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Costly Information Processing and Income Expectations

Author

Listed:
  • Daniel Gutknecht

    () (Oxford University)

  • Stefan Hoderlein

    (Boston College)

  • Michael Peters

    () (Yale University)

Abstract

Do individuals use all information at their disposal when forming expectations about future events? In this paper we present an econometric framework to answer this question. We show how individual information sets can be characterized by simple nonparametric exclusion restrictions and provide a quantile based test for costly information processing. In particular, our methodology does not require individuals' expectations to be rational, and we explicitly allow for individuals to have access to sources of information which the econometrician cannot observe. As an application, we use microdata on individual income expectations to study the information agents employ when forecasting future earnings. Consistent with models where information processing is costly, we find that individuals' information sets are coarse in that valuable information is discarded. To quantify the utility costs, we calibrate a standard consumption life-cycle model. Consumers would be willing to pay 0.04% of their permanent income to incorporate the econometrician’s information set in their forecasts. This represents a lower bound on the costs of information processing.

Suggested Citation

  • Daniel Gutknecht & Stefan Hoderlein & Michael Peters, 2014. "Costly Information Processing and Income Expectations," Boston College Working Papers in Economics 861, Boston College Department of Economics.
  • Handle: RePEc:boc:bocoec:861
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    References listed on IDEAS

    as
    1. 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.
    2. Fatih Guvenen, 2007. "Learning Your Earning: Are Labor Income Shocks Really Very Persistent?," American Economic Review, American Economic Association, vol. 97(3), pages 687-712, June.
    3. 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.
    4. Jappelli, Tullio & Pistaferri, Luigi, 2000. "Using subjective income expectations to test for excess sensitivity of consumption to predicted income growth," European Economic Review, Elsevier, vol. 44(2), pages 337-358, February.
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    More about this item

    Keywords

    Rational Expectations; Bounded Rationality; Information Set; Costly Information; Consumption;

    JEL classification:

    • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • D91 - Microeconomics - - Micro-Based Behavioral Economics - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making

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