Maximum Simulated Likelihood Methods and Applications

Name: Maximum Simulated Likelihood Methods and Applications
Price: 93.14 USD
Availability: InStock
ISBN: 9780857241498

ISBN-10: 0857241494

ISBN-13: 9780857241498

Edition: 2010

Authors: William Greene, R. Carter Hill, Carter Hill, Tom Fomby

List price: $104.99

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Description:

The economics and statistics literature using computer simulation based methods has grown enormously over the past decades. Maximum Simulated Likelihood is a statistical tool useful for incorporating individual differences (called heterogeneity in the econometrics literature) and variations into a statistical analysis. Problems that can be intractable with traditional methods are solved using computer simulation integrated with classical methods. Instead of assuming that everyone responds to stimuli in the same way, allowances are made for the possibility that different decision makers will respond in different ways. The techniques can be applied to problems of individual choice, such as…

Book details

List price: $104.99
Copyright year: 2010
Publisher: Emerald Publishing Limited
Publication date: 12/3/2010
Binding: Hardcover
Pages: 363
Size: 5.98" wide x 9.02" long x 1.30" tall
Weight: 1.452
Language: English



List of Contributors


Introduction



Theory and Methods


Mcmc Perspectives on Simulated Likelihood Estimation



The Panel Probit Model: Adaptive Integration on Sparse Grids



A Comparison of the Maximum Simulated Likelihood and Composite Marginal Likelihood Estimation Approaches in the Context of the Multivariate Ordered-Response Model



Pretest Estimation in the Random Parameters Logit Model



Simulated Maximum Likelihood Estimation of Continuous Time Stochastic Volatility Models




Applications


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 an Application to Female Labor Supply



Alternative Random Effects Panel Gamma SML Estimation with Heterogeneity in Random and One-Sided Error



Modeling and Forecasting Volatility in a Bayesian Approach