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Expectations with Unrealistic Optimism: An Empirical Application

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  • Brea, Humberto
  • Grifell-Tatje, Emili
  • Orea, Luis

Abstract

Several studies claim that people have a tendency to be overoptimistic (Coelho;2010; Lovallo & Kahnenman, 2003). Furthermore, some researchers suggest that optimism could be prevalent in managers as a result of the selection process (Heaton, 2002). Nevertheless, there is very little literature about the subject of optimism and managerial decisions (Coelho, 2010). In this study we present a frontier model of expectations with an optimistic bias based on the adaptive expectation model. In our framework, optimism is considered as a positive random term which skews expectations from a normal forecast based on rational assumptions. We model investment decision based on expectations about key variables such as sales or cash flow. We posit that managers have a skewed viewpoint of reality. An application of the empirical model in the context of the American retail industry is provided. This paper contributes to increasing the literature about unrealistic optimism as well as applying productivity and efficiency techniques in the management field.

Suggested Citation

  • Brea, Humberto & Grifell-Tatje, Emili & Orea, Luis, 2012. "Expectations with Unrealistic Optimism: An Empirical Application," Efficiency Series Papers 2012/01, University of Oviedo, Department of Economics, Oviedo Efficiency Group (OEG).
  • Handle: RePEc:oeg:wpaper:2012/01
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    References listed on IDEAS

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    1. Hansen, Bruce E., 1999. "Threshold effects in non-dynamic panels: Estimation, testing, and inference," Journal of Econometrics, Elsevier, vol. 93(2), pages 345-368, December.
    2. Anand M. Goel & Anjan V. Thakor, 2008. "Overconfidence, CEO Selection, and Corporate Governance," Journal of Finance, American Finance Association, vol. 63(6), pages 2737-2784, December.
    3. Levine, David I, 1993. "Do Corporate Executives Have Rational Expectations?," The Journal of Business, University of Chicago Press, vol. 66(2), pages 271-293, April.
    4. Kumbhakar, Subal C., 1990. "Production frontiers, panel data, and time-varying technical inefficiency," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 201-211.
    5. Hung-jen Wang & Peter Schmidt, 2002. "One-Step and Two-Step Estimation of the Effects of Exogenous Variables on Technical Efficiency Levels," Journal of Productivity Analysis, Springer, vol. 18(2), pages 129-144, September.
    6. Wang, Hung-Jen & Ho, Chia-Wen, 2010. "Estimating fixed-effect panel stochastic frontier models by model transformation," Journal of Econometrics, Elsevier, vol. 157(2), pages 286-296, August.
    7. Coelho, Marta, 2010. "Unrealistic optimism: still a neglected trait," LSE Research Online Documents on Economics 29133, London School of Economics and Political Science, LSE Library.
    8. Hackbarth, Dirk, 2008. "Managerial Traits and Capital Structure Decisions," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 43(4), pages 843-881, December.
    9. Roll, Richard, 1986. "The Hubris Hypothesis of Corporate Takeovers," The Journal of Business, University of Chicago Press, vol. 59(2), pages 197-216, April.
    10. Papenhausen, Chris, 2010. "Managerial optimism and search," Journal of Business Research, Elsevier, vol. 63(7), pages 716-720, July.
    11. Stevenson, Rodney E., 1980. "Likelihood functions for generalized stochastic frontier estimation," Journal of Econometrics, Elsevier, vol. 13(1), pages 57-66, May.
    12. Antonio Alvarez & Christine Amsler & Luis Orea & Peter Schmidt, 2006. "Interpreting and Testing the Scaling Property in Models where Inefficiency Depends on Firm Characteristics," Journal of Productivity Analysis, Springer, vol. 25(3), pages 201-212, June.
    13. Yélou, Clément & Larue, Bruno & Tran, Kien C., 2010. "Threshold effects in panel data stochastic frontier models of dairy production in Canada," Economic Modelling, Elsevier, vol. 27(3), pages 641-647, May.
    14. Emek Basker, 2011. "Does Wal‐Mart Sell Inferior Goods?," Economic Inquiry, Western Economic Association International, vol. 49(4), pages 973-981, October.
    15. Luis Orea & Subal C. Kumbhakar, 2004. "Efficiency measurement using a latent class stochastic frontier model," Empirical Economics, Springer, vol. 29(1), pages 169-183, January.
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