Maximum simulated likelihood methods and applications

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 s...

Full description

Saved in:
Bibliographic Details
Other Authors Greene, William, Hill, R. Carter
Format Electronic eBook
LanguageEnglish
Published Bingley, U.K. : Emerald, 2010.
SeriesAdvances in econometrics ; 26.
Subjects
Econometrics.
elektronické knihy
electronic books
Online AccessFull text
ISBN9780857241504
ISSN0731-9053 ;
DOI10.1108/S0731-9053(2010)26
Physical Description1 online resource (xiv, 356 p.) : ill.

Cover

Table of Contents:
  • Introduction / William Greene
  • MCMC perspectives on simulated likelihood estimation / Ivan Jeliazkov and Esther Hee Lee
  • The panel probit model : adaptive integration on sparse grids / Florian Heiss
  • 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
  • Pretest estimation in the random parameters logit model / Tong Zeng and R. Carter Hill
  • Simulated maximum likelihood estimation of continuous time stochastic volatility models / Tore Selland Kleppe, Jun Yu, Hans J. Skaug
  • Education savings accounts, parent contributions, and education attainment / Michael D. S. Morris
  • Estimating the effect of exchange rate flexibility on financial account openness / Raul Razo-Garcia
  • estimating a fractional response model with a count endogenous regressor and an application to female labor supply / Hoa B. Nguyen
  • Alternative random effects panel gamma SML estimation with heterogeneity in random and one-sided error / Saleem Shaik and Ashok K. Mishra
  • Modelling and forecasting volatility in a Bayesian approach / Esmail Amiri.

Similar Items