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Learning, Forecasting and Optimizing: an Experimental Study

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  • Bao, T.

    ()
    (University of Amsterdam)

  • Duffy, J.

    (University of Pittsburgh)

  • Hommes, C.H.

    ()
    (University of Amsterdam)

Abstract

Rational Expectations (RE) models have two crucial dimensions: 1) agents correctly forecast future prices given all available information, and 2) given expectations, agents solve optimization problems and these solutions in turn determine actual price realizations. Experimental testing of such models typically focuses on only one of these two dimensions. In this paper we consider both forecasting and optimization decisions in an experimental cobweb economy. We report results from four experimental treatments: 1) subjects form forecasts only, 2) subjects determine quantity only (solve an optimization problem), 3) they do both and 4) they are paired in teams and one member is assigned the forecasting role while the other is assigned the optimization task. All treatments converges to Rational Expectation Equilibrium (REE), but the at very different speed. We observe that performance is the best in treatment 1) and worst in the treatment 3). Most forecasters use an adaptive expectations rule. Subjects are less likely to make conditionally optimal production decision for given forecasts in treatment 3) where the forecast is made by themselves, than treatment 4) where the forecast is made by the other member of the team, which confirms ``two heads are better than one" in finding REE.

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Bibliographic Info

Paper provided by Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance in its series CeNDEF Working Papers with number 11-08.

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Date of creation: 2011
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Handle: RePEc:ams:ndfwpp:11-08

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Postal: Dept. of Economics and Econometrics, Universiteit van Amsterdam, Roetersstraat 11, NL - 1018 WB Amsterdam, The Netherlands
Phone: + 31 20 525 52 58
Fax: + 31 20 525 52 83
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Web page: http://www.fee.uva.nl/cendef/
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Citations

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Cited by:
  1. Bao, T. & Hommes, C.H. & Makarewicz, T.A., 2014. "Bubble Formation and (In)efficient Markets in Learning-to-Forecast and -Optimize Experiments," CeNDEF Working Papers 14-01, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
  2. Bao, Te & Duffy, John, 2014. "Adaptive vs. eductive learning: Theory and evidence," Research Report 14002-EEF, University of Groningen, Research Institute SOM (Systems, Organisations and Management).
  3. Wolfgang Luhan & Johann Scharler, 2013. "Monetary Policy, Inflation Illusion and the Taylor Principle: An Experimental Study," Working Papers 2013-03, Faculty of Economics and Statistics, University of Innsbruck.
  4. Jasmina Arifovic & George Evans & Olena Kostyshyna, 2013. "Are Sunspots Learnable? An Experimental Investigation in a Simple General-Equilibrium Model," Working Papers 13-14, Bank of Canada.

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