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Inattention in Individual Expectations


  • Yara de Almeida Campos Cordeiro
  • Wagner Piazza Gaglianone
  • João Victor Issler


This paper investigates the expectations formation process of economic agents about inflation rate. Using the Market Expectations System of Central Bank of Brazil, we perceive that agents do not update their forecasts every period and that even agents who update disagree in their predictions. We then focus on the two most popular types of inattention models that have been discussed in the recent literature: sticky-information and noisy-information models. Estimating a hybrid model we find that, although formally fitting the Brazilian data, it happens at the cost of a much higher degree of information rigidity than observed

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  • Yara de Almeida Campos Cordeiro & Wagner Piazza Gaglianone & João Victor Issler, 2015. "Inattention in Individual Expectations," Working Papers Series 395, Central Bank of Brazil, Research Department.
  • Handle: RePEc:bcb:wpaper:395

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    References listed on IDEAS

    1. Reis, Ricardo, 2006. "Inattentive consumers," Journal of Monetary Economics, Elsevier, vol. 53(8), pages 1761-1800, November.
    2. Ricardo Reis, 2006. "Inattentive Producers," Review of Economic Studies, Oxford University Press, vol. 73(3), pages 793-821.
    3. Andrade, Philippe & Le Bihan, Hervé, 2013. "Inattentive professional forecasters," Journal of Monetary Economics, Elsevier, vol. 60(8), pages 967-982.
    4. Moscarini, Giuseppe, 2004. "Limited information capacity as a source of inertia," Journal of Economic Dynamics and Control, Elsevier, vol. 28(10), pages 2003-2035, September.
    5. 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.
    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. 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.
    8. 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.
    9. Marta Areosa & Waldyr Areosa & Vinicius Carrasco, 2010. "A Sticky-Dispersed Information Phillips Curve: A model with partial and delayed information," Textos para discussão 565, Department of Economics PUC-Rio (Brazil).
    10. Andrade, Philippe & Crump, Richard K. & Eusepi, Stefano & Moench, Emanuel, 2016. "Fundamental disagreement," Journal of Monetary Economics, Elsevier, vol. 83(C), pages 106-128.
    11. Sims, Christopher A., 2003. "Implications of rational inattention," Journal of Monetary Economics, Elsevier, vol. 50(3), pages 665-690, April.
    12. Patton, Andrew J. & Timmermann, Allan, 2010. "Why do forecasters disagree? Lessons from the term structure of cross-sectional dispersion," Journal of Monetary Economics, Elsevier, vol. 57(7), pages 803-820, October.
    13. 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.
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    Cited by:

    1. Waldyr D. Areosa, 2016. "What drives inflation expectations in Brazil? Public versus private information," Working Papers Series 418, Central Bank of Brazil, Research Department.
    2. repec:spr:empeco:v:53:y:2017:i:1:d:10.1007_s00181-016-1163-8 is not listed on IDEAS
    3. Wagner Piazza Gaglianone, 2017. "Empirical Findings on Inflation Expectations in Brazil: a survey," Working Papers Series 464, Central Bank of Brazil, Research Department.
    4. Wagner Piazza Gaglianone & João Victor Issler & Silvia Maria Matos, 2017. "Applying a microfounded-forecasting approach to predict Brazilian inflation," Empirical Economics, Springer, vol. 53(1), pages 137-163, August.

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