Download or read book Discrete Choice Methods with Simulation written by Kenneth Train and published by Cambridge University Press. This book was released on 2009-07-06 with total page 399 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Discrete Choice Methods with Simulation written by Kenneth Train and published by Cambridge University Press. This book was released on 2003-01-13 with total page 346 pages. Available in PDF, EPUB and Kindle. Book excerpt: Table of contents

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.

Download or read book Bayesian Estimation of DSGE Models written by Edward P. Herbst and published by Princeton University Press. This book was released on 2015-12-29 with total page 295 pages. Available in PDF, EPUB and Kindle. Book excerpt: Dynamic stochastic general equilibrium (DSGE) models have become one of the workhorses of modern macroeconomics and are extensively used for academic research as well as forecasting and policy analysis at central banks. This book introduces readers to state-of-the-art computational techniques used in the Bayesian analysis of DSGE models. The book covers Markov chain Monte Carlo techniques for linearized DSGE models, novel sequential Monte Carlo methods that can be used for parameter inference, and the estimation of nonlinear DSGE models based on particle filter approximations of the likelihood function. The theoretical foundations of the algorithms are discussed in depth, and detailed empirical applications and numerical illustrations are provided. The book also gives invaluable advice on how to tailor these algorithms to specific applications and assess the accuracy and reliability of the computations. Bayesian Estimation of DSGE Models is essential reading for graduate students, academic researchers, and practitioners at policy institutions.

Download or read book Econometric Models For Industrial Organization written by Matthew Shum and published by World Scientific. This book was released on 2016-12-14 with total page 154 pages. Available in PDF, EPUB and Kindle. Book excerpt: Economic Models for Industrial Organization focuses on the specification and estimation of econometric models for research in industrial organization. In recent decades, empirical work in industrial organization has moved towards dynamic and equilibrium models, involving econometric methods which have features distinct from those used in other areas of applied economics. These lecture notes, aimed for a first or second-year PhD course, motivate and explain these econometric methods, starting from simple models and building to models with the complexity observed in typical research papers. The covered topics include discrete-choice demand analysis, models of dynamic behavior and dynamic games, multiple equilibria in entry games and partial identification, and auction models.

Download or read book The New Palgrave Dictionary of Economics written by and published by Springer. This book was released on 2016-05-18 with total page 7493 pages. Available in PDF, EPUB and Kindle. Book excerpt: The award-winning The New Palgrave Dictionary of Economics, 2nd edition is now available as a dynamic online resource. Consisting of over 1,900 articles written by leading figures in the field including Nobel prize winners, this is the definitive scholarly reference work for a new generation of economists. Regularly updated! This product is a subscription based product.

Download or read book Structural Econometric Modeling in Industrial Organization and Quantitative Marketing written by Ali Hortaçsu and published by Princeton University Press. This book was released on 2023-10-24 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Within economics a relatively new way of modeling has dominated important subfields: structural modeling. The goal of this book is to give an overview on how the various streams of literatures in empirical industrial organization and quantitative marketing use structural econometric modeling to estimate the model parameters, give the economic-model-based predictions, and conduct the policy counterfactual experiments. The traditional way of modelling, called "reduced-form" builds its models from simple relationships between variables of interests, which are mostly linear. Structural econometric models start by specifying the structure of the economic model, and the variables are calibrated from real-world data. This method enables better predictions and policy counterfactuals, and has other benefits. When considering a hypothetical policy change using the traditional modeling method ("reduced form"), researchers can often only estimate whether an effect would be positive or negative. With a structural econometric model using real-world data, a researcher can obtain the magnitude of the effects resulting from a hypothetical change. But the ability of quantifying the effects associated with a hypothetical policy change comes with its costs: the nonlinearity from explicitly specifying the possible relationships makes the structural econometric approach generally much more difficult to implement than its reduced-form counterpart. Therefore this book will provide a much-needed resource on how to use these methods effectively in the fields in which they been used the most, empirical industrial organization and quantitative marketing"--

Download or read book Discrete Choice Methods with Simulation written by Kenneth E. Train and published by Cambridge University Press. This book was released on 2009-06-30 with total page 399 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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. Recent advances in Bayesian procedures are explored, including the use of the Metropolis-Hastings algorithm and its variant Gibbs sampling. This 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.

Download or read book Modeling Ordered Choices written by William H. Greene and published by Cambridge University Press. This book was released on 2010-04-08 with total page 383 pages. Available in PDF, EPUB and Kindle. Book excerpt: It is increasingly common for analysts to seek out the opinions of individuals and organizations using attitudinal scales such as degree of satisfaction or importance attached to an issue. Examples include levels of obesity, seriousness of a health condition, attitudes towards service levels, opinions on products, voting intentions, and the degree of clarity of contracts. Ordered choice models provide a relevant methodology for capturing the sources of influence that explain the choice made amongst a set of ordered alternatives. The methods have evolved to a level of sophistication that can allow for heterogeneity in the threshold parameters, in the explanatory variables (through random parameters), and in the decomposition of the residual variance. This book brings together contributions in ordered choice modeling from a number of disciplines, synthesizing developments over the last fifty years, and suggests useful extensions to account for the wide range of sources of influence on choice.

