THE METHOD OF SIMULATED MAXIMUM LIKELIHOOD FOR THE ESTIMATON OF DYNAMIC ORDERED PROBIT: AN APPLICATION TO COUNTRY-RISK FOR NON-DEVELOPED COUNTRIES

Mariano Gonzalez Sanchez and R. Minguez (minsal@ceu.es)

International Journal of Applied Econometrics and Quantitative Studies, 2005, vol. 2, issue 3, 99-133

Abstract: This paper aims to give a detailed explanation of the econometric methodology necessary to estimate dynamic probit models with ordinal dependent variables. A typology of cases are established which appear when considering different choices of individual heterogeneity along with time correlation. To be able to estimate by maximum likelihood the models which come out of the different alternatives proposed, simulation techniques are used and put into practice by the GHK simulator and, in this way, estimators by simulated maximum likelihood are obtained. Finally, all the models described are used to measure and determine the macroeconomic factors which explain the ratings of country-risk in non-developed countries.

Keywords: Country risk; panel data; external debt; dynamic ordered probit (search for similar items in EconPapers)
JEL-codes: C33 C35 F34 H63 O16 (search for similar items in EconPapers)
Date: 2005
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.usc.es/economet/reviews/ijaeqs233.pdf
No

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eaa:ijaeqs:v:2:y2005:i:3_3

Ordering information: This journal article can be ordered from
http://www.usc.es/economet/info.htm
mcarmen.guisan@usc.es

Access Statistics for this article

More articles in International Journal of Applied Econometrics and Quantitative Studies from Euro-American Association of Economic Development
Bibliographic data for series maintained by M. Carmen Guisan (mcarmen.guisan@usc.es).