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In this paper we suggest a Stata routine for multinomial logit models with unobserved heterogeneity using maximum simulated likelihood based on Halton sequences. The purpose of this paper is twofold: First, we provide a description of the technical implementation of the estimation routine and...
Persistent link: https://www.econbiz.de/10010260947
In this paper, we suggest a Stata routine for multinomial logit models 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/10009442791
We discuss methods for calculating multivariate normal probabilities by simulation and two new Stata programs for this purpose: mvdraws for deriving draws from the standard uniform density using either Halton or pseudo-random sequences, and an egen function mvnp() for calculating the...
Persistent link: https://www.econbiz.de/10010260956
We discuss methods for calculating multivariate normal probabilities by simulation and two new Stata programs for this purpose: -mdraws- for deriving draws from the standard uniform density using either Halton or pseudo-random sequences, and an egen function -mvnp()- for calculating the...
Persistent link: https://www.econbiz.de/10010267543
We discuss methods for calculating multivariate normal probabilities by simulation and two new Stata programs for this purpose: mvdraws for deriving draws from the standard uniform density using either Halton or pseudo-random sequences, and an egen function mvnp() for calculating the...
Persistent link: https://www.econbiz.de/10004963950
This paper is concerned with estimating preference functionals for choice under risk from the choice behaviour of individuals. We start from the observation that there is heterogeneity in behaviour between individuals and within individuals. By ‘heterogeneity between individuals’ we mean...
Persistent link: https://www.econbiz.de/10005328508
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