Simulation-based Econometric Methods (Hardcover)

Alain Monfort

ISBN 10: 0198774753 / ISBN 13: 9780198774754

Published by Oxford University Press, Oxford, 1997

About this Item

Hardcover. 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 inthe 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 ofproblems 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 financialseries. This book presents an exciting new set of econometric methods. They have been developed as a result of the increase in power and affordability of computers which allow simulations to be run. The authors have played a large role in developing the techniques. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Seller Inventory # 9780198774754

Bibliographic Details

• Title: Simulation-based Econometric Methods (Hardcover)
• Publisher: Oxford University Press, Oxford
• Publication Date: 1997
• Language: English
• ISBN 10: 0198774753
• ISBN 13: 9780198774754
• Binding: Hardcover
• Condition: new

About this title

Synopsis

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.

From the Back Cover

Simulation-Based Econometric Methods introduces a new generation of econometric methods in the classical domain. 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, for instance, 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.