IDEAS home Printed from https://ideas.repec.org/p/een/camaaa/2021-48.html
   My bibliography  Save this paper

Identifying the source of information rigidities in the expectations formation process

Author

Listed:
  • Mototsugu Shintani
  • Kozo Ueda

Abstract

Coibion and Gorodnichenko (2015) provide a useful framework to test the null hypothesis of full-information rational expectations against two popular classes of information rigidities, sticky information (SI) and noisy information (NI). However, the observational equivalence of SI and NI in average forecast errors gives no power in the test for one against the other. We identify the source of information rigidities by estimating the equations for the average forecast errors and variance of forecasts. The results show the importance of both SI and NI, but favor a type of NI in which agents quickly learn the underlying state.

Suggested Citation

  • Mototsugu Shintani & Kozo Ueda, 2021. "Identifying the source of information rigidities in the expectations formation process," CAMA Working Papers 2021-48, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  • Handle: RePEc:een:camaaa:2021-48
    as

    Download full text from publisher

    File URL: https://cama.crawford.anu.edu.au/sites/default/files/publication/cama_crawford_anu_edu_au/2021-06/48_2021_shintani_ueda.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Hur, Joonyoung & Kim, Insu, 2016. "Information rigidities in survey data: Evidence from dispersions in forecasts and forecast revisions," Economics Letters, Elsevier, vol. 142(C), pages 10-14.
    2. N. Gregory Mankiw & Ricardo Reis, 2002. "Sticky Information versus Sticky Prices: A Proposal to Replace the New Keynesian Phillips Curve," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 117(4), pages 1295-1328.
    3. Pedro Bordalo & Nicola Gennaioli & Yueran Ma & Andrei Shleifer, 2020. "Overreaction in Macroeconomic Expectations," American Economic Review, American Economic Association, vol. 110(9), pages 2748-2782, September.
    4. Crucini, Mario J. & Shintani, Mototsugu & Tsuruga, Takayuki, 2015. "Noisy information, distance and law of one price dynamics across US cities," Journal of Monetary Economics, Elsevier, vol. 74(C), pages 52-66.
    5. George-Marios Angeletos & Zhen Huo & Karthik A. Sastry, 2021. "Imperfect Macroeconomic Expectations: Evidence and Theory," NBER Macroeconomics Annual, University of Chicago Press, vol. 35(1), pages 1-86.
    6. N. Gregory Mankiw & Ricardo Reis & Justin Wolfers, 2004. "Disagreement about Inflation Expectations," NBER Chapters, in: NBER Macroeconomics Annual 2003, Volume 18, pages 209-270, National Bureau of Economic Research, Inc.
    7. Olivier Coibion & Yuriy Gorodnichenko, 2012. "What Can Survey Forecasts Tell Us about Information Rigidities?," Journal of Political Economy, University of Chicago Press, vol. 120(1), pages 116-159.
    8. Donald W. K. Andrews, 1999. "Consistent Moment Selection Procedures for Generalized Method of Moments Estimation," Econometrica, Econometric Society, vol. 67(3), pages 543-564, May.
    9. Crucini, Mario J. & Shintani, Mototsugu & Tsuruga, Takayuki, 2010. "Accounting for persistence and volatility of good-level real exchange rates: The role of sticky information," Journal of International Economics, Elsevier, vol. 81(1), pages 48-60, May.
    10. Tobias Broer & Alexandre L. Kholhas, 2022. "Forecaster (Mis-) behavior," Post-Print halshs-03956330, HAL.
    11. Smith, Richard J, 1992. "Non-nested.Tests for Competing Models Estimated by Generalized Method of Moments," Econometrica, Econometric Society, vol. 60(4), pages 973-980, July.
    12. Jeffrey C. Fuhrer, 2018. "Intrinsic expectations persistence: evidence from professional and household survey expectations," Working Papers 18-9, Federal Reserve Bank of Boston.
    13. Olivier Coibion & Yuriy Gorodnichenko, 2015. "Information Rigidity and the Expectations Formation Process: A Simple Framework and New Facts," American Economic Review, American Economic Association, vol. 105(8), pages 2644-2678, August.
    14. Branch, William A., 2007. "Sticky information and model uncertainty in survey data on inflation expectations," Journal of Economic Dynamics and Control, Elsevier, vol. 31(1), pages 245-276, January.
    15. Angeletos, George-Marios & La’O, Jennifer, 2009. "Incomplete information, higher-order beliefs and price inertia," Journal of Monetary Economics, Elsevier, vol. 56(S), pages 19-37.
    16. Andrade, Philippe & Le Bihan, Hervé, 2013. "Inattentive professional forecasters," Journal of Monetary Economics, Elsevier, vol. 60(8), pages 967-982.
    17. Alexandre N. Kohlhas & Ansgar Walther, 2021. "Asymmetric Attention," American Economic Review, American Economic Association, vol. 111(9), pages 2879-2925, September.
    18. Tobias Broer & Alexandre L. Kholhas, 2022. "Forecaster (Mis-) behavior," PSE-Ecole d'économie de Paris (Postprint) halshs-03956330, HAL.
