Maximum Simulated Likelihood Methods and Applications

This volume is a collection of methodological developments and applications of simulation-based methods that were presented at a workshop at Louisiana State University in November, 2009

The first two papers are extensions of the GHK simulator: one reconsiders the computation of the probabilities in a discrete choice model while another example uses an adaptive version of sparse-grids integration (SGI) instead of simulation. Two studies are focused specifically on the methodology: the first compares the performance of the maximum-simulated likelihood (MSL) approach with a proposed composite-marginal likelihood (CML) approach in multivariate ordered-response situations, while the second examines methods of testing for the presence of heterogeneity in the heterogeneity model. Further topics examined include: education savings accounts, parent contributions, and education attainment; estimating the effect of exchange rate flexibility on financial account openness; estimating a fractional response model with a count endogenous regressor; and modeling and forecasting volatility in a Bayesian approach.

1023481413
Maximum Simulated Likelihood Methods and Applications

This volume is a collection of methodological developments and applications of simulation-based methods that were presented at a workshop at Louisiana State University in November, 2009

The first two papers are extensions of the GHK simulator: one reconsiders the computation of the probabilities in a discrete choice model while another example uses an adaptive version of sparse-grids integration (SGI) instead of simulation. Two studies are focused specifically on the methodology: the first compares the performance of the maximum-simulated likelihood (MSL) approach with a proposed composite-marginal likelihood (CML) approach in multivariate ordered-response situations, while the second examines methods of testing for the presence of heterogeneity in the heterogeneity model. Further topics examined include: education savings accounts, parent contributions, and education attainment; estimating the effect of exchange rate flexibility on financial account openness; estimating a fractional response model with a count endogenous regressor; and modeling and forecasting volatility in a Bayesian approach.

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Maximum Simulated Likelihood Methods and Applications

Maximum Simulated Likelihood Methods and Applications

Maximum Simulated Likelihood Methods and Applications

Maximum Simulated Likelihood Methods and Applications

Overview

This volume is a collection of methodological developments and applications of simulation-based methods that were presented at a workshop at Louisiana State University in November, 2009

The first two papers are extensions of the GHK simulator: one reconsiders the computation of the probabilities in a discrete choice model while another example uses an adaptive version of sparse-grids integration (SGI) instead of simulation. Two studies are focused specifically on the methodology: the first compares the performance of the maximum-simulated likelihood (MSL) approach with a proposed composite-marginal likelihood (CML) approach in multivariate ordered-response situations, while the second examines methods of testing for the presence of heterogeneity in the heterogeneity model. Further topics examined include: education savings accounts, parent contributions, and education attainment; estimating the effect of exchange rate flexibility on financial account openness; estimating a fractional response model with a count endogenous regressor; and modeling and forecasting volatility in a Bayesian approach.

Product Details

ISBN-13: 9780857241498
Publisher: Emerald Group Publishing Limited
Publication date: 12/06/2010

Table of Contents

List of Contributors vii

Introduction ix

Part I Theory and Methods

Mcmc Perspectives on Simulated Likelihood Estimation Ivan Jeliazkov Esther Hee Lee 3

The Panel Probit Model: Adaptive Integration on Sparse Grids Florian Heiss 41

A Comparison of the Maximum Simulated Likelihood and Composite Marginal Likelihood Estimation Approaches in the Context of the Multivariate Ordered-Response Model Chandra R. Bhat Cristiano Varin Nazneen Ferdous 65

Pretest Estimation in the Random Parameters Logit Model Tong Zeng R. Carter Hill 107

Simulated Maximum Likelihood Estimation of Continuous Time Stochastic Volatility Models Tore Selland Kleppe Jun Yu H. J. Skaug 137

Part II Applications

Education Savings Accounts, Parent Contributions, and Education Attainment Michael D. S. Morris 165

Estimating the Effect of Exchange Rate Flexibility on Financial Account Openness Raul Razo-Garcia 199

Estimating a Fractional Response Model with a Count Endogenous Regressor and an Application to Female Labor Supply Hoa B. Nguyen 253

Alternative Random Effects Panel Gamma SML Estimation with Heterogeneity in Random and One-Sided Error Saleem Shaik Ashok K. Mishra 299

Modeling and Forecasting Volatility in a Bayesian Approach Esmail Amiri 323

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