Simulation-based Econometric Methods
Language: English
Published by Oxford University Press, GB, 1997
- Hardcover
- New
Seller: Rarewaves.com UK, London, United KingdomRarewaves.com UK
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Condition: New
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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.…
Seller Inventory # LU-9780198774754
- Title
- Simulation-based Econometric Methods
- Author
- Christian Gouriéroux, Alain Monfort
- Publisher
- Oxford University Press, GB
- Publication year
- 1997
- Condition
- New
- Binding
- Hardback
- Language
- English
- ISBN 10
- 0198774753
- ISBN 13
- 9780198774754
- Item weight
- 479 grams
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.
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