Author : Anonim
Publisher : Unknown
Page : 184 pages
File Size : 41,5 Mb
Release : 1997
Category : Electronic
ISBN : OCLC:475414468
Simulation-based Econometric Methods
Anonim
Simulation Based Econometric Methods
Simulation Based Econometric Methods Book in PDF, ePub and Kindle version is available to download in english. Read online anytime anywhere directly from your device. Click on the download button below to get a free pdf file of Simulation Based Econometric Methods book. This book definitely worth reading, it is an incredibly well-written.
Simulation-based Econometric Methods
Christian Gouriéroux,Alain Monfort
Author : Christian Gouriéroux,Alain Monfort
Publisher : OUP Oxford
Page : 190 pages
File Size : 54,5 Mb
Release : 1997-01-09
Category : Business & Economics
ISBN : 9780191525094
Simulation-based Econometric Methods by Christian Gouriéroux,Alain Monfort Pdf
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.
Simulation-based Inference in Econometrics
Roberto Mariano,Til Schuermann,Melvyn J. Weeks
Author : Roberto Mariano,Til Schuermann,Melvyn J. Weeks
Publisher : Cambridge University Press
Page : 488 pages
File Size : 49,8 Mb
Release : 2000-07-20
Category : Business & Economics
ISBN : 0521591120
Simulation-based Inference in Econometrics by Roberto Mariano,Til Schuermann,Melvyn J. Weeks Pdf
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
Roberto S. Mariano
Author : Roberto S. Mariano
Publisher : Unknown
Page : 0 pages
File Size : 51,8 Mb
Release : 2000
Category : Econometric models
ISBN : OCLC:1409192855
Simulation-based Inference in Econometrics by Roberto S. Mariano Pdf
Maximum Simulated Likelihood Methods and Applications
William Greene,R. Carter Hill
Author : William Greene,R. Carter Hill
Publisher : Emerald Group Publishing
Page : 371 pages
File Size : 42,7 Mb
Release : 2010-12-03
Category : Business & Economics
ISBN : 9780857241498
Maximum Simulated Likelihood Methods and Applications by William Greene,R. Carter Hill Pdf
This collection of methodological developments and applications of simulation-based methods were presented at a workshop at Louisiana State University in November, 2009. Topics include: extensions of the GHK simulator; maximum-simulated likelihood; composite marginal likelihood; and modelling and forecasting volatility in a bayesian approach.
Discrete Choice Methods with Simulation
Kenneth Train
Author : Kenneth Train
Publisher : Cambridge University Press
Page : 399 pages
File Size : 53,8 Mb
Release : 2009-07-06
Category : Business & Economics
ISBN : 9780521766555
Discrete Choice Methods with Simulation by Kenneth Train Pdf
This book describes the new generation of discrete choice methods, focusing on the many advances that are made possible by simulation. Researchers use these statistical methods to examine the choices that consumers, households, firms, and other agents make. Each of the major models is covered: logit, generalized extreme value, or GEV (including nested and cross-nested logits), probit, and mixed logit, plus a variety of specifications that build on these basics. Simulation-assisted estimation procedures are investigated and compared, including maximum stimulated likelihood, method of simulated moments, and method of simulated scores. Procedures for drawing from densities are described, including variance reduction techniques such as anithetics and Halton draws. Recent advances in Bayesian procedures are explored, including the use of the Metropolis-Hastings algorithm and its variant Gibbs sampling. The second edition adds chapters on endogeneity and expectation-maximization (EM) algorithms. No other book incorporates all these fields, which have arisen in the past 25 years. The procedures are applicable in many fields, including energy, transportation, environmental studies, health, labor, and marketing.
Simulation Based Estimation of Some Factor Models in Econometrics
Adrian Rodney Pagan,Vance L. Martin
Author : Adrian Rodney Pagan,Vance L. Martin
Publisher : Unknown
Page : 39 pages
File Size : 42,7 Mb
Release : 1996
Category : Econometric models
ISBN : 073251391X
Simulation Based Estimation of Some Factor Models in Econometrics by Adrian Rodney Pagan,Vance L. Martin Pdf
Introductory Econometrics
Humberto Barreto,Frank Howland
Author : Humberto Barreto,Frank Howland
Publisher : Cambridge University Press
Page : 810 pages
File Size : 48,8 Mb
Release : 2006
Category : Business & Economics
ISBN : 0521843197
Introductory Econometrics by Humberto Barreto,Frank Howland Pdf
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.
Monte Carlo Simulation for Econometricians
Jan F. Kiviet
Author : Jan F. Kiviet
Publisher : Foundations & Trends
Page : 185 pages
File Size : 45,7 Mb
Release : 2012
Category : Business & Economics
ISBN : 160198538X
Monte Carlo Simulation for Econometricians by Jan F. Kiviet Pdf
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.
