Monte Carlo simulation for econometricians
著者
書誌事項
Monte Carlo simulation for econometricians
（Foundations and trends in econometrics, 5:1-2）
now Publishers, c2012
- : pbk
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注記
"This book is originally published as Foundations and trends in econometrics, Volume 5 issues 1-2, ISSN: 1551-3076"--Backcover
Includes bibliographical references (p. 183-185)
内容説明・目次
内容説明
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.
目次
Preface and Overview. 1. Introduction to classic Monte Carlo simulation. 2. Monte Carlo assessment of moments. 3. Monte Carlo assessment of probabilities and quantiles. 4. Monte Carlo analysis of asymptotic inference. 5. Further issues regarding classic MCS. 6. Monte Carlo tests and bootstrap inference. Appendices. References.
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