st: probit and ordered probit eqns in a simultaneous system

[Michael Alexander <Michael.Alexander@aifs.gov.au>]

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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