Simulation Methods in Econometric Analysis
Sheng-Kai Chang
Author : Sheng-Kai Chang
Publisher : Unknown
Page : 108 pages
File Size : 49,6 Mb
Release : 2002
Category : Electronic
ISBN : WISC:89085197960
Simulation Methods in Econometric Analysis by Sheng-Kai Chang Pdf
Generalized Method of Moments Estimation
Laszlo Matyas
Author : Laszlo Matyas
Publisher : Cambridge University Press
Page : 332 pages
File Size : 43,9 Mb
Release : 1999-04-13
Category : Business & Economics
ISBN : 0521669677
Generalized Method of Moments Estimation by Laszlo Matyas Pdf
The principal objective of this volume is to offer a complete presentation of the theory of GMM estimation.
Structural Econometric Models
Eugene Choo,Matthew Shum
Author : Eugene Choo,Matthew Shum
Publisher : Emerald Group Publishing
Page : 350 pages
File Size : 52,6 Mb
Release : 2013-12-18
Category : Business & Economics
ISBN : 9781783500536
Structural Econometric Models by Eugene Choo,Matthew Shum Pdf
This volume focuses on recent developments in the use of structural econometric models in empirical economics. The first part looks at recent developments in the estimation of dynamic discrete choice models. The second part looks at recent advances in the area empirical matching models.
Microeconometrics
A. Colin Cameron,Pravin K. Trivedi
Author : A. Colin Cameron,Pravin K. Trivedi
Publisher : Cambridge University Press
Page : 128 pages
File Size : 42,9 Mb
Release : 2005-05-09
Category : Business & Economics
ISBN : 9781139444866
Microeconometrics by A. Colin Cameron,Pravin K. Trivedi Pdf
This book provides the most comprehensive treatment to date of microeconometrics, the analysis of individual-level data on the economic behavior of individuals or firms using regression methods for cross section and panel data. The book is oriented to the practitioner. A basic understanding of the linear regression model with matrix algebra is assumed. The text can be used for a microeconometrics course, typically a second-year economics PhD course; for data-oriented applied microeconometrics field courses; and as a reference work for graduate students and applied researchers who wish to fill in gaps in their toolkit. Distinguishing features of the book include emphasis on nonlinear models and robust inference, simulation-based estimation, and problems of complex survey data. The book makes frequent use of numerical examples based on generated data to illustrate the key models and methods. More substantially, it systematically integrates into the text empirical illustrations based on seven large and exceptionally rich data sets.
Applications of Simulation Methods in Environmental and Resource Economics
Riccardo Scarpa,Anna Alberini
Author : Riccardo Scarpa,Anna Alberini
Publisher : Springer Science & Business Media
Page : 456 pages
File Size : 40,8 Mb
Release : 2005-08-12
Category : Business & Economics
ISBN : 1402036833
Applications of Simulation Methods in Environmental and Resource Economics by Riccardo Scarpa,Anna Alberini Pdf
Simulation methods are revolutionizing the practice of applied economic analysis. In this book, leading researchers from around the world discuss interpretation issues, similarities and differences across alternative models, and propose practical solutions for the choice of the model and programming. Case studies show the practical use and the results brought forth by the different methods.
Econometric Modelling with Time Series
Vance Martin,Stan Hurn,David Harris
Author : Vance Martin,Stan Hurn,David Harris
Publisher : Cambridge University Press
Page : 925 pages
File Size : 43,6 Mb
Release : 2013
Category : Business & Economics
ISBN : 9780521139816
Econometric Modelling with Time Series by Vance Martin,Stan Hurn,David Harris Pdf
"Maximum likelihood estimation is a general method for estimating the parameters of econometric models from observed data. The principle of maximum likelihood plays a central role in the exposition of this book, since a number of estimators used in econometrics can be derived within this framework. Examples include ordinary least squares, generalized least squares and full-information maximum likelihood. In deriving the maximum likelihood estimator, a key concept is the joint probability density function (pdf) of the observed random variables, yt. Maximum likelihood estimation requires that the following conditions are satisfied. (1) The form of the joint pdf of yt is known. (2) The specification of the moments of the joint pdf are known. (3) The joint pdf can be evaluated for all values of the parameters, 9. Parts ONE and TWO of this book deal with models in which all these conditions are satisfied. Part THREE investigates models in which these conditions are not satisfied and considers four important cases. First, if the distribution of yt is misspecified, resulting in both conditions 1 and 2 being violated, estimation is by quasi-maximum likelihood (Chapter 9). Second, if condition 1 is not satisfied, a generalized method of moments estimator (Chapter 10) is required. Third, if condition 2 is not satisfied, estimation relies on nonparametric methods (Chapter 11). Fourth, if condition 3 is violated, simulation-based estimation methods are used (Chapter 12). 1.2 Motivating Examples To highlight the role of probability distributions in maximum likelihood estimation, this section emphasizes the link between observed sample data and 4 The Maximum Likelihood Principle the probability distribution from which they are drawn"-- publisher.