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Log-concave Probability Distributions: Theory and Statistical Testing

Author

Listed:
  • Mark Yuying An

    (Duke University)

Abstract

This paper studies the broad class of log-concave probability distributions that arise in economics of uncertainty and information.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Mark Yuying An, 1996. "Log-concave Probability Distributions: Theory and Statistical Testing," Game Theory and Information 9611002, University Library of Munich, Germany.
    • Handle: RePEc:wpa:wuwpga:9611002
    Note: Type of Document - LaTex; prepared on UNIX Sparc TeX; to print on PostScript; pages: 31 ; figures: request from author. We never published this piece and now we would like to reduce our mailing and xerox cost by posting it.
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    References listed on IDEAS

    as
    1. Mark Bagnoli & Ted Bergstrom, 2006. "Log-concave probability and its applications," Studies in Economic Theory, in: Charalambos D. Aliprantis & Rosa L. Matzkin & Daniel L. McFadden & James C. Moore & Nicholas C. Yann (ed.), Rationality and Equilibrium, pages 217-241, Springer.
    2. Flinn, Christopher J & Heckman, James J, 1983. "Are Unemployment and Out of the Labor Force Behaviorally Distinct Labor Force States?," Journal of Labor Economics, University of Chicago Press, vol. 1(1), pages 28-42, January.
    3. Heckman, James J & Honore, Bo E, 1990. "The Empirical Content of the Roy Model," Econometrica, Econometric Society, vol. 58(5), pages 1121-1149, September.
    4. Burdett, Kenneth & Ondrich, Jan I, 1985. "How Changes in Labor Demand Affect Unemployed Workers," Journal of Labor Economics, University of Chicago Press, vol. 3(1), pages 1-10, January.
    5. Burdett, Kenneth, 1980. "How Changes in Labor Demand Affects Unemployed Workers," Working Paper Series 28, Research Institute of Industrial Economics.
    6. A. D. Roy, 1951. "Some Thoughts On The Distribution Of Earnings," Oxford Economic Papers, Oxford University Press, vol. 3(2), pages 135-146.
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    Cited by:

    1. Abdi, Me’raj & Madadi, Mohsen & Balakrishnan, Narayanaswamy & Jamalizadeh, Ahad, 2021. "Family of mean-mixtures of multivariate normal distributions: Properties, inference and assessment of multivariate skewness," Journal of Multivariate Analysis, Elsevier, vol. 181(C).
    2. Pedersen, Peder J. & Smith, Nina, 2001. "International Migration and Migration policy in Denmark," CLS Working Papers 01-5, University of Aarhus, Aarhus School of Business, Centre for Labour Market and Social Research.
    3. Rosholm, Michael & Toomet, Ott, 2005. "A Search Model of Discouragement," IZA Discussion Papers 1633, IZA Network @ LISER.
    4. Müller, Samuel & Rufibach, Kaspar, 2008. "On the max-domain of attraction of distributions with log-concave densities," Statistics & Probability Letters, Elsevier, vol. 78(12), pages 1440-1444, September.
    5. Wang, Jin, 2021. "Do birds of a feather flock together? Platform’s quality screening and end-users’ choices theory and empirical study of online trading platforms," International Journal of Industrial Organization, Elsevier, vol. 75(C).
    6. Ortega, J., 2000. "Job Rotation as a Mechanism for Learning," Papers 00-04, Centre for Labour Market and Social Research, Danmark-.
    7. Anup Malani, 2004. "Testing for Placebo Effects Using Data from Blinded, Randomized Controlled Trials," Econometric Society 2004 North American Summer Meetings 104, Econometric Society.
    8. Westergaard-Nielsen, Niels, 2001. "Danish Labour Market Policy: Is it worth it?," CLS Working Papers 01-10, University of Aarhus, Aarhus School of Business, Centre for Labour Market and Social Research.

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    Keywords

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    JEL classification:

    • D80 - Microeconomics - - Information, Knowledge, and Uncertainty - - - General
    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General

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