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Econometric Inference Using Simulation Techniques
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Book Synopsis Econometric Inference Using Simulation Techniques by : Herman K. van Dijk
Download or read book Econometric Inference Using Simulation Techniques written by Herman K. van Dijk and published by . This book was released on 1995-07-11 with total page 290 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Simulation-based Inference in Econometrics by : Roberto Mariano
Download or read book Simulation-based Inference in Econometrics written by Roberto Mariano and published by Cambridge University Press. This book was released on 2000-07-20 with total page 488 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Econometric Inference Using Simulation Techniques by : Herman Van Dijk
Download or read book Econometric Inference Using Simulation Techniques written by Herman Van Dijk and published by John Wiley & Sons. This book was released on 1995-10-01 with total page 265 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Special issue on econometric inference using simulation techniques by : Bryan W. Brown
Download or read book Special issue on econometric inference using simulation techniques written by Bryan W. Brown and published by . This book was released on 1993 with total page 173 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Simulation-based Econometric Methods by : Christian Gouriéroux
Download or read book Simulation-based Econometric Methods written by Christian Gouriéroux and published by OUP Oxford. This book was released on 1997-01-09 with total page 190 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Monte Carlo Simulation for Econometricians by : Jan F. Kiviet
Download or read book Monte Carlo Simulation for Econometricians written by Jan F. Kiviet and published by Foundations & Trends. This book was released on 2012 with total page 185 pages. Available in PDF, EPUB and Kindle. Book excerpt: Monte Carlo Simulation for Econometricians presents the fundamentals of Monte Carlo simulation (MCS), pointing to opportunities not often utilized in current practice, especially with regards to designing their general setup, controlling their accuracy, recognizing their shortcomings, and presenting their results in a coherent way. The author explores the properties of classic econometric inference techniques by simulation. The first three chapters focus on the basic tools of MCS. After treating the basic tools of MCS, Chapter 4 examines the crucial elements of analyzing the properties of asymptotic test procedures by MCS. Chapter 5 examines more general aspects of MCS, such as its history, possibilities to increase its efficiency and effectiveness, and whether synthetic random exogenous variables should be kept fixed over all the experiments or be treated as genuinely random and thus redrawn every replication. The simulation techniques that we discuss in the first five chapters are often addressed as naive or classic Monte Carlo methods. However, simulation can also be used not just for assessing the qualities of inference techniques, but also directly for obtaining inference in practice from empirical data. Various advanced inference techniques have been developed which incorporate simulation techniques. An early example of this is Monte Carlo testing, which corresponds to the parametric bootstrap technique. Chapter 6 highlights such techniques and presents a few examples of (semi-)parametric bootstrap techniques. This chapter also demonstrates that the bootstrap is not an alternative to MCS but just another practical inference technique, which uses simulation to produce econometric inference. Each chapter includes exercises allowing the reader to immerse in performing and interpreting MCS studies. The material has been used extensively in courses for undergraduate and graduate students. The various chapters all contain illustrations which throw light on what uses can be made from MCS to discover the finite sample properties of a broad range of alternative econometric methods with a focus on the rather basic models and techniques.
Book Synopsis Simulation Based Bayesian Econometric Inference by : Lennart F. Hoogerheide
Download or read book Simulation Based Bayesian Econometric Inference written by Lennart F. Hoogerheide and published by . This book was released on 2007 with total page 60 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Simulation-based Inference in Econometrics by : Roberto S. Mariano
Download or read book Simulation-based Inference in Econometrics written by Roberto S. Mariano and published by . This book was released on 2000 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Using Simulation Methods for Bayesian Econometric Models by : John Geweke
Download or read book Using Simulation Methods for Bayesian Econometric Models written by John Geweke and published by . This book was released on 1998 with total page 62 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Bayesian Inference in Dynamic Econometric Models by : Luc Bauwens
Download or read book Bayesian Inference in Dynamic Econometric Models written by Luc Bauwens and published by OUP Oxford. This book was released on 2000-01-06 with total page 370 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Econometric Modeling and Inference by : Jean-Pierre Florens
Download or read book Econometric Modeling and Inference written by Jean-Pierre Florens and published by Cambridge University Press. This book was released on 2007-07-02 with total page 17 pages. Available in PDF, EPUB and Kindle. Book excerpt: Presents the main statistical tools of econometrics, focusing specifically on modern econometric methodology. The authors unify the approach by using a small number of estimation techniques, mainly generalized method of moments (GMM) estimation and kernel smoothing. The choice of GMM is explained by its relevance in structural econometrics and its preeminent position in econometrics overall. Split into four parts, Part I explains general methods. Part II studies statistical models that are best suited for microeconomic data. Part III deals with dynamic models that are designed for macroeconomic and financial applications. In Part IV the authors synthesize a set of problems that are specific to statistical methods in structural econometrics, namely identification and over-identification, simultaneity, and unobservability. Many theoretical examples illustrate the discussion and can be treated as application exercises. Nobel Laureate James A. Heckman offers a foreword to the work.
