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Do Misperceptions about Demand Matter? Theory and Evidence

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Abstract

We assess theoretically and empirically the consequences of demand misperceptions. In a New Keynesian model with dispersed information, agents receive noisy signals about both supply and demand. Firms and consumers have an asymmetric access to information, so aggregate misperceptions of demand by the supply side can drive economic fluctuations. The model’s predictions are used to identify empirically fundamental and noise shocks on supply and demand. We exploit survey nowcast errors on both GDP growth and inflation, fundamental and noise shocks affecting the errors with opposite signs. We show that demand-related noise shocks have a negative effect on output and contribute substantially to business cycles. Additionally, monetary policy plays a key role in the transmission of demand noise.

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  • Kenza Benhima & Céline Poilly, 2017. "Do Misperceptions about Demand Matter? Theory and Evidence," AMSE Working Papers 1717, Aix-Marseille School of Economics, France.
  • Handle: RePEc:aim:wpaimx:1717
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    1. Robert B. Barsky & Eric R. Sims, 2012. "Information, Animal Spirits, and the Meaning of Innovations in Consumer Confidence," American Economic Review, American Economic Association, vol. 102(4), pages 1343-1377, June.
    2. Lawrence J. Christiano & Cosmin Ilut & Roberto Motto & Massimo Rostagno, 2010. "Monetary policy and stock market booms," Proceedings - Economic Policy Symposium - Jackson Hole, Federal Reserve Bank of Kansas City, pages 85-145.
    3. Richard Clarida & Jordi Galí & Mark Gertler, 2000. "Monetary Policy Rules and Macroeconomic Stability: Evidence and Some Theory," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 115(1), pages 147-180.
    4. Dées, Stephane & Zimic, Srečko, 2019. "Animal spirits, fundamental factors and business cycle fluctuations," Journal of Macroeconomics, Elsevier, vol. 61(C), pages 1-1.
    5. Zeno Enders & Michael Kleemann & Gernot J. Muller, 2021. "Growth Expectations, Undue Optimism, and Short-Run Fluctuations," The Review of Economics and Statistics, MIT Press, vol. 103(5), pages 905-921, December.
    6. Chari, V.V. & Kehoe, Patrick J. & McGrattan, Ellen R., 2008. "Are structural VARs with long-run restrictions useful in developing business cycle theory?," Journal of Monetary Economics, Elsevier, vol. 55(8), pages 1337-1352, November.
    7. Roberto perotti, 2011. "Expectations and Fiscal Policy: An Empirical Investigation," Working Papers 429, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    8. Olivier J. Blanchard & Jean-Paul L'Huillier & Guido Lorenzoni, 2013. "News, Noise, and Fluctuations: An Empirical Exploration," American Economic Review, American Economic Association, vol. 103(7), pages 3045-3070, December.
    9. Uhlig, Harald, 2005. "What are the effects of monetary policy on output? Results from an agnostic identification procedure," Journal of Monetary Economics, Elsevier, vol. 52(2), pages 381-419, March.
    10. Paul Beaudry & Patrick Feve & Alain Guay & Franck Portier, 2019. "When is Nonfundamentalness in SVARs a Real Problem?," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 34, pages 221-243, October.
    11. Fève, Patrick & Pietrunti, Mario, 2016. "Noisy fiscal policy," European Economic Review, Elsevier, vol. 85(C), pages 144-164.
    12. Leonardo Melosi, 2014. "Estimating Models with Dispersed Information," American Economic Journal: Macroeconomics, American Economic Association, vol. 6(1), pages 1-31, January.
    13. Nir Jaimovich & Sergio Rebelo, 2009. "Can News about the Future Drive the Business Cycle?," American Economic Review, American Economic Association, vol. 99(4), pages 1097-1118, September.
    14. Mario Forni & Luca Gambetti & Luca Sala, 2014. "No News in Business Cycles," Economic Journal, Royal Economic Society, vol. 124(581), pages 1168-1191, December.
    15. Fève, Patrick & Kass-Hanna, Tannous & Pietrunti, Mario, 2016. "An analytical characterization of noisy fiscal policy," Economics Letters, Elsevier, vol. 148(C), pages 76-79.
    16. Juan F. Rubio-Ramírez & Jonas E. Arias & Daniel F. Waggoner, 2013. "Inference Based on SVARs Identied with Sign and Zero Restrictions: Theory and Applications," Working Papers 1338, BBVA Bank, Economic Research Department.
    17. Dedola, Luca & Neri, Stefano, 2007. "What does a technology shock do? A VAR analysis with model-based sign restrictions," Journal of Monetary Economics, Elsevier, vol. 54(2), pages 512-549, March.
    18. Andrei A Levchenko & Nitya Pandalai-Nayar, 2020. "Tfp, News, and “Sentiments”: the International Transmission of Business Cycles," Journal of the European Economic Association, European Economic Association, vol. 18(1), pages 302-341.
