Maximum simulated likelihood methods and applications [[electronic resource] /] / edited by William Greene, R. Carter Hill

• Pubblicazione: Bingley, UK, : Emerald, 2010
• Edizione: 1st ed.
• Descrizione fisica: 1 online resource (370 p.)
• Disciplina: 330.015195
• Soggetto topico: Econometric models; Mathematical models
• Soggetto genere / forma: Electronic books.
• Altri autori: GreeneWilliam H. <1951-> HillR. Carter
• Note generali: Description based upon print version of record.
• Nota di bibliografia: Includes bibliographical references.
• Nota di contenuto: Front cover; Advances in Econometrics; Copyright page; Contents; List of contributors; Introduction; Acknowledgments; References; Part I: Theory and Methods; Chapter 1. MCMC perspectives on simulated likelihood estimation; Chapter 2. The panel probit model: Adaptive integration on sparse grids; Chapter 3. A comparison of the maximum simulated likelihood and composite marginal likelihood estimation approaches in the context of the multivariate ordered-response model; Chapter 4. Pretest Estimation in the Random Parameters Logit Model ; Chapter 5. Simulated maximum likelihood estimation of continuous time stochastic volatility modelsPart II: Applications; Chapter 6. Education savings accounts, parent contributions, and education attainment; Chapter 7. Estimating the effect of exchange rate flexibility on financial account openness; Chapter 8. Estimating a Fractional Response Model with a count endogenous regressor and an application to female labor supply; Chapter 9. Alternative random effects panel gamma SML estimation with heterogeneity in random and one-sided error ; Chapter 10. Modeling and forecasting volatility in a bayesian approach
• Sommario/riassunto: 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. Contributors to the volume discuss alternative simulation methods that permit faster and more accurate inference, as well as applications of established methods.
• Titolo autorizzato: Maximum simulated likelihood methods and applications
• ISBN: 1-282-96400-3; 9786612964008; 0-85724-150-8
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910459715403321
• Lo trovi qui: Univ. Federico II
• Serie: Advances in econometrics ; ; v. 26.