Simulation Methods in Econometric Analysis PDF Download

Author: Riccardo Scarpa
Publisher: Springer Science & Business Media
ISBN: 9781402036835
Category : Business & Economics
Languages : en
Pages : 456

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Book Description
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.

Author: Sheng-Kai Chang
Publisher:
ISBN:
Category :
Languages : en
Pages : 108

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Book Description

Author: Roberto Mariano
Publisher: Cambridge University Press
ISBN: 9780521591126
Category : Business & Economics
Languages : en
Pages : 488

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Book Description
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: Kenneth Train
Publisher: Cambridge University Press
ISBN: 0521766559
Category : Business & Economics
Languages : en
Pages : 399

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Book Description
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.

Author: Jan F. Kiviet
Publisher: Foundations & Trends
ISBN: 9781601985385
Category : Business & Economics
Languages : en
Pages : 185

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Book Description
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
ISBN: 9780521843195
Category : Business & Economics
Languages : en
Pages : 810

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Book Description
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: Robert C. Meier
Publisher: Prentice Hall
ISBN:
Category : Business & Economics
Languages : en
Pages : 392

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Book Description
Management development guide on simulation techniques applicable to scientific management and economics - covers pert (network analysis), business organization, quality control, models of dynamics in industry, econometrics, computer programmes and language, systems design, etc. Bibliography at the end of each chapter.

Author: Herman K. van Dijk
Publisher:
ISBN:
Category : Business & Economics
Languages : en
Pages : 290

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Book Description
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.

Author: Thomas H. Naylor
Publisher:
ISBN:
Category : Computer simulation
Languages : en
Pages : 376

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Book Description
Provides a detailed treatment of the methods and procedures involved in planning and designing computer simulation experiments as well as the theory on which these methods are based.

Author: Marco Bee
Publisher:
ISBN:
Category : Business & Economics
Languages : en
Pages : 124

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Book Description
In this book the authors present a reassessment of some recently proposed econometric methods for the analysis of continuous-time specifications of economic models. Given the vastness of this stream of the literature, that does not allow for a full exposition of the topic, the authors concentrate on the estimation and simulation analysis of a continuous-time econometric model based on a theoretical framework -- the SETI model -- developed in Padoan (1996). The application is almost completely instrumental to a more thorough analysis of methodological issues entailed with continuous-time econometrics. Nevertheless, it presents some interesting theoretical aspects such as the process of diffusion of ICT and the role of services in international diffusion of technology. The standard methods are not suitable for theoretical models in which disequilibrium analysis is necessary and, in general, presents a clear limitation when the structural multi-equation form of the model should be preserved. Thus the authors show how, by means of continuous-time econometric, it is possible to estimate the parameters of the model using the Full Information Maximum Likelihood techniques in a time series set-up. Then, the authors extend the econometric analysis in order to evaluate the out-of-equilibrium dynamic properties of a system via simulation techniques. The declared aim of the present work is to define the conditions to the equilibrium and to discuss its stability properties. Furthermore, the application provides the guidelines for the formulation and empirical validation of a model considering growth-driven-by-technology phenomena, interactions between countries through trade effects, and the diffusion of technology. Finally, spatial aspects of the problem are explicitly taken into account.