Download or read book Advances in Economics and Econometrics Volume 3 Econometrics written by Daron Acemoglu and published by Cambridge University Press. This book was released on 2013-05-13 with total page 633 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the third of three volumes containing edited versions of papers and commentaries presented at invited symposium sessions of the Tenth World Congress of the Econometric Society, held in Shanghai in August 2010. The papers summarize and interpret key developments in economics and econometrics, and they discuss future directions for a wide variety of topics, covering both theory and application. Written by the leading specialists in their fields, these volumes provide a unique, accessible survey of progress on the discipline. The first volume primarily addresses economic theory, with specific focuses on nonstandard markets, contracts, decision theory, communication and organizations, epistemics and calibration, and patents.

Download or read book Advances in Economics and Econometrics written by Econometric Society. World Congress and published by Cambridge University Press. This book was released on 2013-05-27 with total page 633 pages. Available in PDF, EPUB and Kindle. Book excerpt: The third volume of edited papers from the Tenth World Congress of the Econometric Society 2010.

Download or read book Handbook of Econometrics written by J.J. Heckman and published by Elsevier. This book was released on 2001-11-22 with total page 737 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Handbook is a definitive reference source and teaching aid for econometricians. It examines models, estimation theory, data analysis and field applications in econometrics. Comprehensive surveys, written by experts, discuss recent developments at a level suitable for professional use by economists, econometricians, statisticians, and in advanced graduate econometrics courses. For more information on the Handbooks in Economics series, please see our home page on http://www.elsevier.nl/locate/hes

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.

Download or read book The Limits of Inference without Theory written by Kenneth I. Wolpin and published by MIT Press. This book was released on 2013-04-26 with total page 197 pages. Available in PDF, EPUB and Kindle. Book excerpt: The role of theory in ex ante policy evaluations and the limits that eschewing theory places on inference In this rigorous and well-crafted work, Kenneth Wolpin examines the role of theory in inferential empirical work in economics and the social sciences in general—that is, any research that uses raw data to go beyond the mere statement of fact or the tabulation of statistics. He considers in particular the limits that eschewing the use of theory places on inference. Wolpin finds that the absence of theory in inferential work that addresses microeconomic issues is pervasive. That theory is unnecessary for inference is exemplified by the expression “let the data speak for themselves.” This approach is often called “reduced form.” A more nuanced view is based on the use of experiments or quasi-experiments to draw inferences. Atheoretical approaches stand in contrast to what is known as the structuralist approach, which requires that a researcher specify an explicit model of economic behavior—that is, a theory. Wolpin offers a rigorous examination of both structuralist and nonstructuralist approaches. He first considers ex ante policy evaluation, highlighting the role of theory in the implementation of parametric and nonparametric estimation strategies. He illustrates these strategies with two examples, a wage tax and a school attendance subsidy, and summarizes the results from applications. He then presents a number of examples that illustrate the limits of inference without theory: the effect of unemployment benefits on unemployment duration; the effect of public welfare on women's labor market and demographic outcomes; the effect of school attainment on earnings; and a famous field experiment in education dealing with class size. Placing each example within the context of the broader literature, he contrasts them to recent work that relies on theory for inference.

Download or read book Dynamic Linear Models with R written by Giovanni Petris and published by Springer Science & Business Media. This book was released on 2009-06-12 with total page 258 pages. Available in PDF, EPUB and Kindle. Book excerpt: State space models have gained tremendous popularity in recent years in as disparate fields as engineering, economics, genetics and ecology. After a detailed introduction to general state space models, this book focuses on dynamic linear models, emphasizing their Bayesian analysis. Whenever possible it is shown how to compute estimates and forecasts in closed form; for more complex models, simulation techniques are used. A final chapter covers modern sequential Monte Carlo algorithms. The book illustrates all the fundamental steps needed to use dynamic linear models in practice, using R. Many detailed examples based on real data sets are provided to show how to set up a specific model, estimate its parameters, and use it for forecasting. All the code used in the book is available online. No prior knowledge of Bayesian statistics or time series analysis is required, although familiarity with basic statistics and R is assumed.

Download or read book Econometrics as a Con Art written by Imad A. Moosa and published by Edward Elgar Publishing. This book was released on 2017-07-28 with total page 253 pages. Available in PDF, EPUB and Kindle. Book excerpt: Imad Moosa challenges convention with this comprehensive and compelling critique of econometrics, condemning the common practices of misapplied statistical methods in both economics and finance.

Download or read book The Oxford Handbook of Bayesian Econometrics written by John Geweke and published by Oxford University Press. This book was released on 2011-09-29 with total page 576 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bayesian econometric methods have enjoyed an increase in popularity in recent years. Econometricians, empirical economists, and policymakers are increasingly making use of Bayesian methods. This handbook is a single source for researchers and policymakers wanting to learn about Bayesian methods in specialized fields, and for graduate students seeking to make the final step from textbook learning to the research frontier. It contains contributions by leading Bayesians on the latest developments in their specific fields of expertise. The volume provides broad coverage of the application of Bayesian econometrics in the major fields of economics and related disciplines, including macroeconomics, microeconomics, finance, and marketing. It reviews the state of the art in Bayesian econometric methodology, with chapters on posterior simulation and Markov chain Monte Carlo methods, Bayesian nonparametric techniques, and the specialized tools used by Bayesian time series econometricians such as state space models and particle filtering. It also includes chapters on Bayesian principles and methodology.