Simulation Based Inference In Econometrics
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Simulation Based Inference In Econometrics
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Author : Roberto Mariano
language : en
Publisher: Cambridge University Press
Release Date : 2000-07-20
Simulation Based Inference In Econometrics written by Roberto Mariano and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000-07-20 with Business & Economics categories.
This substantial volume has two principal objectives. First it provides an overview of the statistical foundations of Simulation-based inference. This includes the summary and synthesis of the many concepts and results extant in the theoretical literature, the different classes of problems and estimators, the asymptotic properties of these estimators, as well as descriptions of the different simulators in use. Second, the volume provides empirical and operational examples of SBI methods. Often what is missing, even in existing applied papers, are operational issues. Which simulator works best for which problem and why? This volume will explicitly address the important numerical and computational issues in SBI which are not covered comprehensively in the existing literature. Examples of such issues are: comparisons with existing tractable methods, number of replications needed for robust results, choice of instruments, simulation noise and bias as well as efficiency loss in practice.
Simulation Based Inference In Econometrics
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Author : Roberto S. Mariano
language : en
Publisher:
Release Date : 2000
Simulation Based Inference In Econometrics written by Roberto S. Mariano and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000 with Econometric models categories.
Finite Sample Simulation Based Inference In Var Models With Applications To Order Selection And Causality Testing
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Author : Dufour, Jean-Marie
language : en
Publisher: Montréal : CIRANO
Release Date : 2005
Finite Sample Simulation Based Inference In Var Models With Applications To Order Selection And Causality Testing written by Dufour, Jean-Marie and has been published by Montréal : CIRANO this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005 with Autoregression (Statistics) categories.
Simulation Based Econometric Methods
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Author : Christian Gouriéroux
language : en
Publisher: OUP Oxford
Release Date : 1997-01-09
Simulation Based Econometric Methods written by Christian Gouriéroux and has been published by OUP Oxford this book supported file pdf, txt, epub, kindle and other format this book has been release on 1997-01-09 with Business & Economics categories.
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.
Finite Sample Simulation Based Inference In Var Models With Applications To Order Selection And Causality Testing
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Author : Jean-Marie Dufour
language : en
Publisher: Centre interuniversitaire de recherche en économie quantitative
Release Date : 2005*
Finite Sample Simulation Based Inference In Var Models With Applications To Order Selection And Causality Testing written by Jean-Marie Dufour and has been published by Centre interuniversitaire de recherche en économie quantitative this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005* with Autoregression (Statistics) categories.
Simulation Based Bayesian Econometric Inference
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Author : Lennart F. Hoogerheide
language : en
Publisher:
Release Date : 2007
Simulation Based Bayesian Econometric Inference written by Lennart F. Hoogerheide and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007 with categories.
Simulation Based Econometric Methods
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Author :
language : en
Publisher:
Release Date : 1997
Simulation Based Econometric Methods written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1997 with categories.
Bayesian Inference In Dynamic Econometric Models
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Author : Luc Bauwens
language : en
Publisher: OUP Oxford
Release Date : 2000-01-06
Bayesian Inference In Dynamic Econometric Models written by Luc Bauwens and has been published by OUP Oxford this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000-01-06 with Business & Economics categories.
This book contains an up-to-date coverage of the last twenty years advances in Bayesian inference in econometrics, with an emphasis on dynamic models. It shows how to treat Bayesian inference in non linear models, by integrating the useful developments of numerical integration techniques based on simulations (such as Markov Chain Monte Carlo methods), and the long available analytical results of Bayesian inference for linear regression models. It thus covers a broad range of rather recent models for economic time series, such as non linear models, autoregressive conditional heteroskedastic regressions, and cointegrated vector autoregressive models. It contains also an extensive chapter on unit root inference from the Bayesian viewpoint. Several examples illustrate the methods.
Econometric Inference Using Simulation Techniques
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Author : Herman K. van Dijk
language : en
Publisher:
Release Date : 1995-07-11
Econometric Inference Using Simulation Techniques written by Herman K. van Dijk and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1995-07-11 with Business & Economics categories.
This book provides a comprehensive assessment of the latest simulation techniques, and examines the three main areas of econometric inference where the use of simulation methods has been successful; Bayesian inference, classical inference, and the solution and stochastic simulation of dynamic econometric models, in particular general equilibrium models.
Simulation And Inference For Stochastic Differential Equations
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Author : Stefano M. Iacus
language : en
Publisher: Springer Science & Business Media
Release Date : 2009-04-27
Simulation And Inference For Stochastic Differential Equations written by Stefano M. Iacus and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-04-27 with Computers categories.
This book covers a highly relevant and timely topic that is of wide interest, especially in finance, engineering and computational biology. The introductory material on simulation and stochastic differential equation is very accessible and will prove popular with many readers. While there are several recent texts available that cover stochastic differential equations, the concentration here on inference makes this book stand out. No other direct competitors are known to date. With an emphasis on the practical implementation of the simulation and estimation methods presented, the text will be useful to practitioners and students with minimal mathematical background. What’s more, because of the many R programs, the information here is appropriate for many mathematically well educated practitioners, too.