The Method of Simulated Scores for the Estimation of LDV Models
Vassilis Hajivassiliou () and
Econometrica, 1998, vol. 66, issue 4, 863-896
The method of simulated scores (MSS) is presented for estimating limited dependent variables models (LDV) with flexible correlation structure in the unobservables. The authors propose simulators that are continuous in the unknown parameter vectors, and hence standard optimization methods can be used to compute the MSS estimators that employ these simulators. The first continuous method relies on a recursive conditioning of the multivariate normal density through a Cholesky triangularization of its variance-covariance matrix. The second method combines results about the conditionals of the multivariate normal distribution with Gibbs resampling techniques. The authors establish consistency and asymptotic normality of the MSS estimators and derive suitable rates at which the number of simulations must rise if biased simulators are used.
References: Add references at CitEc
Citations: View citations in EconPapers (120) Track citations by RSS feed
There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.
Working Paper: The Method of Simulated Scores for the Estimation of LDV Models (1997)
Working Paper: The Method of Simulated Scores for the Estimation of LDV Models (1993)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:ecm:emetrp:v:66:y:1998:i:4:p:863-896
Ordering information: This journal article can be ordered from
https://www.economet ... ordering-back-issues
Access Statistics for this article
Econometrica is currently edited by Daron Acemoglu
More articles in Econometrica from Econometric Society Contact information at EDIRC.
Bibliographic data for series maintained by Wiley-Blackwell Digital Licensing ().