Book Synopsis Probability Theory and Statistical Inference by : Aris Spanos
Download or read book Probability Theory and Statistical Inference written by Aris Spanos and published by Cambridge University Press. This book was released on 2019-09-19 with total page 787 pages. Available in PDF, EPUB and Kindle. Book excerpt: This empirical research methods course enables informed implementation of statistical procedures, giving rise to trustworthy evidence.
Book Synopsis Introductory Econometrics by : Humberto Barreto
Download or read book Introductory Econometrics written by Humberto Barreto and published by Cambridge University Press. This book was released on 2006 with total page 810 pages. Available in PDF, EPUB and Kindle. Book excerpt: This highly accessible and innovative text with supporting web site uses Excel (R) to teach the core concepts of econometrics without advanced mathematics. It enables students to use Monte Carlo simulations in order to understand the data generating process and sampling distribution. Intelligent repetition of concrete examples effectively conveys the properties of the ordinary least squares (OLS) estimator and the nature of heteroskedasticity and autocorrelation. Coverage includes omitted variables, binary response models, basic time series, and simultaneous equations. The authors teach students how to construct their own real-world data sets drawn from the internet, which they can analyze with Excel (R) or with other econometric software. The accompanying web site with text support can be found at www.wabash.edu/econometrics.
Book Synopsis Economic Modeling and Inference by : Bent Jesper Christensen
Download or read book Economic Modeling and Inference written by Bent Jesper Christensen and published by Princeton University Press. This book was released on 2021-07-13 with total page 488 pages. Available in PDF, EPUB and Kindle. Book excerpt: Economic Modeling and Inference takes econometrics to a new level by demonstrating how to combine modern economic theory with the latest statistical inference methods to get the most out of economic data. This graduate-level textbook draws applications from both microeconomics and macroeconomics, paying special attention to financial and labor economics, with an emphasis throughout on what observations can tell us about stochastic dynamic models of rational optimizing behavior and equilibrium. Bent Jesper Christensen and Nicholas Kiefer show how parameters often thought estimable in applications are not identified even in simple dynamic programming models, and they investigate the roles of extensions, including measurement error, imperfect control, and random utility shocks for inference. When all implications of optimization and equilibrium are imposed in the empirical procedures, the resulting estimation problems are often nonstandard, with the estimators exhibiting nonregular asymptotic behavior such as short-ranked covariance, superconsistency, and non-Gaussianity. Christensen and Kiefer explore these properties in detail, covering areas including job search models of the labor market, asset pricing, option pricing, marketing, and retirement planning. Ideal for researchers and practitioners as well as students, Economic Modeling and Inference uses real-world data to illustrate how to derive the best results using a combination of theory and cutting-edge econometric techniques. Covers identification and estimation of dynamic programming models Treats sources of error--measurement error, random utility, and imperfect control Features financial applications including asset pricing, option pricing, and optimal hedging Describes labor applications including job search, equilibrium search, and retirement Illustrates the wide applicability of the approach using micro, macro, and marketing examples
Book Synopsis Simulation and Inference for Stochastic Differential Equations by : Stefano M. Iacus
Download or read book Simulation and Inference for Stochastic Differential Equations written by Stefano M. Iacus and published by Springer Science & Business Media. This book was released on 2009-04-27 with total page 298 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Simulation based inference in econometric by : Roberto Mariano
Download or read book Simulation based inference in econometric written by Roberto Mariano and published by . This book was released on 2000 with total page 462 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Simulation-based Econometric Methods by :
Download or read book Simulation-based Econometric Methods written by and published by . This book was released on 1997 with total page 184 pages. Available in PDF, EPUB and Kindle. Book excerpt:
