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A Comment On Estimating Dynamic Discrete Choice Models With Hyperbolic Discounting By Hanming Fang And Yang Wang
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Book Synopsis A Comment on “Estimating Dynamic Discrete Choice Models with Hyperbolic Discounting” by Hanming Fang and Yang Wang by : Jaap H. Abbring
Download or read book A Comment on “Estimating Dynamic Discrete Choice Models with Hyperbolic Discounting” by Hanming Fang and Yang Wang written by Jaap H. Abbring and published by . This book was released on 2020 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Fang and Wang's (2015) Proposition 2 claims generic identification of a dynamic discrete choice model with hyperbolic discounting under exclusion restrictions. We note that Proposition 2 uses a definition of “generic” that does not preclude that a generically identified model is nowhere identified. We provide two examples of models that are generically identified under this definition, but that are, respectively, everywhere and nowhere identified. We then show that the proof of Proposition 2 is incorrect and incomplete. We conclude that Proposition 2 has no implications for identification of the dynamic discrete choice model and suggest alternative approaches to its identification.
Book Synopsis Estimating Dynamic Discrete Choice Models with Hyperbolic Discounting, with an Application to Mammography Decisions by : Hanming Fang
Download or read book Estimating Dynamic Discrete Choice Models with Hyperbolic Discounting, with an Application to Mammography Decisions written by Hanming Fang and published by . This book was released on 2015 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: We extend the semiparametric estimation method for dynamic discrete choice models using Hotz and Miller's (Review of Economic Studies 60 (1993), 497-529) conditional choice probability approach to the setting where individuals may have hyperbolic discounting time preferences and may be naive about their time inconsistency. We illustrate the proposed identification and estimation method with an empirical application of adult women's decisions to undertake mammography to evaluate the importance of present bias and naivety in the underutilization of this preventive health care. Our results show evidence for both present bias and naivety.
Book Synopsis Identification of Dynamic Discrete Choice Models with Hyperbolic Discounting Using a Terminating Action by : Chao Wang
Download or read book Identification of Dynamic Discrete Choice Models with Hyperbolic Discounting Using a Terminating Action written by Chao Wang and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Handbook of Industrial Organization by :
Download or read book Handbook of Industrial Organization written by and published by Elsevier. This book was released on 2021-12-09 with total page 788 pages. Available in PDF, EPUB and Kindle. Book excerpt: Handbook of Industrial Organization, Volume Four highlights new advances in the field, with this new volume presenting interesting chapters written by an international board of expert authors. Presents authoritative surveys and reviews of advances in theory and econometrics Reviews recent research on capital raising methods and institutions Includes discussions on developing countries
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 Dynamic Programming Approaches for Estimating and Applying Large-scale Discrete Choice Models by : Anh Tien Mai
Download or read book Dynamic Programming Approaches for Estimating and Applying Large-scale Discrete Choice Models written by Anh Tien Mai and published by . This book was released on 2015 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: People go through their life making all kinds of decisions, and some of these decisions affect their demand for transportation, for example, their choices of where to live and where to work, how and when to travel and which route to take. Transport related choices are typically time dependent and characterized by large number of alternatives that can be spatially correlated. This thesis deals with models that can be used to analyze and predict discrete choices in large-scale networks. The proposed models and methods are highly relevant for, but not limited to, transport applications. We model decisions as sequences of choices within the dynamic discrete choice framework, also known as parametric Markov decision processes. Such models are known to be difficult to estimate and to apply to make predictions because dynamic programming problems need to be solved in order to compute choice probabilities. In this thesis we show that it is possible to explore the network structure and the flexibility of dynamic programming so that the dynamic discrete choice modeling approach is not only useful to model time dependent choices, but also makes it easier to model large-scale static choices. The thesis consists of seven articles containing a number of models and methods for estimating, applying and testing large-scale discrete choice models. In the following we group the contributions under three themes: route choice modeling, large-scale multivariate extreme value (MEV) model estimation and nonlinear optimization algorithms. Five articles are related to route choice modeling. We propose different dynamic discrete choice models that allow paths to be correlated based on the MEV and mixed logit models. The resulting route choice models become expensive to estimate and we deal with this challenge by proposing innovative methods that allow to reduce the estimation cost. For example, we propose a decomposition method that not only opens up for possibility of mixing, but also speeds up the estimation for simple logit models, which has implications also for traffic simulation. Moreover, we compare the utility maximization and regret minimization decision rules, and we propose a misspecification test for logit-based route choice models. The second theme is related to the estimation of static discrete choice models with large choice sets. We establish that a class of MEV models can be reformulated as dynamic discrete choice models on the networks of correlation structures. These dynamic models can then be estimated quickly using dynamic programming techniques and an efficient nonlinear optimization algorithm. Finally, the third theme focuses on structured quasi-Newton techniques for estimating discrete choice models by maximum likelihood. We examine and adapt switching methods that can be easily integrated into usual optimization algorithms (line search and trust region) to accelerate the estimation process. The proposed dynamic discrete choice models and estimation methods can be used in various discrete choice applications. In the area of big data analytics, models that can deal with large choice sets and sequential choices are important. Our research can therefore be of interest in various demand analysis applications (predictive analytics) or can be integrated with optimization models (prescriptive analytics). Furthermore, our studies indicate the potential of dynamic programming techniques in this context, even for static models, which opens up a variety of future research directions.
