economic Association, vol. 3(1), pages 19-34, March.
    10. Hassan, Tarek & Hollander, Stephan & van Lent, Laurence & Schwedeler, Markus & Tahoun, Ahmed, 2020. "Firm-Level Exposure to Epidemic Diseases: Covid-19, SARS, and H1N1," CEPR Discussion Papers 14573, C.E.P.R. Discussion Papers.
    11. Veronica Guerrieri & Guido Lorenzoni & Ludwig Straub & Iván Werning, 2022. "Macroeconomic Implications of COVID-19: Can Negative Supply Shocks Cause Demand Shortages?," American Economic Review, American Economic Association, vol. 112(5), pages 1437-1474, May.
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    16. Hall, George & Rust, John, 2000. "An empirical model of inventory investment by durable commodity intermediaries," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 52(1), pages 171-214, June.
    17. Alberto Cavallo & Robert C. Feenstra & Robert Inklaar, 2023. "Product Variety, the Cost of Living, and Welfare across Countries," American Economic Journal: Macroeconomics, American Economic Association, vol. 15(4), pages 40-66, October.
    18. Kanika Mahajan & Shekhar Tomar, 2021. "COVID‐19 and Supply Chain Disruption: Evidence from Food Markets in India†," American Journal of Agricultural Economics, John Wiley & Sons, vol. 103(1), pages 35-52, January.
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    21. John C. Driscoll & Aart C. Kraay, 1998. "Consistent Covariance Matrix Estimation With Spatially Dependent Panel Data," The Review of Economics and Statistics, MIT Press, vol. 80(4), pages 549-560, November.
    22. Alberto Cavallo & Eduardo Cavallo & Roberto Rigobon, 2014. "Prices and Supply Disruptions during Natural Disasters," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 60(S2), pages 449-471, November.
    23. Stock, James H & Wright, Jonathan H & Yogo, Motohiro, 2002. "A Survey of Weak Instruments and Weak Identification in Generalized Method of Moments," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(4), pages 518-529, October.
    24. Cavallo, Alberto, 2013. "Online and official price indexes: Measuring Argentina's inflation," Journal of Monetary Economics, Elsevier, vol. 60(2), pages 152-165.
    25. Meier, Matthias & Pinto, Eugenio, 2024. "COVID-19 Supply Chain Disruptions," European Economic Review, Elsevier, vol. 162(C).
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    28. repec:bla:revinw:v:60:y:2014:i::p:s449-s471 is not listed on IDEAS
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    Full references (including those not matched with items on IDEAS)

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    Cited by:

    1. Youngna Choi, 2022. "Economic Stimulus and Financial Instability: Recent Case of the U.S. Household," JRFM, MDPI, vol. 15(6), pages 1-25, June.
    2. Hugh Montag & Daniel Villar, 2022. "Price-Setting During the Covid Era," Economic Working Papers 547, Bureau of Labor Statistics.
    3. Patrick W. McLaughlin & Alexander Stevens & Shawn Arita & Xiao Dong, 2023. "Stocking up and stocking out: Food retail stock‐outs, consumer demand, and prices during the COVID‐19 pandemic in 2020," Applied Economic Perspectives and Policy, John Wiley & Sons, vol. 45(3), pages 1618-1633, September.
    4. Rachel Soloveichik, 2022. "Theoretical Inflation for Unavailable Products," BEA Working Papers 0193, Bureau of Economic Analysis.
    5. Meyer, Brent H. & Prescott, Brian C. & Sheng, Xuguang Simon, 2023. "The impact of supply chain disruptions on business expectations during the pandemic," Energy Economics, Elsevier, vol. 126(C).
    6. Alessandria, George & Khan, Shafaat Yar & Khederlarian, Armen & Mix, Carter & Ruhl, Kim J., 2023. "The aggregate effects of global and local supply chain disruptions: 2020–2022," Journal of International Economics, Elsevier, vol. 146(C).
    7. An, Zidong & Sheng, Xuguang Simon & Zheng, Xinye, 2023. "What is the role of perceived oil price shocks in inflation expectations?," Energy Economics, Elsevier, vol. 126(C).
    8. Beck, Günter W. & Carstensen, Kai & Menz, Jan-Oliver & Schnorrenberger, Richard & Wieland, Elisabeth, 2023. "Nowcasting consumer price inflation using high-frequency scanner data: Evidence from Germany," Discussion Papers 34/2023, Deutsche Bundesbank.
    9. Uzma Khan & Alexander DePaoli, 2024. "Brand loyalty in the face of stockouts," Journal of the Academy of Marketing Science, Springer, vol. 52(1), pages 44-74, January.
    10. Higo, Masahiro & Shiratsuka, Shigenori, 2023. "Consumer price measurement under the first wave of the COVID-19 spread in Japan: Scanner data evidence for retailers in Tokyo," Japan and the World Economy, Elsevier, vol. 65(C).
    11. Brent Meyer & Nicholas B. Parker & Xuguang Sheng, 2021. "Unit Cost Expectations and Uncertainty: Firms' Perspectives on Inflation," FRB Atlanta Working Paper 2021-12a, Federal Reserve Bank of Atlanta.
    12. Sonan Memon, 2022. "Inflation in Pakistan: High-Frequency Estimation and Forecasting," PIDE-Working Papers 2022:12, Pakistan Institute of Development Economics.
    13. Galina Hale & John Leer & Fernanda Nechio, 2022. "Inflationary Effects of Fiscal Support to Households and Firms," Working Paper Series 2023-02, Federal Reserve Bank of San Francisco.
    14. Richard K. Crump & Stefano Eusepi & Marc Giannoni & Ayşegül Şahin, 2022. "The Unemployment-Inflation Trade-off Revisited: The Phillips Curve in COVID Times," NBER Working Papers 29785, National Bureau of Economic Research, Inc.
    15. Melissa Maas & Gumataw Kifle Abebe & Christopher M. Hartt & Emmanuel K. Yiridoe, 2022. "Consumer Perceptions about the Value of Short Food Supply Chains during COVID-19: Atlantic Canada Perspective," Sustainability, MDPI, vol. 14(13), pages 1-20, July.

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    More about this item

    JEL classification:

    • D22 - Microeconomics - - Production and Organizations - - - Firm Behavior: Empirical Analysis
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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