IDEAS home Printed from https://ideas.repec.org/p/bcb/wpaper/418.html
   My bibliography  Save this paper

What drives inflation expectations in Brazil? Public versus private information

Author

Listed:
  • Waldyr D. Areosa

Abstract

This article applies a noisy information model with strategic interactions à la Morris and Shin (2002) to a panel from the Central Bank of Brazil Market Expectations System to provide evidence of how professional forecasters weight private and public information when building inflation expectations in Brazil. The main results are: (i) forecasters attach more weight to public information than private information because (ii) public information is more precise than private information. Nevertheless, (iii) forecasters overweight private information in order to (iv) differentiate themselves from each other (strategic substitutability)

Suggested Citation

  • Waldyr D. Areosa, 2016. "What drives inflation expectations in Brazil? Public versus private information," Working Papers Series 418, Central Bank of Brazil, Research Department.
  • Handle: RePEc:bcb:wpaper:418
    as

    Download full text from publisher

    File URL: https://www.bcb.gov.br/pec/wps/ingl/wps418.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Korenok, Oleg, 2008. "Empirical comparison of sticky price and sticky information models," Journal of Macroeconomics, Elsevier, vol. 30(3), pages 906-927, September.
    2. Yara de Almeida Campos Cordeiro & Wagner Piazza Gaglianone & João Victor Issler, 2017. "Inattention in individual expectations," Economia, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics], vol. 17(1), pages 40-59.
    3. Andrade, Philippe & Le Bihan, Hervé, 2013. "Inattentive professional forecasters," Journal of Monetary Economics, Elsevier, vol. 60(8), pages 967-982.
    4. 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.
    5. Olivier Coibion, 2010. "Testing the Sticky Information Phillips Curve," The Review of Economics and Statistics, MIT Press, vol. 92(1), pages 87-101, February.
    6. 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, Oxford University Press, vol. 117(4), pages 1295-1328.
    7. Michael T. Kiley, 2007. "A Quantitative Comparison of Sticky-Price and Sticky-Information Models of Price Setting," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(s1), pages 101-125, February.
    8. Areosa, Marta B. M. & Areosa, Waldyr D. & Carrasco, Vinicius, 2020. "A Sticky–Dispersed Information Phillips Curve: A Model With Partial And Delayed Information," Macroeconomic Dynamics, Cambridge University Press, vol. 24(4), pages 747-773, June.
    9. Thompson, Samuel B., 2011. "Simple formulas for standard errors that cluster by both firm and time," Journal of Financial Economics, Elsevier, vol. 99(1), pages 1-10, January.
    10. Marta Areosa & Waldyr Areosa, 2012. "Asset Prices and Monetary Policy – A sticky-dispersed information model," Working Papers Series 285, Central Bank of Brazil, Research Department.
    11. Christopher D. Carroll, 2003. "Macroeconomic Expectations of Households and Professional Forecasters," The Quarterly Journal of Economics, Oxford University Press, vol. 118(1), pages 269-298.
    12. Klenow, Peter J. & Willis, Jonathan L., 2007. "Sticky information and sticky prices," Journal of Monetary Economics, Elsevier, vol. 54(Supplemen), pages 79-99, September.
    13. Bulow, Jeremy I & Geanakoplos, John D & Klemperer, Paul D, 1985. "Multimarket Oligopoly: Strategic Substitutes and Complements," Journal of Political Economy, University of Chicago Press, vol. 93(3), pages 488-511, June.
    14. Bill Dupor & Tomiyuki Kitamura & Takayuki Tsuruga, 2010. "Integrating Sticky Prices and Sticky Information," The Review of Economics and Statistics, MIT Press, vol. 92(3), pages 657-669, August.
    15. Maćkowiak, Bartosz & Moench, Emanuel & Wiederholt, Mirko, 2009. "Sectoral price data and models of price setting," Journal of Monetary Economics, Elsevier, vol. 56(S), pages 78-99.
    16. George-Marios Angeletos & Alessandro Pavan, 2007. "Efficient Use of Information and Social Value of Information," Econometrica, Econometric Society, vol. 75(4), pages 1103-1142, July.
    17. Lena Dräger & Michael Lamla, 2013. "Imperfect Information and Inflation Expectations: Evidence from Microdata," Macroeconomics and Finance Series 201301, University of Hamburg, Department of Socioeconomics.
    18. 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.
    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. Wagner Piazza Gaglianone, 2017. "Empirical Findings on Inflation Expectations in Brazil: a survey," Working Papers Series 464, Central Bank of Brazil, Research Department.
    2. Cambara, Leilane de Freitas Rocha & Meurer, Roberto & Lima, Gilberto Tadeu, 2022. "Deviating from full rationality but not from theoretical consistency: The behavior of inflation expectations in Brazil," The Quarterly Review of Economics and Finance, Elsevier, vol. 84(C), pages 492-501.
    3. Joscha Beckmann & Ansgar Belke & Irina Dubova, 2022. "What drives updates of inflation expectations? A Bayesian VAR analysis for the G‐7 countries," The World Economy, Wiley Blackwell, vol. 45(9), pages 2748-2765, September.