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 0 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:
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 Identifying the Discount Factor in Dynamic Discrete Choice Models by : Jaap H. Abbring
Download or read book Identifying the Discount Factor in Dynamic Discrete Choice Models written by Jaap H. Abbring and published by . This book was released on 2019 with total page 39 pages. Available in PDF, EPUB and Kindle. Book excerpt: Empirical research often cites observed choice responses to variation that shifts expected discounted future utilities, but not current utilities, as an intuitive source of information on time preferences. We study the identification of dynamic discrete choice models under such economically motivated exclusion restrictions on primitive utilities. We show that each exclusion restriction leads to an easily interpretable moment condition with the discount factor as the only unknown parameter. The identified set of discount factors that solves this condition is finite, but not necessarily a singleton. Consequently, in contrast to common intuition, an exclusion restriction does not in general give point identification. Finally, we show that exclusion restrictions have nontrivial empirical content: The implied moment conditions impose restrictions on choices that are absent from the unconstrained model.
Book Synopsis Estimating Dynamic Discrete-Choice Games of Incomplete Information by : Michael Egesdal
Download or read book Estimating Dynamic Discrete-Choice Games of Incomplete Information written by Michael Egesdal and published by . This book was released on 2014 with total page 33 pages. Available in PDF, EPUB and Kindle. Book excerpt: We investigate the estimation of models of dynamic discrete-choice games of incomplete information, formulating the maximum-likelihood estimation exercise as a constrained optimization problem which can be solved using state-of-the-art constrained optimization solvers. Under the assumption that only one equilibrium is played in the data, our approach avoids repeatedly solving the dynamic game or finding all equilibria for each candidate vector of the structural parameters. We conduct Monte Carlo experiments to investigate the numerical performance and finite-sample properties of the constrained optimization approach for computing the maximum-likelihood estimator, the two-step pseudo maximum-likelihood estimator and the nested pseudo-likelihood estimator, implemented by both the nested pseudo-likelihood algorithm and a modified nested pseudo-likelihood algorithm.
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 A Simulation Estimator for Dynamic Models of Discrete Choice by : V. Joseph Hotz
Download or read book A Simulation Estimator for Dynamic Models of Discrete Choice written by V. Joseph Hotz and published by . This book was released on 1992 with total page 35 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Estimating Dynamic Panel Data Discrete Choice Models with Fixed Effects by : Jesús M. Carro
Download or read book Estimating Dynamic Panel Data Discrete Choice Models with Fixed Effects written by Jesús M. Carro and published by . This book was released on 2003 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Estimating Dynamic Panel Data Discrete Choice Models with Fixed Effects by : Jesús M. Carro
Download or read book Estimating Dynamic Panel Data Discrete Choice Models with Fixed Effects written by Jesús M. Carro and published by . This book was released on 2003 with total page 41 pages. Available in PDF, EPUB and Kindle. Book excerpt:
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 Essays on Dynamic Discrete Choice Models by : Selin Akca
Download or read book Essays on Dynamic Discrete Choice Models written by Selin Akca and published by . This book was released on 2014 with total page 131 pages. Available in PDF, EPUB and Kindle. Book excerpt: