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Estimating the Standard Errors of Individual-Specific Parameters in Random Parameters Models

Author

Listed:
  • William H Greene

    (Economics Department, Stern School of Business, New York University (NYU))

  • Mark N Harris

    (School of Economics and Finance, Curtin University)

  • Christopher Spencer

    (School of Business and Economics, Loughborough University)

Abstract
We consider the estimation of the standard errors of individual-specific parameters calculated ex post from a non-linear random parameters model. Our key contribution lies in introducing a simple method of appropriately calculating these standard errors, which explicitly takes into account the sampling variability of the estimation of the model's parameters. To demonstrate the applicability of the technique, we use it in a model of the voting behaviour of Bank of England MPC members. Our results have clear implications for drawing statistical inference on the estimated random parameters.

Suggested Citation

  • William H Greene & Mark N Harris & Christopher Spencer, 2013. "Estimating the Standard Errors of Individual-Specific Parameters in Random Parameters Models," Bankwest Curtin Economics Centre Working Paper series WP1309, Bankwest Curtin Economics Centre (BCEC), Curtin Business School.
    • Handle: RePEc:ozl:bcecwp:wp1309
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    References listed on IDEAS

    as
    1. William Greene, 2004. "Convenient estimators for the panel probit model: Further results," Empirical Economics, Springer, vol. 29(1), pages 21-47, January.
    2. Frederic S. Mishkin, 2011. "Over the Cliff: From the Subprime to the Global Financial Crisis," Journal of Economic Perspectives, American Economic Association, vol. 25(1), pages 49-70, Winter.
    3. Martin, Christopher & Milas, Costas, 2013. "Financial crises and monetary policy: Evidence from the UK," Journal of Financial Stability, Elsevier, vol. 9(4), pages 654-661.
    4. Timothy Besley & Neil Meads & Paolo Surico, 2008. "Insiders versus Outsiders in Monetary Policymaking," American Economic Review, American Economic Association, vol. 98(2), pages 218-223, May.
    5. Matthias Neuenkirch, 2013. "Predicting Bank of England's asset purchase decisions with MPC voting records," Applied Economics Letters, Taylor & Francis Journals, vol. 20(13), pages 1275-1278, September.
    6. Manuel Arellano & Stéphane Bonhomme, 2012. "Identifying Distributional Characteristics in Random Coefficients Panel Data Models," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 79(3), pages 987-1020.
    7. David Revelt & Kenneth Train, 1998. "Mixed Logit With Repeated Choices: Households' Choices Of Appliance Efficiency Level," The Review of Economics and Statistics, MIT Press, vol. 80(4), pages 647-657, November.
    8. David F. Layton & Gardner Brown, 2000. "Heterogeneous Preferences Regarding Global Climate Change," The Review of Economics and Statistics, MIT Press, vol. 82(4), pages 616-624, November.
    9. Judson, Ruth A. & Owen, Ann L., 1999. "Estimating dynamic panel data models: a guide for macroeconomists," Economics Letters, Elsevier, vol. 65(1), pages 9-15, October.
    10. Mark N. Harris & Christopher Spencer, 2009. "The Policy Choices and Reaction Functions of Bank of England MPC Members," Southern Economic Journal, John Wiley & Sons, vol. 76(2), pages 482-499, October.
    11. Paul Mizen, 2008. "The credit crunch of 2007-2008: a discussion of the background, market reactions, and policy responses," Review, Federal Reserve Bank of St. Louis, vol. 90(Sep), pages 531-568.
    12. Brooks, Robert & Harris, Mark N. & Spencer, Christopher, 2012. "Inflated ordered outcomes," Economics Letters, Elsevier, vol. 117(3), pages 683-686.
    13. Greene,William H. & Hensher,David A., 2010. "Modeling Ordered Choices," Cambridge Books, Cambridge University Press, number 9780521194204, November.
    14. Krinsky, Itzhak & Robb, A Leslie, 1986. "On Approximating the Statistical Properties of Elasticities," The Review of Economics and Statistics, MIT Press, vol. 68(4), pages 715-719, November.
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    Cited by:

    1. Sarrias, Mauricio, 2016. "Discrete Choice Models with Random Parameters in R: The Rchoice Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 74(i10).
    2. Sarrias, Mauricio & Daziano, Ricardo A., 2018. "Individual-specific point and interval conditional estimates of latent class logit parameters," Journal of choice modelling, Elsevier, vol. 27(C), pages 50-61.

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    More about this item

    Keywords

    Random parameters; individual?specific parameters; standard errors; voting; Monetary Policy Committee;
    All these keywords.

    JEL classification:

    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities

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