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A General Method To Estimate Correlated Discrete Random Variables

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  • van Ophem, Hans

Abstract

In this paper a method is presented to estimate correlated discrete random variables with known univariate distribution functions up to some parameters. We also present an empirical illustration on Dutch recreational data.

Suggested Citation

  • van Ophem, Hans, 1999. "A General Method To Estimate Correlated Discrete Random Variables," Econometric Theory, Cambridge University Press, vol. 15(2), pages 228-237, April.
    • Handle: RePEc:cup:etheor:v:15:y:1999:i:02:p:228-237_15
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    Cited by:

    1. Marco Alfò & Giovanni Trovato, 2004. "Semiparametric Mixture Models for Multivariate Count Data, with Application," CEIS Research Paper 51, Tor Vergata University, CEIS.
    2. Bijwaard, G.E. & Franses, Ph.H.B.F., 2006. "Does rounding matter for payment efficiency?," Econometric Institute Research Papers EI 2006-43, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    3. Eugenio Miravete, 2014. "Testing for complementarities among countable strategies," Empirical Economics, Springer, vol. 46(4), pages 1521-1544, June.
    4. Shi, Peng & Valdez, Emiliano A., 2014. "Multivariate negative binomial models for insurance claim counts," Insurance: Mathematics and Economics, Elsevier, vol. 55(C), pages 18-29.
    5. Bermúdez, Lluís & Karlis, Dimitris, 2011. "Bayesian multivariate Poisson models for insurance ratemaking," Insurance: Mathematics and Economics, Elsevier, vol. 48(2), pages 226-236, March.
    6. Pravin Trivedi & David Zimmer, 2017. "A Note on Identification of Bivariate Copulas for Discrete Count Data," Econometrics, MDPI, vol. 5(1), pages 1-11, February.
    7. Sengupta, Sanchita, 2010. "Three Essays in Environmental and Agricultural Issues," ISU General Staff Papers 201001010800002848, Iowa State University, Department of Economics.
    8. Greene, W., 2001. "Fixed and Random Effects in Nonlinear Models," New York University, Leonard N. Stern School Finance Department Working Paper Seires 01-01, New York University, Leonard N. Stern School of Business-.
    9. A. Colin Cameron & Tong Li & Pravin K. Trivedi & David M. Zimmer, 2004. "Modelling the differences in counted outcomes using bivariate copula models with application to mismeasured counts," Econometrics Journal, Royal Economic Society, vol. 7(2), pages 566-584, December.
    10. José Murteira & Óscar Lourenço, 2011. "Health care utilization and self-assessed health: specification of bivariate models using copulas," Empirical Economics, Springer, vol. 41(2), pages 447-472, October.
    11. Simon Luechinger & Alois Stutzer & Rainer Winkelmann, 2008. "Self-Selection and Subjective Well-Being: Copula Models with an Application to Public and Private Sector Work," SOEPpapers on Multidisciplinary Panel Data Research 135, DIW Berlin, The German Socio-Economic Panel (SOEP).
    12. Fernandes, Mário Correia & Dias, José Carlos & Nunes, João Pedro Vidal, 2021. "Modeling energy prices under energy transition: A novel stochastic-copula approach," Economic Modelling, Elsevier, vol. 105(C).
    13. Lluís Bermúdez & Dimitris Karlis, 2010. "Modelling dependence in a ratemaking procedure with multivariate Poisson regression models," Working Papers XREAP2010-04, Xarxa de Referència en Economia Aplicada (XREAP), revised Apr 2010.
    14. Mothafer, Ghasak I.M.A. & Yamamoto, Toshiyuki & Shankar, Venkataraman N., 2018. "A multivariate heterogeneous-dispersion count model for asymmetric interdependent freeway crash types," Transportation Research Part B: Methodological, Elsevier, vol. 108(C), pages 84-105.
    15. Erik Brouwer & Alfred Kleinknecht & Pierre Mohnen & Hans van Ophem, 2001. "R&D and Patents: Which Way Does the Causality Run?," CIRANO Working Papers 2001s-31, CIRANO.
    16. Rainer Winkelmann, 2009. "Copula-based bivariate binary response models," SOI - Working Papers 0913, Socioeconomic Institute - University of Zurich.
    17. Faugeras Olivier P., 2017. "Inference for copula modeling of discrete data: a cautionary tale and some facts," Dependence Modeling, De Gruyter, vol. 5(1), pages 121-132, January.
    18. James E. Prieger, "undated". "A Generalized Parametric Selection Model for Non-Normal Data," Department of Economics 00-09, California Davis - Department of Economics.
    19. Jacek Osiewalski & Jerzy Marzec, 2019. "Joint modelling of two count variables when one of them can be degenerate," Computational Statistics, Springer, vol. 34(1), pages 153-171, March.
    20. A. Colin Cameron & Tong Li & Pravin K. Trivedi & David M. Zimmer, 2004. "Modelling the differences in counted outcomes using bivariate copula models with application to mismeasured counts," Econometrics Journal, Royal Economic Society, vol. 7(2), pages 566-584, December.
    21. James E. Prieger, "undated". "A Generalized Parametric Selection Model for Non-Normal Data," Department of Economics 00-09, California Davis - Department of Economics.
    22. Juliana Schulz & Christian Genest & Mhamed Mesfioui, 2021. "A multivariate Poisson model based on comonotonic shocks," International Statistical Review, International Statistical Institute, vol. 89(2), pages 323-348, August.

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