IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2311.06831.html
   My bibliography  Save this paper

Quasi-Bayes in Latent Variable Models

Author

Listed:
  • Sid Kankanala

Abstract

Latent variable models are widely used to account for unobserved determinants of economic behavior. Traditional nonparametric methods to estimate latent heterogeneity do not scale well into multidimensional settings. Distributional restrictions alleviate tractability concerns but may impart non-trivial misspecification bias. Motivated by these concerns, this paper introduces a quasi-Bayes approach to estimate a large class of multidimensional latent variable models. Our approach to quasi-Bayes is novel in that we center it around relating the characteristic function of observables to the distribution of unobservables. We propose a computationally attractive class of priors that are supported on Gaussian mixtures and derive contraction rates for a variety of latent variable models.

Suggested Citation

  • Sid Kankanala, 2023. "Quasi-Bayes in Latent Variable Models," Papers 2311.06831, arXiv.org.
    • Handle: RePEc:arx:papers:2311.06831
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/2311.06831
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Chernozhukov, Victor & Hong, Han, 2003. "An MCMC approach to classical estimation," Journal of Econometrics, Elsevier, vol. 115(2), pages 293-346, August.
    2. repec:dau:papers:123456789/3984 is not listed on IDEAS
    3. Geweke, John & Keane, Michael, 2000. "An empirical analysis of earnings dynamics among men in the PSID: 1968-1989," Journal of Econometrics, Elsevier, vol. 96(2), pages 293-356, June.
    4. Hu, Yingyao, 2008. "Identification and estimation of nonlinear models with misclassification error using instrumental variables: A general solution," Journal of Econometrics, Elsevier, vol. 144(1), pages 27-61, May.
    5. Heckman, James & Singer, Burton, 1984. "A Method for Minimizing the Impact of Distributional Assumptions in Econometric Models for Duration Data," Econometrica, Econometric Society, vol. 52(2), pages 271-320, March.
    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. Jean-Pierre Florens & Anna Simoni, 2021. "Revisiting Identification Concepts in Bayesian Analysis," Annals of Economics and Statistics, GENES, issue 144, pages 1-38.
    2. Benjamin Friedrich & Costas Meghir & Lisa Laun & Luigi Pistaferri, 2018. "Earnings Dynamics and Firm-Level Shocks," 2018 Meeting Papers 536, Society for Economic Dynamics.
    3. repec:hal:spmain:info:hdl:2441/lpag9391598uoauqu4u9opq76 is not listed on IDEAS
    4. A. Ronald Gallant & Han Hong & Ahmed Khwaja, 2018. "The Dynamic Spillovers of Entry: An Application to the Generic Drug Industry," Management Science, INFORMS, vol. 64(3), pages 1189-1211, March.
    5. Jesús Fernández-Villaverde, 2010. "The econometrics of DSGE models," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 1(1), pages 3-49, March.
    6. Stéphane Bonhomme & Koen Jochmans & Jean-Marc Robin, 2017. "Nonparametric estimation of non-exchangeable latent-variable models," Sciences Po publications info:hdl:2441/4m4fqk908d9, Sciences Po.
    7. Manuel Arellano & Stéphane Bonhomme, 2023. "Recovering Latent Variables by Matching," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 118(541), pages 693-706, January.
    8. Sasaki, Yuya, 2015. "Heterogeneity and selection in dynamic panel data," Journal of Econometrics, Elsevier, vol. 188(1), pages 236-249.
    9. Bonhomme, Stéphane & Jochmans, Koen & Robin, Jean-Marc, 2017. "Nonparametric estimation of non-exchangeable latent-variable models," Journal of Econometrics, Elsevier, vol. 201(2), pages 237-248.
    10. Bonhomme, Stéphane & Jochmans, Koen & Robin, Jean-Marc, 2017. "Nonparametric estimation of non-exchangeable latent-variable models," Journal of Econometrics, Elsevier, vol. 201(2), pages 237-248.
    11. Yuichi Kitamura, 2006. "Empirical Likelihood Methods in Econometrics: Theory and Practice," CIRJE F-Series CIRJE-F-430, CIRJE, Faculty of Economics, University of Tokyo.
    12. repec:hal:spmain:info:hdl:2441/4m4fqk908d9obqasu0uhft7t94 is not listed on IDEAS
    13. Patrick Arni & Rafael Lalive & Jan C. Van Ours, 2013. "How Effective Are Unemployment Benefit Sanctions? Looking Beyond Unemployment Exit," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 28(7), pages 1153-1178, November.
    14. Kemptner, Daniel & Tolan, Songül, 2018. "The role of time preferences in educational decision making," Economics of Education Review, Elsevier, vol. 67(C), pages 25-39.
    15. Christelis, Dimitris & Dobrescu, Loretti I. & Motta, Alberto, 2020. "Early life conditions and financial risk-taking in older age," The Journal of the Economics of Ageing, Elsevier, vol. 17(C).
    16. Michelle Sheran Sylvester, 2007. "The Career and Family Choices of Women: A Dynamic Analysis of Labor Force Participation, Schooling, Marriage and Fertility Decisions," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 10(3), pages 367-399, July.
    17. Insoo Cho & Peter F. Orazem, 2021. "How endogenous risk preferences and sample selection affect analysis of firm survival," Small Business Economics, Springer, vol. 56(4), pages 1309-1332, April.
    18. Patrick Bajari & Jeremy Fox & Stephen Ryan, 2008. "Evaluating wireless carrier consolidation using semiparametric demand estimation," Quantitative Marketing and Economics (QME), Springer, vol. 6(4), pages 299-338, December.
    19. Ali Palali & Jan C. Van ours, 2017. "Love Conquers all but Nicotine: Spousal Peer Effects on the Decision to Quit Smoking," Health Economics, John Wiley & Sons, Ltd., vol. 26(12), pages 1710-1727, December.
    20. Steven M. Lewis & Adrian E. Raftery, 1999. "Bayesian Analysis of Event History Models with Unobserved Heterogeneity via Markov Chain Monte Carlo," Sociological Methods & Research, , vol. 28(1), pages 35-60, August.
    21. Parent, Daniel, 1999. "Wages and Mobility: The Impact of Employer-Provided Training," Journal of Labor Economics, University of Chicago Press, vol. 17(2), pages 298-317, April.
    22. Steven T Berry & Giovanni Compiani, 2023. "An Instrumental Variable Approach to Dynamic Models," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 90(4), pages 1724-1758.

    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:arx:papers:2311.06831. 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: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    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.