    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. Andrade, Philippe & Le Bihan, Hervé, 2013. "Inattentive professional forecasters," Journal of Monetary Economics, Elsevier, vol. 60(8), pages 967-982.
    2. Carrillo, Julio A., 2012. "How well does sticky information explain the dynamics of inflation, output, and real wages?," Journal of Economic Dynamics and Control, Elsevier, vol. 36(6), pages 830-850.
    3. Carrera, César & Ramírez-Rondán, N.R., 2019. "Inflation, Information Rigidity, And The Sticky Information Phillips Curve," Macroeconomic Dynamics, Cambridge University Press, vol. 23(7), pages 2597-2615, October.
    4. 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.
    5. Yara de Almeida Campos Cordeiro & Wagner Piazza Gaglianone & João Victor Issler, 2017. "Inattention in individual expectations," Economia, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics], vol. 17(1), pages 40-59.
    6. 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.
    7. James M. Nason & Gregor W. Smith, 2021. "Measuring the slowly evolving trend in US inflation with professional forecasts," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(1), pages 1-17, January.
    8. Kim, Insu & Kim, Young Se, 2019. "Inattentive agents and inflation forecast error dynamics: A Bayesian DSGE approach," Journal of Macroeconomics, Elsevier, vol. 62(C).
    9. Paul Hubert & Harun Mirza, 2019. "The role of forward‐ and backward‐looking information for inflation expectations formation," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 38(8), pages 733-748, December.
    10. Bredemeier, Christian & Goecke, Henry, 2011. "Sticky Prices vs. Sticky Information – A Cross-Country Study of Inflation Dynamics," Ruhr Economic Papers 255, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    11. repec:zbw:rwirep:0255 is not listed on IDEAS
    12. Carrera Cesar, 2012. "Estimating Information Rigidity Using Firms' Survey Data," The B.E. Journal of Macroeconomics, De Gruyter, vol. 12(1), pages 1-34, June.
    13. 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.
    14. Yingying Xu & Zhixin Liu & Zichao Jia & Chi-Wei Su, 2017. "Is time-variant information stickiness state-dependent?," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 16(3), pages 169-187, December.
    15. Christian Bredemeier & Henry Goecke, 2011. "Sticky Prices vs. Sticky Information – A Cross-Country Study of Inflation Dynamics," Ruhr Economic Papers 0255, Rheinisch-Westfälisches Institut für Wirtschaftsforschung, Ruhr-Universität Bochum, Universität Dortmund, Universität Duisburg-Essen.
    16. Christian Gillitzer, 2016. "The Sticky Information Phillips Curve: Evidence for Australia," The Economic Record, The Economic Society of Australia, vol. 92(299), pages 548-567, December.
    17. Arslan, M. Murat, 2010. "Relative importance of sticky prices and sticky information in price setting," Economic Modelling, Elsevier, vol. 27(5), pages 1124-1135, September.
    18. James M. Nason & Gregor W. Smith, 2013. "Reverse Kalman filtering U.S. inflation with sticky professional forecasts," Working Papers 13-34, Federal Reserve Bank of Philadelphia.
    19. George-Marios Angeletos & Chen Lian, 2016. "Incomplete Information in Macroeconomics: Accommodating Frictions in Coordination," NBER Working Papers 22297, National Bureau of Economic Research, Inc.
    20. Gomes, Orlando, 2012. "Thought experimentation and the Phillips curve," Research in Economics, Elsevier, vol. 66(1), pages 45-64.
    21. Paul Hubert, 2014. "FOMC Forecasts as a Focal Point for Private Expectations," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 46(7), pages 1381-1420, October.

    More about this item

    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:bcb:wpaper:418. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: . General contact details of provider: https://www.bcb.gov.br/?english .

    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: Rodrigo Barbone Gonzalez (email available below). General contact details of provider: https://www.bcb.gov.br/?english .

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.