Simulation-Based Econometric Methods

by Christian Gouriéroux, Alain Monfort

Overview

This book introduces a new generation of statistical econometrics. After linear models leading to analytical expressions for estimators, and non-linear models using numerical optimization algorithms, the availability of high- speed computing has enabled econometricians to consider econometric models without simple analytical expressions. The previous difficulties presented by the presence of integrals of large dimensions in the probability density functions or in the moments can be circumvented by a simulation-based approach.

After a brief survey of classical parametric and semi-parametric non-linear estimation methods and a description of problems in which criterion functions contain integrals, the authors present a general form of the model where it is possible to simulate the observations. They then move to calibration problems and the simulated analogue of the method of moments, before considering simulated versions of maximum likelihood, pseudo-maximum likelihood, or non-linear least squares. The general principle of indirect inference is presented and is then applied to limited dependent variable models and to financial series.

Product Details

ISBN-13:	9780198774754
Publisher:	Oxford University Press
Publication date:	04/10/1997
Series:	OUP/CORE Lecture Series
Edition description:	New Edition
Pages:	184
Product dimensions:	6.20(w) x 9.10(h) x 0.90(d)
Lexile:	1280L (what's this?)

About the Author

CREST and CEPREMAP, Paris

CREST, Paris

Table of Contents

1. Introduction and Motivations2. The Method of Simulated Moments3. Simulated Maximum Likelihood, Pseudo-maximum Likelihood, and Nonlinear Least Squares Methods4. Indirect Inference5. Applications of Limited Dependent Variable Models6. Applications to Financial Series7. Applications to Switching Regime Models