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Inflation Expectations, Learning and Supermarket Prices

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  • Alberto Cavallo
  • Guillermo Cruces
  • Ricardo Perez-Truglia

Abstract

Information frictions play a central role in the formation of household inflation expectations, but there is no consensus about their origins. We address this question with novel evidence from survey experiments. We document two main findings. First, individuals in lower-inflation contexts have significantly weaker priors about the inflation rate. This finding suggests that rational inattention may be an important source of information frictions. Second, cognitive limitations also appear to be a source of information frictions: even when information about inflation statistics is made readily available, individuals still place a significant weight on less accurate sources of information, such as their memories of the price changes of the supermarket products they purchase. We discuss the implications of these findings for macroeconomic models and policy-making.

Suggested Citation

  • Alberto Cavallo & Guillermo Cruces & Ricardo Perez-Truglia, 2014. "Inflation Expectations, Learning and Supermarket Prices," NBER Working Papers 20576, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:20576
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    Cited by:

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    2. Goldfayn-Frank, Olga & Wohlfart, Johannes, 2018. "How do consumers adapt to a new environment in their economic forecasting? Evidence from the German reunification," IMFS Working Paper Series 129, Goethe University Frankfurt, Institute for Monetary and Financial Stability (IMFS).
    3. Emanuele Ciani & Adeline Delavande & Ben Etheridge & Marco Francesconi, 2023. "Policy Uncertainty and Information Flows: Evidence from Pension Reform Expectations," The Economic Journal, Royal Economic Society, vol. 133(649), pages 98-129.
    4. Lergetporer, Philipp & Woessmann, Ludger, 2019. "The Political Economy of Higher Education Finance: How Information and Design Affect Public Preferences for Tuition," Rationality and Competition Discussion Paper Series 145, CRC TRR 190 Rationality and Competition.
    5. Sukudhew (Sukhdave) Singh, 2016. "Economic changes, inflation dynamics and policy responses: the Malaysian experience," BIS Papers chapters, in: Bank for International Settlements (ed.), Inflation mechanisms, expectations and monetary policy, volume 89, pages 231-245, Bank for International Settlements.
    6. Katharina Werner, 2019. "The Role of Information for Public Preferences on Education – Evidence from Representative Survey Experiments," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 82.
    7. Alexander Ballantyne & Christian Gillitzer & David Jacobs & Ewan Rankin, 2016. "Disagreement about Inflation Expectations," RBA Research Discussion Papers rdp2016-02, Reserve Bank of Australia.
    8. Naohito Abe & Yuko Ueno, 2016. "The Mechanism of Inflation Expectation Formation among Consumers," UTokyo Price Project Working Paper Series 064, University of Tokyo, Graduate School of Economics.
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    10. Alberto Cavallo, 2017. "Are Online and Offline Prices Similar? Evidence from Large Multi-channel Retailers," American Economic Review, American Economic Association, vol. 107(1), pages 283-303, January.
    11. Hunziker, Hans-Ueli & Raggi, Christian & Rosenblatt-Wisch, Rina & Zanetti, Attilio, 2022. "The impact of guidance, short-term dynamics and individual characteristics on firms’ long-term inflation expectations," Journal of Macroeconomics, Elsevier, vol. 71(C).
    12. Alberto Cavallo & Roberto Rigobon, 2016. "The Billion Prices Project: Using Online Prices for Measurement and Research," Journal of Economic Perspectives, American Economic Association, vol. 30(2), pages 151-178, Spring.
    13. Olympia Bover, 2015. "Measuring expectations from household surveys: new results on subjective probabilities of future house prices," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 6(4), pages 361-405, November.
    14. Alberto Cavallo & Guillermo Cruces & Ricardo Perez-Truglia, 2016. "Learning from Potentially Biased Statistics," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 52(1 (Spring), pages 59-108.
    15. Vadim Grishchenko & Diana Gasanova & Egor Fomin & Grigory Korenyak, 2023. "Visible prices and their influence on inflation expectations of Russian households," Bank of Russia Working Paper Series wps117, Bank of Russia.
    16. George-Marios Angeletos & Chen Lian, 2016. "Incomplete Information in Macroeconomics: Accommodating Frictions in Coordination," NBER Working Papers 22297, National Bureau of Economic Research, Inc.
    17. Ingar Haaland & Christopher Roth, 2023. "Beliefs about Racial Discrimination and Support for Pro-Black Policies," The Review of Economics and Statistics, MIT Press, vol. 105(1), pages 40-53, January.
    18. Abe, Naohito & Ueno, Yuko, 2016. "The Mechanism of Inflation Expectation Formation among Consumers," RCESR Discussion Paper Series DP16-1, Research Center for Economic and Social Risks, Institute of Economic Research, Hitotsubashi University.
    19. Abe, Naohito & Ueno, Yuko, 2015. "Measuring Inflation Expectations: Consumers' Heterogeneity and Nonlinearity," RCESR Discussion Paper Series DP15-5, Research Center for Economic and Social Risks, Institute of Economic Research, Hitotsubashi University.
    20. Koichiro Kamada & Jouchi Nakajima & Shusaku Nishiguchi, 2015. "Are Household Inflation Expectations Anchored in Japan?," Bank of Japan Working Paper Series 15-E-8, Bank of Japan.
    21. Alberto Cavallo & Guillermo Cruces & Ricardo Perez-Truglia, 2016. "Learning from Potentially-Biased Statistics: Household Inflation Perceptions and Expectations in Argentina," NBER Working Papers 22103, National Bureau of Economic Research, Inc.
    22. Xu, Yingying & Chang, Hsu-Ling & Lobonţ, Oana-Ramona & Su, Chi-Wei, 2016. "Modeling heterogeneous inflation expectations: empirical evidence from demographic data?," Economic Modelling, Elsevier, vol. 57(C), pages 153-163.
    23. Alberto Cavallo & Guillermo Cruces & Ricardo Perez-Truglia, 2016. "Learning from Potentially Biased Statistics," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 47(1 (Spring), pages 59-108.

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    More about this item

    JEL classification:

    • C93 - Mathematical and Quantitative Methods - - Design of Experiments - - - Field Experiments
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • E58 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Central Banks and Their Policies

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