Estimation Of Dynamic Discrete Choice Models By Maximum Likelihood And The Simulated Method Of Moments PDF Download
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Author | : Phillipp Eisenhauer |
Publisher | : |
Total Pages | : 47 |
Release | : 2014 |
Genre | : Decision making |
ISBN | : |
Download Estimation of Dynamic Discrete Choice Models by Maximum Likelihood and the Simulated Method of Moments Book in PDF, ePub and Kindle
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.
Author | : Philipp Eisenhauer |
Publisher | : |
Total Pages | : 47 |
Release | : 2014 |
Genre | : |
ISBN | : |
Download Estimation Od Dynamic Discrete Choice Models by Maximum Likelihood and the Simulated Method of Moments Book in PDF, ePub and Kindle
Author | : Kenneth Train |
Publisher | : Cambridge University Press |
Total Pages | : 399 |
Release | : 2009-07-06 |
Genre | : Business & Economics |
ISBN | : 0521766559 |
Download Discrete Choice Methods with Simulation Book in PDF, ePub and Kindle
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 | : Lung-Fei Lee |
Publisher | : |
Total Pages | : 0 |
Release | : 1994 |
Genre | : Monte Carlo method |
ISBN | : |
Download Simulated Maximum Likelihood Estimation of Dynamic Discrete Choice Statistical Models Book in PDF, ePub and Kindle
Author | : Lung-Fei Lee |
Publisher | : |
Total Pages | : 23 |
Release | : 1993 |
Genre | : Estimation theory |
ISBN | : |
Download Simulated Maximum Likelihood Estimation of Discrete Models with Group Data Book in PDF, ePub and Kindle
Author | : Stephane Hess |
Publisher | : Edward Elgar Publishing |
Total Pages | : 797 |
Release | : 2024-06-05 |
Genre | : Business & Economics |
ISBN | : 1800375638 |
Download Handbook of Choice Modelling Book in PDF, ePub and Kindle
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.
Author | : Dennis Kristensen |
Publisher | : |
Total Pages | : 36 |
Release | : 2006 |
Genre | : |
ISBN | : |
Download Estimation of Dynamic Models with Nonparametric Simulated Maximum Likelihood Book in PDF, ePub and Kindle
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.
Author | : David A. Hensher |
Publisher | : Routledge |
Total Pages | : 485 |
Release | : 2018-04-09 |
Genre | : Business & Economics |
ISBN | : 1351140752 |
Download Applied Discrete-Choice Modelling Book in PDF, ePub and Kindle
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.
Author | : Lung-Fei Lee |
Publisher | : |
Total Pages | : 26 |
Release | : 1992 |
Genre | : Estimation theory |
ISBN | : |
Download Asymptotic Bias in Maximum Simulated Likelihood Estimation of Discrete Choice Models Book in PDF, ePub and Kindle
Author | : William Greene |
Publisher | : Emerald Group Publishing |
Total Pages | : 371 |
Release | : 2010-12-03 |
Genre | : Business & Economics |
ISBN | : 0857241508 |
Download Maximum Simulated Likelihood Methods and Applications Book in PDF, ePub and Kindle
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.