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Alternative Simulation-Based Estimators of Logit Models with Random Effects

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Logit models with random effects are now widely used in applied Statistics and Econometrics. They usually lead to intractable likelihood functions, as they involve integrals without closed form solution. Numerical integration can be used to compute the likelihood and software is available (Hedeker and Gibbons, 1996). Difficulties can be encountered when the number of random effect parameters is not very small. With a detailed Monte Carlo experimentation, we show in this paper that the simulation-based estimators are almost as efficient as maximum likelihood. They are Simulated Maximum Likelihood (Gouri´eroux and Monfort, 1991), Indirect Inference (Gouri´eroux, Monfort and Renault, 1993) using an auxiliary approximated likelihood estimator, and Indirect Inference using an auxiliary linear probability model. The advantage of the latter is its great simplicity and computational speed.

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Paper provided by Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti" in its series Econometrics Working Papers Archive with number quaderno48.

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Length: 21
Date of creation: 2001
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Handle: RePEc:fir:econom:quaderno48

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  1. Gourieroux, C. & Monfort, A. & Renault, E., 1992. "Indirect Inference," Papers 92.279, Toulouse - GREMAQ.
  2. Giorgio Calzolari & Gabriele Fiorentini & Enrique Sentana, 2004. "Constrained Indirect Estimation," Review of Economic Studies, Oxford University Press, vol. 71(4), pages 945-973.
  3. Mealli, Fabrizia & Rampichini, Carla, 1999. "Estimating binary multilevel models through indirect inference," Computational Statistics & Data Analysis, Elsevier, vol. 29(3), pages 313-324, January.
  4. Calzolari, Giorgio & Di Iorio, Francesca & Fiorentini, Gabriele, 1996. "Control variates for variance reduction in indirect inference: interest rate models in continuous time," MPRA Paper 23160, University Library of Munich, Germany, revised Nov 1996.
  5. Bianchi, Carlo & Calzolari, Giorgio & Corsi, Paolo, 1978. "A Program for Stochastic Simulation of Econometric Models," Econometrica, Econometric Society, vol. 46(1), pages 235-36, January.
  6. Stephen Pudney & Michael Shields, 2000. "Gender, race, pay and promotion in the British nursing profession: estimation of a generalized ordered probit model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(4), pages 367-399.
  7. Mealli, Fabrizia & Pudney, Stephen, 1996. "Occupational Pensions and Job Mobility in Britain: Estimation of a Random-Effects Competing Risks Model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 11(3), pages 293-320, May-June.
  8. Longford, N. T., 1994. "Logistic regression with random coefficients," Computational Statistics & Data Analysis, Elsevier, vol. 17(1), pages 1-15, January.
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