IDEAS home Printed from https://ideas.repec.org/p/wyi/wpaper/002036.html
   My bibliography  Save this paper

Generalized Maximum Entropy Estimation of Discrete Sequential Move Games of Perfect Information

Author

Listed:
  • Yafeng Wang
  • Brett Graham

Abstract

We propose a data-constrained generalized maximum entropy estimator for discrete sequential move games of perfect information. Unlike most other work on the estimation of complete information games, the method we proposed is data constrained and requires o simulation or assumptions about the distribution of random preference shocks. We formulate the GME estimation as a (convex) mixed-integer nonlinear optimization problem which can be easily implemented on optimization software with high-level interfaces such as GAMS. The model is identified with only weak scale and location normalizations. Monte Carlo evidence demonstrates that the estimator can perform well in moderately size samples. As an application we study the location choice of German siblings using the German Ageing Survey.

Suggested Citation

  • Yafeng Wang & Brett Graham, 2013. "Generalized Maximum Entropy Estimation of Discrete Sequential Move Games of Perfect Information," Working Papers 2013-10-14, Wang Yanan Institute for Studies in Economics (WISE), Xiamen University.
    • Handle: RePEc:wyi:wpaper:002036
    as

    Download full text from publisher

    File URL: https://econpub.xmu.edu.cn/research/repec/upload/20116301449277055475115776.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Joel L. Horowitz, 1998. "Bootstrap Methods for Median Regression Models," Econometrica, Econometric Society, vol. 66(6), pages 1327-1352, November.
    2. Che‐Lin Su & Kenneth L. Judd, 2012. "Constrained Optimization Approaches to Estimation of Structural Models," Econometrica, Econometric Society, vol. 80(5), pages 2213-2230, September.
    3. Bajari, Patrick & Hong, Han & Krainer, John & Nekipelov, Denis, 2010. "Estimating Static Models of Strategic Interactions," Journal of Business & Economic Statistics, American Statistical Association, vol. 28(4), pages 469-482.
    4. Berry, Steven T, 1992. "Estimation of a Model of Entry in the Airline Industry," Econometrica, Econometric Society, vol. 60(4), pages 889-917, July.
    5. Patrick Bajari & Han Hong & Stephen P. Ryan, 2010. "Identification and Estimation of a Discrete Game of Complete Information," Econometrica, Econometric Society, vol. 78(5), pages 1529-1568, September.
    6. Lee, Lung-Fei, 1995. "Asymptotic Bias in Simulated Maximum Likelihood Estimation of Discrete Choice Models," Econometric Theory, Cambridge University Press, vol. 11(3), pages 437-483, June.
    7. Golan, Amos & Judge, George G. & Miller, Douglas, 1996. "Maximum Entropy Econometrics," Staff General Research Papers Archive 1488, Iowa State University, Department of Economics.
    8. R. Carter Hill & Randall C. Campbell, 2001. "Maximum Entropy Estimation in Economic Models with Linear Inequality Restrictions," Departmental Working Papers 2001-11, Department of Economics, Louisiana State University.
    9. Jouneau-Sion, Frederic & Torres, Olivier, 2006. "MMC techniques for limited dependent variables models: Implementation by the branch-and-bound algorithm," Journal of Econometrics, Elsevier, vol. 133(2), pages 479-512, August.
    10. Kreps,David M. & Wallis,Kenneth F. (ed.), 1997. "Advances in Economics and Econometrics: Theory and Applications," Cambridge Books, Cambridge University Press, number 9780521589833, September.
    11. Martin J. Osborne & Ariel Rubinstein, 1994. "A Course in Game Theory," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262650401, April.
    12. Kreps,David M. & Wallis,Kenneth F. (ed.), 1997. "Advances in Economics and Econometrics: Theory and Applications," Cambridge Books, Cambridge University Press, number 9780521589819, September.
    13. Shiko Maruyama, 2009. "Estimating Sequential-move Games by a Recursive Conditioning Simulator," Discussion Papers 2009-01, School of Economics, The University of New South Wales.
    14. Michael J. Mazzeo, 2002. "Product Choice and Oligopoly Market Structure," RAND Journal of Economics, The RAND Corporation, vol. 33(2), pages 221-242, Summer.
    15. Golan, Amos & Judge, George & Perloff, Jeffrey, 1997. "Estimation and inference with censored and ordered multinomial response data," Journal of Econometrics, Elsevier, vol. 79(1), pages 23-51, July.
    16. Kreps,David M. & Wallis,Kenneth F. (ed.), 1997. "Advances in Economics and Econometrics: Theory and Applications," Cambridge Books, Cambridge University Press, number 9780521589826, September.
    17. Philipp Schmidt-Dengler, 2006. "The Timing of New Technology Adoption: The Case of MRI," 2006 Meeting Papers 3, Society for Economic Dynamics.
    Full references (including those not matched with items on IDEAS)