    19. Carlo Altavilla & Matteo Ciccarelli, 2011. "Monetary Policy Analysis in Real-Time. Vintage combination from a real-time dataset," CSEF Working Papers 274, Centre for Studies in Economics and Finance (CSEF), University of Naples, Italy.
    20. Renée Fry & Adrian Pagan, 2011. "Sign Restrictions in Structural Vector Autoregressions: A Critical Review," Journal of Economic Literature, American Economic Association, vol. 49(4), pages 938-960, December.
    21. Forni, Mario & Gambetti, Luca, 2016. "Government spending shocks in open economy VARs," Journal of International Economics, Elsevier, vol. 99(C), pages 68-84.
    22. Milani, Fabio & Rajbhandari, Ashish, 2020. "Observed expectations, news shocks, and the business cycle," Research in Economics, Elsevier, vol. 74(2), pages 95-118.
    23. Mario Forni & Luca Gambetti & Marco Lippi & Luca Sala, 2017. "Noisy News in Business Cycles," American Economic Journal: Macroeconomics, American Economic Association, vol. 9(4), pages 122-152, October.
    24. Canova, Fabio & Paustian, Matthias, 2011. "Business cycle measurement with some theory," Journal of Monetary Economics, Elsevier, vol. 58(4), pages 345-361.
    25. Jonas E. Arias & Juan F. Rubio-Ramirez & Daniel F. Waggoner, 2014. "Inference Based on SVARs Identified with Sign and Zero Restrictions: Theory and Applications," International Finance Discussion Papers 1100, Board of Governors of the Federal Reserve System (U.S.).
    26. Beaudry, Paul & Collard, Fabrice & Portier, Franck, 2011. "Gold rush fever in business cycles," Journal of Monetary Economics, Elsevier, vol. 58(2), pages 84-97, March.
    27. Neville Francis & Valerie A. Ramey, 2009. "Measures of per Capita Hours and Their Implications for the Technology-Hours Debate," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 41(6), pages 1071-1097, September.
    28. Nadav Ben Zeev & Christopher Gunn & Hashmat Khan, 2020. "Monetary News Shocks," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 52(7), pages 1793-1820, October.
    29. Beaudry, Paul & Portier, Franck, 2004. "An exploration into Pigou's theory of cycles," Journal of Monetary Economics, Elsevier, vol. 51(6), pages 1183-1216, September.
    30. Riccardo M. Masolo & Alessia Paccagnini, 2019. "Identifying Noise Shocks: A VAR with Data Revisions," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 51(8), pages 2145-2172, December.
    31. Guido Lorenzoni, 2009. "A Theory of Demand Shocks," American Economic Review, American Economic Association, vol. 99(5), pages 2050-2084, December.
    32. Fabio Milani & John Treadwell, 2012. "The Effects of Monetary Policy “News” and “Surprises”," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 44(8), pages 1667-1692, December.
    33. Susan Yang, Shu-Chun, 2005. "Quantifying tax effects under policy foresight," Journal of Monetary Economics, Elsevier, vol. 52(8), pages 1557-1568, November.
    34. Nimark, Kristoffer, 2008. "Monetary policy with signal extraction from the bond market," Journal of Monetary Economics, Elsevier, vol. 55(8), pages 1389-1400, November.
    35. Orphanides, Athanasios, 2003. "Monetary policy evaluation with noisy information," Journal of Monetary Economics, Elsevier, vol. 50(3), pages 605-631, April.
    36. Milani, Fabio, 2017. "Sentiment and the U.S. business cycle," Journal of Economic Dynamics and Control, Elsevier, vol. 82(C), pages 289-311.
    37. Ricco, Giovanni, 2015. "A new identification of fiscal shocks based on the information flow," Working Paper Series 1813, European Central Bank.
    38. Calvo, Guillermo A., 1983. "Staggered prices in a utility-maximizing framework," Journal of Monetary Economics, Elsevier, vol. 12(3), pages 383-398, September.
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    Cited by:

    1. Ambrocio, Gene, 2017. "The real effects of overconfidence and fundamental uncertainty shocks," Research Discussion Papers 37, Bank of Finland.
    2. Riccardo M. Masolo & Alessia Paccagnini, 2019. "Identifying Noise Shocks: A VAR with Data Revisions," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 51(8), pages 2145-2172, December.
    3. Dées, Stephane & Zimic, Srečko, 2019. "Animal spirits, fundamental factors and business cycle fluctuations," Journal of Macroeconomics, Elsevier, vol. 61(C), pages 1-1.
    4. repec:zbw:bofrdp:037 is not listed on IDEAS
    5. repec:zbw:bofrdp:2017_037 is not listed on IDEAS

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    More about this item

    Keywords

    Business cycles; information frictions; noise shocks; SVARs with sign restrictions;
    All these keywords.

    JEL classification:

    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation

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