Maximum Simulated Likelihood Methods and Applications (eBook, PDF)
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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 ma...
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 modelling and forecasting volatility in a bayesian approach.
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