IDEAS home Printed from https://ideas.repec.org/a/ect/emjrnl/v12y2009i1p164-186.html
   My bibliography  Save this article

EM algorithms for ordered probit models with endogenous regressors

Author

Listed:
  • Hiroyuki Kawakatsu
  • Ann G. Largey

Abstract

We propose an EM algorithm to estimate ordered probit models with endogenous regressors. The proposed algorithm has a number of computational advantages in comparison to direct numerical maximization of the (limited information) log-likelihood function. First, the sequence of conditional M(aximization)-steps can all be computed analytically. Second, the algorithm updates the model parameters so that positive definiteness of the covariance matrix and monotonicity of cutpoints are naturally satisfied. Third, the variance parameters normalized for identification can be activated to accelerate convergence of the algorithm. The algorithm can be applied to models with dummy endogenous, continuous endogenous or latent endogenous regressors. A small Monte Carlo simulation experiment examines the finite sample performance of the proposed algorithms. Copyright The Author(s). Journal compilation Royal Economic Society 2009

Suggested Citation

  • Hiroyuki Kawakatsu & Ann G. Largey, 2009. "EM algorithms for ordered probit models with endogenous regressors," Econometrics Journal, Royal Economic Society, vol. 12(1), pages 164-186, March.
  • Handle: RePEc:ect:emjrnl:v:12:y:2009:i:1:p:164-186
    as

    Download full text from publisher

    File URL: http://www.blackwell-synergy.com/doi/abs/10.1111/j.1368-423X.2008.00272.x
    File Function: link to full text
    Download Restriction: Access to full text is restricted to subscribers.

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Seya, Hajime & Nakamichi, Kumiko & Yamagata, Yoshiki, 2016. "The residential parking rent price elasticity of car ownership in Japan," Transportation Research Part A: Policy and Practice, Elsevier, vol. 85(C), pages 123-134.
    2. Giulia Bettin & Riccardo Lucchetti, . "Instrumental Variable Interval Regression," EHUCHAPS, Universidad del País Vasco - Facultad de Ciencias Económicas y Empresariales.
    3. Vargas, Jose P Mauricio, 2012. "Binding Constraints: Does Firm Size Matter?," MPRA Paper 41286, University Library of Munich, Germany.
    4. Mauricio Vargas, 2015. "Identifying Binding Constraints to Growth; Does Firm Size Matter?," IMF Working Papers 15/3, International Monetary Fund.
    5. Giulia Bettin & Riccardo Lucchetti, 2012. "Interval regression models with endogenous explanatory variables," Empirical Economics, Springer, vol. 43(2), pages 475-498, October.

    More about this item

    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:ect:emjrnl:v:12:y:2009:i:1:p:164-186. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Wiley-Blackwell Digital Licensing) or (Christopher F. Baum). General contact details of provider: http://edirc.repec.org/data/resssea.html .

    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.

    We have no references for this item. You can help adding them by using 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.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.