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Calculation of Multivariate Normal Probabilities by Simulation, with Applications to Maximum Simulated Likelihood Estimation

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Author Info
Lorenzo Cappellari () (Catholic University of Milan, ISER and IZA Bonn)
Stephen P. Jenkins () (ISER, University of Essex, DIW Berlin and IZA Bonn)

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Abstract

We discuss methods for calculating multivariate normal probabilities by simulation and two new Stata programs for this purpose: -mdraws- for deriving draws from the standard uniform density using either Halton or pseudo-random sequences, and an egen function -mvnp()- for calculating the probabilities themselves. Several illustrations show how the programs may be used for maximum simulated likelihood estimation.

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Publisher Info
Paper provided by Institute for the Study of Labor (IZA) in its series IZA Discussion Papers with number 2112.

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Length: 29 pages
Date of creation: May 2006
Date of revision:
Handle: RePEc:iza:izadps:dp2112

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Postal: IZA, P.O. Box 7240, D-53072 Bonn, Germany
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Related research
Keywords: simulation estimation; maximum simulated likelihood; multivariate probit; Halton sequences; pseudo-random sequences; multivariate normal; GHK simulator;

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Find related papers by JEL classification:
C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Statistical Simulation Methods
C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
C87 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Econometric Software

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References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
  1. William W. Gould & Jeffrey Pitblado & William Sribney, 2006. "Maximum Likelihood Estimation with Stata," Stata Press books, StataCorp LP, edition 3, number ml3, November-. [Downloadable!]
  2. Lorenzo Cappellari & Stephen P. Jenkins, 2003. "Multivariate probit regression using simulated maximum likelihood," United Kingdom Stata Users' Group Meetings 2003 10, Stata Users Group. [Downloadable!]
    Other versions:
  3. Stephen P. Jenkins & Lorenzo Cappellari & Peter Lynn & Annette Jäckle & Emanuela Sala, 2006. "Patterns of consent: evidence from a general household survey," Journal Of The Royal Statistical Society Series A, Royal Statistical Society, vol. 169(4), pages 701-722. [Downloadable!] (restricted)
    Other versions:
  4. Kenneth Train, 2003. "Discrete Choice Methods with Simulation," Online economics textbooks, SUNY-Oswego, Department of Economics, number emetr2, March. [Downloadable!]
  5. Peter Haan & Arne Uhlendorff, 2006. "Estimation of Multinomial Logit Models with Unobserved Heterogeneity Using Maximum Simulated Likelihood," Discussion Papers of DIW Berlin 573, DIW Berlin, German Institute for Economic Research. [Downloadable!]
    Other versions:
  6. Stephane Hess & John Polak, 2003. "An alternative method to the scrambled Halton sequence for removing correlation between standard Halton sequences in high dimensions," ERSA conference papers ersa03p406, European Regional Science Association. [Downloadable!]
  7. Lorenzo Cappellari & Stephen P. Jenkins, 2004. "Modelling low income transitions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 19(5), pages 593-610. [Downloadable!]
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  8. Mark Stewart, 2006. "Maximum simulated likelihood estimation of random-effects dynamic probit models with autocorrelated errors," Stata Journal, StataCorp LP, vol. 6(2), pages 256-272, June. [Downloadable!]
  9. Sandor, Zsolt & Andras, P.Peter, 2004. "Alternative sampling methods for estimating multivariate normal probabilities," Journal of Econometrics, Elsevier, vol. 120(2), pages 207-234, June. [Downloadable!] (restricted)
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