IDEAS home Printed from https://ideas.repec.org/p/jrp/jrpwrp/2013-027.html
   My bibliography  Save this paper

Endogenous variables in non-linear models with mixed effects: Inconsistence under perfect identification conditions?

Author

Listed:
  • Franz Buscha

    (Westminster Business School, University of Westminster)

  • Anna Conte

    (Strategic Interaction Group, Max Planck Institute of Economics, Jena)

Abstract

This paper examines the consequences of introducing a normally distributed effect into a system where the dependent variable is ordered and the explanatory variable is ordered and endogenous. Using simulation techniques we show that a naïve bivariate ordered probit estimator which fails to take a mixed effect into account will result in inconsistent estimates even when identification conditions are optimal. Our results suggest this finding only applies to non-linear endogenous systems.

Suggested Citation

  • Franz Buscha & Anna Conte, 2013. "Endogenous variables in non-linear models with mixed effects: Inconsistence under perfect identification conditions?," Jena Economics Research Papers 2013-027, Friedrich-Schiller-University Jena.
    • Handle: RePEc:jrp:jrpwrp:2013-027
    as

    Download full text from publisher

    File URL: https://oweb.b67.uni-jena.de/Papers/jerp2013/wp_2013_027.pdf
    Download Restriction: no
    ---><---

    More about this item

    Keywords

    bivariate probit; bivariate ordered probit; mixed effects; endogenous binary variables; constant parameters;
    All these keywords.

    JEL classification:

    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
    • C36 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Instrumental Variables (IV) Estimation
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:jrp:jrpwrp:2013-027. See general information about how to correct material in RePEc.

    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 bibliographic 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.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Markus Pasche (email available below). General contact details of provider: http://www.jenecon.de .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.