    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. Wang, Yafeng & Graham, Brett, 2009. "Generalized Maximum Entropy estimation of discrete sequential move games of perfect information," MPRA Paper 21331, University Library of Munich, Germany.
    2. Wang, Yafeng & Graham, Brett, 2010. "Simulation Based Estimation of Discrete Sequential Move Games of Perfect Information," MPRA Paper 23153, University Library of Munich, Germany.
    3. Shiko Maruyama, 2009. "Estimating Sequential-move Games by a Recursive Conditioning Simulator," Discussion Papers 2009-01, School of Economics, The University of New South Wales.
    4. R. Carter Hill & Randall C. Campbell, 2001. "Maximum Entropy Estimation in Economic Models with Linear Inequality Restrictions," Departmental Working Papers 2001-11, Department of Economics, Louisiana State University.
    5. Dufour, Jean-Marie, 2006. "Monte Carlo tests with nuisance parameters: A general approach to finite-sample inference and nonstandard asymptotics," Journal of Econometrics, Elsevier, vol. 133(2), pages 443-477, August.
    6. Kristensen, Dennis & Shin, Yongseok, 2012. "Estimation of dynamic models with nonparametric simulated maximum likelihood," Journal of Econometrics, Elsevier, vol. 167(1), pages 76-94.
    7. Asheim, Geir B., 2002. "On the epistemic foundation for backward induction," Mathematical Social Sciences, Elsevier, vol. 44(2), pages 121-144, November.
    8. Drew Fudenberg, 2006. "Advancing Beyond Advances in Behavioral Economics," Journal of Economic Literature, American Economic Association, vol. 44(3), pages 694-711, September.
    9. Doug J. Chung & Kyoungwon Seo & Reo Song, 2023. "Efficient computation of discrete games: Estimating the effect of Apple on market structure," Production and Operations Management, Production and Operations Management Society, vol. 32(7), pages 2245-2263, July.
    10. A. Orhun, 2013. "Spatial differentiation in the supermarket industry: The role of common information," Quantitative Marketing and Economics (QME), Springer, vol. 11(1), pages 3-37, March.
    11. Daniel Ackerberg, 2009. "A new use of importance sampling to reduce computational burden in simulation estimation," Quantitative Marketing and Economics (QME), Springer, vol. 7(4), pages 343-376, December.
    12. Gong, X. & van Soest, A.H.O. & Zhang, P., 2000. "Sexual Bias and Household Consumption : A Semiparametic Analysis of Engel curves in Rural China," Discussion Paper 2000-45, Tilburg University, Center for Economic Research.
    13. Masahiko Aoki, 2013. "Endogenizing institutions and institutional changes," Chapters, in: Comparative Institutional Analysis, chapter 16, pages 267-297, Edward Elgar Publishing.
    14. Xiao Luo, 2016. "Rational beliefs in rationalizability," Theory and Decision, Springer, vol. 81(2), pages 189-198, August.
    15. Joel L. Horowitz, 2018. "Bootstrap Methods in Econometrics," Papers 1809.04016, arXiv.org.
    16. Oliver Board, 2002. "Algorithmic Characterization of Rationalizability in Extensive Form Games," Working Paper 244, Department of Economics, University of Pittsburgh, revised Jan 2002.
    17. Whang, Yoon-Jae, 2006. "Smoothed Empirical Likelihood Methods For Quantile Regression Models," Econometric Theory, Cambridge University Press, vol. 22(2), pages 173-205, April.
    18. Moscati Ivan, 2009. "Interactive and common knowledge in the state-space model," CESMEP Working Papers 200903, University of Turin.
    19. Joel L. Horowitz, 2018. "Bootstrap methods in econometrics," CeMMAP working papers CWP53/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    20. Masahiko Aoki, 2006. "Mechanisms of Endogenous Institutional Change," Discussion Papers 05-013, Stanford Institute for Economic Policy Research.

    More about this item

    Keywords

    Game-Theoretic Econometric Models; Sequential-Move Game; Generalized ，Maximum Entropy; Mixed-Integer Nonlinear Programming.;
    All these keywords.

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C72 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Noncooperative Games

    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:wyi:wpaper:002036. See general information about how to correct material in RePEc.

    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: WISE Technical Team (email available below). General contact details of provider: https://www.wise.xmu.edu.cn/english/ .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.