    19. Lucas, Robert Jr., 1972. "Expectations and the neutrality of money," Journal of Economic Theory, Elsevier, vol. 4(2), pages 103-124, April.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Born, Benjamin & Enders, Zeno & Müller, Gernot J., 2023. "On FIRE, news, and expectations," Working Papers 42, German Research Foundation's Priority Programme 1859 "Experience and Expectation. Historical Foundations of Economic Behaviour", Humboldt University Berlin.
    2. Toshitaka Sekine & Frank Packer & Shunichi Yoneyama, 2022. "Individual Trend Inflation," IMES Discussion Paper Series 22-E-14, Institute for Monetary and Economic Studies, Bank of Japan.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Conrad, Christian & Lahiri, Kajal, 2023. "Heterogeneous expectations among professional forecasters," ZEW Discussion Papers 23-062, ZEW - Leibniz Centre for European Economic Research.
    2. Zhao Han & Xiaohan Ma & Ruoyun Mao, 2023. "The Role of Dispersed Information in Inflation and Inflation Expectations," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 48, pages 72-106, April.
    3. Angeletos, G.-M. & Lian, C., 2016. "Incomplete Information in Macroeconomics," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 1065-1240, Elsevier.
    4. Andrade, Philippe & Gautier, Erwan & Mengus, Eric, 2023. "What matters in households’ inflation expectations?," Journal of Monetary Economics, Elsevier, vol. 138(C), pages 50-68.
    5. Bernardo Candia & Olivier Coibion & Yuriy Gorodnichenko, 2021. "The Inflation Expectations of U.S. Firms: Evidence from a new survey," NBER Working Papers 28836, National Bureau of Economic Research, Inc.
    6. Bernardo Candia & Olivier Coibion & Yuriy Gorodnichenko, 2020. "Communication and the Beliefs of Economic Agents," NBER Working Papers 27800, National Bureau of Economic Research, Inc.
    7. Czudaj, Robert L., 2022. "Heterogeneity of beliefs and information rigidity in the crude oil market: Evidence from survey data," European Economic Review, Elsevier, vol. 143(C).
    8. J. Daniel Aromí & Martín Llada, 2024. "Are professional forecasters inattentive to public discussions? The case of inflation in Argentina," Working Papers 300, Red Nacional de Investigadores en Economía (RedNIE).
    9. George-Marios Angeletos & Chen Lian, 2016. "Incomplete Information in Macroeconomics: Accommodating Frictions in Coordination," NBER Working Papers 22297, National Bureau of Economic Research, Inc.
    10. An, Zidong & Zheng, Xinye, 2023. "Diligent forecasters can make accurate predictions despite disagreeing with the consensus," Economic Modelling, Elsevier, vol. 125(C).
    11. Camille Cornand & Paul Hubert, 2021. "Information frictions in inflation expectations among five types of economic agents," Working Papers halshs-03351632, HAL.
    12. Jean-Paul L'Huillier & Sanjay R. Singh & Donghoon Yoo, 2021. "Incorporating Diagnostic Expectations into the New Keynesian Framework," Working Papers 339, University of California, Davis, Department of Economics.
    13. Osnat Zohar, 2021. "Cyclicality of Uncertainty and Disagreement," Bank of Israel Working Papers 2021.09, Bank of Israel.
    14. Hagenhoff, Tim & Lustenhouwer, Joep, 2023. "The role of stickiness, extrapolation and past consensus forecasts in macroeconomic expectations," Journal of Economic Dynamics and Control, Elsevier, vol. 149(C).
    15. Cornand, Camille & Hubert, Paul, 2022. "Information frictions across various types of inflation expectations," European Economic Review, Elsevier, vol. 146(C).
    16. Olivier Coibion & Yuriy Gorodnichenko, 2015. "Information Rigidity and the Expectations Formation Process: A Simple Framework and New Facts," American Economic Review, American Economic Association, vol. 105(8), pages 2644-2678, August.
    17. Andrade, Philippe & Crump, Richard K. & Eusepi, Stefano & Moench, Emanuel, 2016. "Fundamental disagreement," Journal of Monetary Economics, Elsevier, vol. 83(C), pages 106-128.
    18. Hur, Joonyoung & Kim, Insu, 2016. "Information rigidities in survey data: Evidence from dispersions in forecasts and forecast revisions," Economics Letters, Elsevier, vol. 142(C), pages 10-14.
    19. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    20. Andrade, Philippe & Le Bihan, Hervé, 2013. "Inattentive professional forecasters," Journal of Monetary Economics, Elsevier, vol. 60(8), pages 967-982.

    More about this item

    Keywords

    imperfect information; heterogeneity; sticky information; noisy information; observational equivalence;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations
    • E13 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Neoclassical
    • 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

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:een:camaaa:2021-48. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Cama Admin (email available below). General contact details of provider: https://edirc.repec.org/data/asanuau.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.