Monte Carlo Simulation For Econometricians PDF Download
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Author | : Jan F. Kiviet |
Publisher | : Foundations & Trends |
Total Pages | : 185 |
Release | : 2012 |
Genre | : Business & Economics |
ISBN | : 9781601985385 |
Download Monte Carlo Simulation for Econometricians Book in PDF, ePub and Kindle
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.
Author | : Humberto Barreto |
Publisher | : Cambridge University Press |
Total Pages | : 810 |
Release | : 2006 |
Genre | : Business & Economics |
ISBN | : 9780521843195 |
Download Introductory Econometrics Book in PDF, ePub and Kindle
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.
Author | : Jan Frederik Kiviet |
Publisher | : |
Total Pages | : 197 |
Release | : 2012 |
Genre | : Econometrics |
ISBN | : 9781601985392 |
Download Monte Carlo Simulation for Econometricians Book in PDF, ePub and Kindle
Many studies in econometric theory are supplemented by Monte Carlo simulation investigations. These illustrate the properties of alternative inference techniques when applied to samples drawn from mostly entirely synthetic data generating processes. They should provide information on how techniques, which may be sound asymptotically, perform in finite samples and then unveil the effects of model characteristics too complex to analyze analytically. Also the interpretation of applied studies should often benefit when supplemented by a dedicated simulation study, based on a design inspired by the postulated actual empirical data generating process, which would come close to bootstrapping. This review presents and illustrates the fundamentals of conceiving and executing such simulation studies, especially synthetic but also more dedicated, focussing on controlling their accuracy, increasing their efficiency, recognizing their limitations, presenting their results in a coherent and palatable way, and on the appropriate interpretation of their actual findings, especially when the simulation study is used to rank the qualities of alternative inference techniques.
Author | : Paolo Brandimarte |
Publisher | : John Wiley & Sons |
Total Pages | : 620 |
Release | : 2014-06-20 |
Genre | : Business & Economics |
ISBN | : 1118594517 |
Download Handbook in Monte Carlo Simulation Book in PDF, ePub and Kindle
An accessible treatment of Monte Carlo methods, techniques, and applications in the field of finance and economics Providing readers with an in-depth and comprehensive guide, the Handbook in Monte Carlo Simulation: Applications in Financial Engineering, Risk Management, and Economics presents a timely account of the applicationsof Monte Carlo methods in financial engineering and economics. Written by an international leading expert in thefield, the handbook illustrates the challenges confronting present-day financial practitioners and provides various applicationsof Monte Carlo techniques to answer these issues. The book is organized into five parts: introduction andmotivation; input analysis, modeling, and estimation; random variate and sample path generation; output analysisand variance reduction; and applications ranging from option pricing and risk management to optimization. The Handbook in Monte Carlo Simulation features: An introductory section for basic material on stochastic modeling and estimation aimed at readers who may need a summary or review of the essentials Carefully crafted examples in order to spot potential pitfalls and drawbacks of each approach An accessible treatment of advanced topics such as low-discrepancy sequences, stochastic optimization, dynamic programming, risk measures, and Markov chain Monte Carlo methods Numerous pieces of R code used to illustrate fundamental ideas in concrete terms and encourage experimentation The Handbook in Monte Carlo Simulation: Applications in Financial Engineering, Risk Management, and Economics is a complete reference for practitioners in the fields of finance, business, applied statistics, econometrics, and engineering, as well as a supplement for MBA and graduate-level courses on Monte Carlo methods and simulation.
Author | : Paul Glasserman |
Publisher | : Springer Science & Business Media |
Total Pages | : 603 |
Release | : 2013-03-09 |
Genre | : Mathematics |
ISBN | : 0387216170 |
Download Monte Carlo Methods in Financial Engineering Book in PDF, ePub and Kindle
From the reviews: "Paul Glasserman has written an astonishingly good book that bridges financial engineering and the Monte Carlo method. The book will appeal to graduate students, researchers, and most of all, practicing financial engineers [...] So often, financial engineering texts are very theoretical. This book is not." --Glyn Holton, Contingency Analysis
Author | : Christian Robert |
Publisher | : Springer Science & Business Media |
Total Pages | : 297 |
Release | : 2010 |
Genre | : Computers |
ISBN | : 1441915753 |
Download Introducing Monte Carlo Methods with R Book in PDF, ePub and Kindle
This book covers the main tools used in statistical simulation from a programmer’s point of view, explaining the R implementation of each simulation technique and providing the output for better understanding and comparison.
Author | : Roberto Mariano |
Publisher | : Cambridge University Press |
Total Pages | : 488 |
Release | : 2000-07-20 |
Genre | : Business & Economics |
ISBN | : 9780521591126 |
Download Simulation-based Inference in Econometrics Book in PDF, ePub and Kindle
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.
Author | : Jun S. Liu |
Publisher | : Springer Science & Business Media |
Total Pages | : 350 |
Release | : 2013-11-11 |
Genre | : Mathematics |
ISBN | : 0387763716 |
Download Monte Carlo Strategies in Scientific Computing Book in PDF, ePub and Kindle
This book provides a self-contained and up-to-date treatment of the Monte Carlo method and develops a common framework under which various Monte Carlo techniques can be "standardized" and compared. Given the interdisciplinary nature of the topics and a moderate prerequisite for the reader, this book should be of interest to a broad audience of quantitative researchers such as computational biologists, computer scientists, econometricians, engineers, probabilists, and statisticians. It can also be used as a textbook for a graduate-level course on Monte Carlo methods.
Author | : Siddhartha Chib |
Publisher | : |
Total Pages | : 32 |
Release | : 1994 |
Genre | : |
ISBN | : |
Download Markov Chain Monte Carlo Simulation Methods in Econometrics Book in PDF, ePub and Kindle
Author | : David F. Hendry |
Publisher | : Princeton University Press |
Total Pages | : 378 |
Release | : 2012-06-21 |
Genre | : Business & Economics |
ISBN | : 1400845653 |
Download Econometric Modeling Book in PDF, ePub and Kindle
Econometric Modeling provides a new and stimulating introduction to econometrics, focusing on modeling. The key issue confronting empirical economics is to establish sustainable relationships that are both supported by data and interpretable from economic theory. The unified likelihood-based approach of this book gives students the required statistical foundations of estimation and inference, and leads to a thorough understanding of econometric techniques. David Hendry and Bent Nielsen introduce modeling for a range of situations, including binary data sets, multiple regression, and cointegrated systems. In each setting, a statistical model is constructed to explain the observed variation in the data, with estimation and inference based on the likelihood function. Substantive issues are always addressed, showing how both statistical and economic assumptions can be tested and empirical results interpreted. Important empirical problems such as structural breaks, forecasting, and model selection are covered, and Monte Carlo simulation is explained and applied. Econometric Modeling is a self-contained introduction for advanced undergraduate or graduate students. Throughout, data illustrate and motivate the approach, and are available for computer-based teaching. Technical issues from probability theory and statistical theory are introduced only as needed. Nevertheless, the approach is rigorous, emphasizing the coherent formulation, estimation, and evaluation of econometric models relevant for empirical research.