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Estimation Of Dynamic Discrete Choice Models By Maximum Likelihood And The Simulated Method Of Moments
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Book Synopsis Estimation of Dynamic Discrete Choice Models by Maximum Likelihood and the Simulated Method of Moments by : Phillipp Eisenhauer
Download or read book Estimation of Dynamic Discrete Choice Models by Maximum Likelihood and the Simulated Method of Moments written by Phillipp Eisenhauer and published by . This book was released on 2014 with total page 47 pages. Available in PDF, EPUB and Kindle. Book excerpt: We compare the performance of maximum likelihood (ML) and simulated method of moments (SMM) estimation for dynamic discrete choice models. We construct and estimate a simplified dynamic structural model of education that captures some basic features of educational choices in the United States in the 1980s and early 1990s. We use estimates from our model to simulate a synthetic dataset and assess the ability of ML and SMM to recover the model parameters on this sample. We investigate the performance of alternative tuning parameters for SMM.
Book Synopsis Estimation Od Dynamic Discrete Choice Models by Maximum Likelihood and the Simulated Method of Moments by : Philipp Eisenhauer
Download or read book Estimation Od Dynamic Discrete Choice Models by Maximum Likelihood and the Simulated Method of Moments written by Philipp Eisenhauer and published by . This book was released on 2014 with total page 47 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Discrete Choice Methods with Simulation by : Kenneth Train
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.
Book Synopsis Simulated Maximum Likelihood Estimation of Dynamic Discrete Choice Statistical Models by : Lung-Fei Lee
Download or read book Simulated Maximum Likelihood Estimation of Dynamic Discrete Choice Statistical Models written by Lung-Fei Lee and published by . This book was released on 1994 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Simulated Maximum Likelihood Estimation of Discrete Models with Group Data by : Lung-Fei Lee
Download or read book Simulated Maximum Likelihood Estimation of Discrete Models with Group Data written by Lung-Fei Lee and published by . This book was released on 1993 with total page 23 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Handbook of Choice Modelling by : Stephane Hess
Download or read book Handbook of Choice Modelling written by Stephane Hess and published by Edward Elgar Publishing. This book was released on 2024-06-05 with total page 797 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thoroughly revised second edition Handbook provides an authoritative and in-depth overview of choice modelling, covering essential topics range from data collection through model specification and estimation to analysis and use of results. It aptly emphasises the broad relevance of choice modelling when applied to a multitude of fields, including but not limited to transport, marketing, health and environmental economics.
Book Synopsis Estimation of Dynamic Models with Nonparametric Simulated Maximum Likelihood by : Dennis Kristensen
Download or read book Estimation of Dynamic Models with Nonparametric Simulated Maximum Likelihood written by Dennis Kristensen and published by . This book was released on 2006 with total page 36 pages. Available in PDF, EPUB and Kindle. Book excerpt: We propose a simulated maximum likelihood estimator (SMLE) for general stochastic dynamic models based on nonparametric kernel methods. The method requires that, while the actual likelihood function cannot be written down, we can still simulate observations from the model. From the simulated observations, we estimate the unknown density of the model nonparametrically by kernel methods, and then obtain the SMLEs of the model parameters. Our method avoids the issue of non-identification arising from poor choice of auxiliary models in simulated methods of moments (SMM) or indirect inference. More importantly, our SMLEs achieve higher efficiency under weak regularity conditions. Finally, our method allows for potentially nonstationary processes, including time-inhomogeneous dynamics.
Book Synopsis Applied Discrete-Choice Modelling by : David A. Hensher
Download or read book Applied Discrete-Choice Modelling written by David A. Hensher and published by Routledge. This book was released on 2018-04-09 with total page 485 pages. Available in PDF, EPUB and Kindle. Book excerpt: Originally published in 1981. Discrete-choice modelling is an area of econometrics where significant advances have been made at the research level. This book presents an overview of these advances, explaining the theory underlying the model, and explores its various applications. It shows how operational choice models can be used, and how they are particularly useful for a better understanding of consumer demand theory. It discusses particular problems connected with the model and its use, and reports on the authors’ own empirical research. This is a comprehensive survey of research developments in discrete choice modelling and its applications.
Book Synopsis Asymptotic Bias in Maximum Simulated Likelihood Estimation of Discrete Choice Models by : Lung-Fei Lee
Download or read book Asymptotic Bias in Maximum Simulated Likelihood Estimation of Discrete Choice Models written by Lung-Fei Lee and published by . This book was released on 1992 with total page 26 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Maximum Simulated Likelihood Methods and Applications by : William Greene
Download or read book Maximum Simulated Likelihood Methods and Applications written by William Greene and published by Emerald Group Publishing. This book was released on 2010-12-03 with total page 371 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Efficient Estimation of Discrete-choice Models from Choice-based Samples by : Stephen Rhys Cosslett
Download or read book Efficient Estimation of Discrete-choice Models from Choice-based Samples written by Stephen Rhys Cosslett and published by . This book was released on 1979 with total page 498 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Maximum Likelihood Estimation of Controlled Discrete Choice Processes by : John Philip Rust
Download or read book Maximum Likelihood Estimation of Controlled Discrete Choice Processes written by John Philip Rust and published by . This book was released on 1984 with total page 80 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Discrete Choice Methods with Simulation by : Kenneth Train
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
Book Synopsis Econometric Models For Industrial Organization by : Matthew Shum
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.
Book Synopsis Simulation-based Econometric Methods by : Christian Gouriéroux
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.
Book Synopsis Masking Identification of Discrete Choice Models Under Simulation Methods by : Lesley Chiou
Download or read book Masking Identification of Discrete Choice Models Under Simulation Methods written by Lesley Chiou and published by . This book was released on 2008 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: We present examples based on actual and synthetic datasets to illustrate how simulation methods can mask identification problems in the estimation of discrete choice models such as mixed logit. Simulation methods approximate an integral (without a closed form) by taking draws from the underlying distribution of the random variable of integration. Our examples reveal how a low number of draws can generate estimates that appear identified, but in fact, are either not theoretically identified by the model or not empirically identified by the data. For the particular case of maximum simulated likelihood estimation, we investigate the underlying source of the problem by focusing on the shape of the simulated log-likelihood function under different conditions.
Book Synopsis Essays on the Simulation-based Estimation of Dynamic Discrete Choice Models by : Ben Waltmann
Download or read book Essays on the Simulation-based Estimation of Dynamic Discrete Choice Models written by Ben Waltmann and published by . This book was released on 2021 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
