IDEAS home Printed from https://ideas.repec.org/p/tse/wpaper/124826.html
   My bibliography  Save this paper

On the cost of Bayesian posterior mean strategy for log-concave models

Author

Listed:
  • Gadat, Sébastien
  • Panloup, Fabien
  • Pellegrini, C.

Abstract

No abstract is available for this item.

Suggested Citation

  • Gadat, Sébastien & Panloup, Fabien & Pellegrini, C., 2020. "On the cost of Bayesian posterior mean strategy for log-concave models," TSE Working Papers 20-1155, Toulouse School of Economics (TSE), revised Feb 2022.
    • Handle: RePEc:tse:wpaper:124826
    as

    Download full text from publisher

    File URL: https://www.tse-fr.eu/sites/default/files/TSE/documents/doc/wp/2020/wp_tse_1155.pdf
    File Function: Full Text
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Pagès, Gilles & Panloup, Fabien, 2014. "A mixed-step algorithm for the approximation of the stationary regime of a diffusion," Stochastic Processes and their Applications, Elsevier, vol. 124(1), pages 522-565.
    2. Heckman, James J & Honore, Bo E, 1990. "The Empirical Content of the Roy Model," Econometrica, Econometric Society, vol. 58(5), pages 1121-1149, September.
    3. Caplin, Andrew & Nalebuff, Barry, 1991. "Aggregation and Social Choice: A Mean Voter Theorem," Econometrica, Econometric Society, vol. 59(1), pages 1-23, January.
    4. Caplin, Andrew & Nalebuff, Barry, 1991. "Aggregation and Imperfect Competition: On the Existence of Equilibrium," Econometrica, Econometric Society, vol. 59(1), pages 25-59, January.
    5. Laffont, Jean-Jacques & Tirole, Jean, 1988. "The Dynamics of Incentive Contracts," Econometrica, Econometric Society, vol. 56(5), pages 1153-1175, September.
    6. 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.
    7. Arnak S. Dalalyan, 2017. "Theoretical guarantees for approximate sampling from smooth and log-concave densities," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 79(3), pages 651-676, June.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Crespo, Marelys & Gadat, Sébastien & Gendre, Xavier, 2023. "Stochastic Langevin Monte Carlo for (weakly) log-concave posterior distributions," TSE Working Papers 23-1398, Toulouse School of Economics (TSE).
    2. Crespo, Marelys, 2024. "Discretisation of Langevin diffusion in the weak log-concave case," TSE Working Papers 24-1506, Toulouse School of Economics (TSE).

    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. An, Mark Yuying, 1998. "Logconcavity versus Logconvexity: A Complete Characterization," Journal of Economic Theory, Elsevier, vol. 80(2), pages 350-369, June.
    2. Madeleine Cule & Richard Samworth & Michael Stewart, 2010. "Maximum likelihood estimation of a multi‐dimensional log‐concave density," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 72(5), pages 545-607, November.
    3. Simon Cowan, 2007. "The welfare effects of third-degree price discrimination with nonlinear demand functions," RAND Journal of Economics, RAND Corporation, vol. 38(2), pages 419-428, June.
    4. Le, Toan, 2024. "Robust lower bounds on monopoly profit with α-concave demand," Economics Letters, Elsevier, vol. 244(C).
    5. Alexandre de Corniere, 2013. "Search Advertising," Economics Series Working Papers 649, University of Oxford, Department of Economics.
    6. Chakravarty, Surajeet & Kaplan, Todd R. & Myles, Gareth, 2018. "When costly voting is beneficial," Journal of Public Economics, Elsevier, vol. 167(C), pages 33-42.
    7. Schweizer, Nikolaus & Szech, Nora, 2015. "A quantitative version of Myerson regularity," Working Paper Series in Economics 76, Karlsruhe Institute of Technology (KIT), Department of Economics and Management.
    8. Anderson, Simon P. & Renault, Regis, 2003. "Efficiency and surplus bounds in Cournot competition," Journal of Economic Theory, Elsevier, vol. 113(2), pages 253-264, December.
    9. Daisuke Oyama & Yasuhiro Sato & Takatoshi Tabuchi & Jacques‐François Thisse, 2011. "On the impact of trade on the industrial structures of nations," International Journal of Economic Theory, The International Society for Economic Theory, vol. 7(1), pages 93-109, March.
    10. Caplin, Andrew & Nalebuff, Barry, 1991. "Aggregation and Social Choice: A Mean Voter Theorem," Econometrica, Econometric Society, vol. 59(1), pages 1-23, January.
    11. Christian Ewerhart & Julia Lareida, 2018. "Voluntary disclosure in asymmetric contests," ECON - Working Papers 279, Department of Economics - University of Zurich, revised Jul 2023.
    12. Zhou, Jidong, 2021. "Mixed bundling in oligopoly markets," Journal of Economic Theory, Elsevier, vol. 194(C).
    13. Schweizer, Nikolaus & Szech, Nora, 2015. "The quantitative view of Myerson regularity," Discussion Papers, Research Unit: Economics of Change SP II 2015-307, WZB Berlin Social Science Center.
    14. Gibbons, Robert & Katz, Lawrence F, 1991. "Layoffs and Lemons," Journal of Labor Economics, University of Chicago Press, vol. 9(4), pages 351-380, October.
    15. von Thadden, Ernst-Ludwig, 2002. "An incentive problem in the dynamic theory of banking," Journal of Mathematical Economics, Elsevier, vol. 38(1-2), pages 271-292, September.
    16. Foucart, Renaud, 2020. "Metasearch and market concentration," International Journal of Industrial Organization, Elsevier, vol. 70(C).
    17. Hazelton, Martin L., 2011. "Assessing log-concavity of multivariate densities," Statistics & Probability Letters, Elsevier, vol. 81(1), pages 121-125, January.
    18. Benjamin Heymann & Alejandro Jofré, 2016. "Mechanism design and allocation algorithms for network markets with piece-wise linear costs and externalities," Working Papers hal-01416411, HAL.
    19. Xefteris, Dimitrios, 2016. "Stability in electoral competition: A case for multiple votes," Journal of Economic Theory, Elsevier, vol. 161(C), pages 76-102.
    20. S Nageeb Ali & Greg Lewis & Shoshana Vasserman, 2023. "Voluntary Disclosure and Personalized Pricing," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 90(2), pages 538-571.

    More about this item

    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:tse:wpaper:124826. 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: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/tsetofr.html .

    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.