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Discrete Continuous Dynamic Choice Models Identification And Conditional Choice Probability Estimation
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Book Synopsis Discrete-continuous Dynamic Choice Models: Identification and Conditional Choice Probability Estimation by : Christophe Alain Bruneel-Zupanc
Download or read book Discrete-continuous Dynamic Choice Models: Identification and Conditional Choice Probability Estimation written by Christophe Alain Bruneel-Zupanc and published by . This book was released on 2021 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Conditional Choice Probabilities and the Estimation of Dynamic Discrete Choice Models by : V. Joseph Hotz
Download or read book Conditional Choice Probabilities and the Estimation of Dynamic Discrete Choice Models written by V. Joseph Hotz and published by . This book was released on 1988 with total page 51 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Estimation of Dynamic Discrete Choice Models in Continuous Time! by :
Download or read book Estimation of Dynamic Discrete Choice Models in Continuous Time! written by and published by . This book was released on 2010 with total page 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 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 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 Nonparametric Identification and Estimation of Finite Mixture Models of Dynamic Discrete Choices by : Hiroyuki Kasahara
Download or read book Nonparametric Identification and Estimation of Finite Mixture Models of Dynamic Discrete Choices written by Hiroyuki Kasahara and published by . This book was released on 2006 with total page 45 pages. Available in PDF, EPUB and Kindle. Book excerpt: In dynamic discrete choice analysis, controlling for unobserved heterogeneity is an im- portant issue, and finite mixture models provide flexible ways to account for unobserved heterogeneity. This paper studies nonparametric identifiability of type probabilities and type-specific component distributions in finite mixture models of dynamic discrete choices. We derive sufficient conditions for nonparametric identification for various finite mixture models of dynamic discrete choices used in applied work. Three elements emerge as the important determinants of identification; the time-dimension of panel data, the number of values the covariates can take, and the heterogeneity of the response of different types to changes in the covariates. For example, in a simple case, a time-dimension of T = 3 is sufficient for identification, provided that the number of values the covariates can take is no smaller than the number of types, and that the changes in the covariates induce sufficiently heterogeneous variations in the choice probabilities across types. Type-specific components are identifiable even when state dependence is present as long as the panel has a moderate time-dimension ( T {u2265} 6). We also develop a series logit estimator for finite mixture models of dynamic discrete choices and derive its convergence rate.
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 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 Random Regret-based Discrete Choice Modeling by : Caspar G. Chorus
Download or read book Random Regret-based Discrete Choice Modeling written by Caspar G. Chorus and published by Springer Science & Business Media. This book was released on 2012-04-07 with total page 60 pages. Available in PDF, EPUB and Kindle. Book excerpt: This tutorial presents a hands-on introduction to a new discrete choice modeling approach based on the behavioral notion of regret-minimization. This so-called Random Regret Minimization-approach (RRM) forms a counterpart of the Random Utility Maximization-approach (RUM) to discrete choice modeling, which has for decades dominated the field of choice modeling and adjacent fields such as transportation, marketing and environmental economics. Being as parsimonious as conventional RUM-models and compatible with popular software packages, the RRM-approach provides an alternative and appealing account of choice behavior. Rather than providing highly technical discussions as usually encountered in scholarly journals, this tutorial aims to allow readers to explore the RRM-approach and its potential and limitations hands-on and based on a detailed discussion of examples. This tutorial is written for students, scholars and practitioners who have a basic background in choice modeling in general and RUM-modeling in particular. It has been taken care of that all concepts and results should be clear to readers that do not have an advanced knowledge of econometrics.
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 Another Look at the Identification of Dynamic Discrete Decision Processes by : Victor Aguirregabiria
Download or read book Another Look at the Identification of Dynamic Discrete Decision Processes written by Victor Aguirregabiria and published by . This book was released on 2005 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper presents an econometric approach to estimate the behavioral effects of counterfactual policy experiments in the context of dynamic decision models where the current utility function and the distribution of unobservables are nonparametrically specified. Previous studies have shown that the identification of the current utility function in dynamic decision models requires of stronger assumptions than in static decision models. We show in this paper that knowledge of the current utility function (or of a normalized utility function) is not necessary to identify counterfactual choice probabilities in dynamic models. To identify these counterfactuals we need the probability distribution of the unobservables and the difference between the present value of choosing always the same alternative and the present value of deviating one period from this strategy. We show that both functions are identified from the factual choice probabilities under similar conditions as in static decision models. Based on this result we propose a nonparametric procedure to estimate the behavioral effects of counterfactual experiments in dynamic decision models. We apply this method to evaluate the effects of an investment subsidy program in the context of a model of machine replacement.
Book Synopsis Interpreting Discrete Choice Models by : Garrett Glasgow
Download or read book Interpreting Discrete Choice Models written by Garrett Glasgow and published by Cambridge University Press. This book was released on 2022-05-12 with total page 131 pages. Available in PDF, EPUB and Kindle. Book excerpt: In discrete choice models the relationships between the independent variables and the choice probabilities are nonlinear, depending on both the value of the particular independent variable being interpreted and the values of the other independent variables. Thus, interpreting the magnitude of the effects (the “substantive effects”) of the independent variables on choice behavior requires the use of additional interpretative techniques. Three common techniques for interpretation are described here: first differences, marginal effects and elasticities, and odds ratios. Concepts related to these techniques are also discussed, as well as methods to account for estimation uncertainty. Interpretation of binary logits, ordered logits, multinomial and conditional logits, and mixed discrete choice models such as mixed multinomial logits and random effects logits for panel data are covered in detail. The techniques discussed here are general, and can be applied to other models with discrete dependent variables which are not specifically described here.
Book Synopsis Modeling Ordered Choices by : William H. Greene
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.
Book Synopsis Spmv Approaches to Dynamic Discrete Choice Models with Limited Transition by : Yu Wang
Download or read book Spmv Approaches to Dynamic Discrete Choice Models with Limited Transition written by Yu Wang and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Dynamic optimization problems often involve continuous state variables. Casting such problems into dynamic discrete choice models usually requires variable discretization. When there are multiple state variables, many discretized future states will be visited with only very small probability conditional on current states. We investigate pruning these small transition probabilities and applying the sparse matrix-vector multiplication method in value function iterations. We assess our method in a numerical example inspired by Rust (1987) and Barwick and Pathak (2015). Our method substantially improves computational performance and reduces memory requirements with little loss in accuracy.
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 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:
