Showing 1 - 6 of 6
An accurate and efficient numerical approximation of the multivariate normal (MVN) distribution function is necessary for obtaining maximum likeli- hood estimates for models involving the MVN distribution. Numerical integration through simulation (Monte Carlo) or number-theoretic (quasi-Monte...
Persistent link: https://www.econbiz.de/10004964303
In this paper, we suggest a Stata routine for multinomial logit mod- els with unobserved heterogeneity using maximum simulated likelihood based on Halton sequences. The purpose of this paper is twofold. First, we describe the technical implementation of the estimation routine and discuss its...
Persistent link: https://www.econbiz.de/10004964311
We describe specification and estimation of a multinomial treatment effects negative binomial regression model. A latent factor structure is used to accommodate selection into treatment, and a simulated likelihood method is used for estimation. We describe its implementation via the mtreatnb...
Persistent link: https://www.econbiz.de/10004964314
This paper investigates using maximum simulated likelihood (MSL) estimation for random-effects dynamic probit models with autocorrelated errors. It presents and illustrates a new Stata command, redpace, for this estimator. The paper also compares using pseudorandom numbers and Halton sequences...
Persistent link: https://www.econbiz.de/10004964315
In this article, we describe the gmnl Stata command, which can be used to fit the generalized multinomial logit model and its special cases. Copyright 2013 by StataCorp LP.
Persistent link: https://www.econbiz.de/10010680826
This article describes the mixlogit Stata command for fitting mixed logit models by using maximum simulated likelihood. Copyright 2007 by StataCorp LP.
Persistent link: https://www.econbiz.de/10005568886