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st: probit and ordered probit eqns in a simultaneous system


From   Michael Alexander <Michael.Alexander@aifs.gov.au>
To   statalist@hsphsun2.harvard.edu
Subject   st: probit and ordered probit eqns in a simultaneous system
Date   Wed, 05 Jul 2006 11:32:48 +1000

Hi listreaders

I have a particular econometric problem that I am trying to analyse in Stata. I am trying to model employment of mothers (binary dependent variable) with the inclusion of self-reported health as an explanatory variable. I am postulating that self-reported health (a five-level categorical variable) is endogeous to employment. Following Cai and Kalb (2006) I am also postulating that labour force status is also a determinant of self-reported health (although this is of secondary importance to me).

Consequently, my modelling approach was to do a system of two equations (one for LFS and one for self-reported health) and estimate them simultaneously. Unfortunately, I have only found the -mvprobit- command which will sort of allow me to model this, but only if I convert my self-reported health variable to a binary variable. What I ideally need is a command that will allow me to simultaneously model a binary dependent variable (employment) and an ordinal categorical dependent variable (self-reported health, which has five-levels). Does such a command exist? Or am I able to build my own estimator ? (Not something I am keen on as I haven't done a lot of programming but am willing to give it a go if this is the only approach).

An alternative approach would be to not worry about the impact of LFS on self-reported health and only focus on the endogenous nature of self-reported health on employment. That way I could use an instrumental variable approach to dealing with the endogeniety of self-reported health in an employment equation. But as far as I can make out, this still requires me to model self-reported health as a binary variable (using -ivprobit-). Can I use an instrumental variable approach even when my endogeous variable is (ordinal) categorical.

Thanks in anticipation
Michael

Cai, L. and Kalb, K. (2006), 'Health Status and Labour Force Participation: Evidence from the HILDA Data', Health Economics, vol. 15, March, pp. 241-261.

--
Michael Alexander
Principal Research Fellow
Australian Institute of Family Studies

300 Queen Street Melbourne VIC 3000

Tel: 03 9214 7841
Fax: 03 9214 7839
Mob: 0419 406 078
Email: Michael.Alexander@aifs.gov.au
Web-site: www.aifs.gov.au

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