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Linear Iv Regression Estimators For Structural Dynamic Discrete Choice Models
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Book Synopsis Linear IV Regression Estimators for Structural Dynamic Discrete Choice Models by : Myrto Kalouptsidi
Download or read book Linear IV Regression Estimators for Structural Dynamic Discrete Choice Models written by Myrto Kalouptsidi and published by . This book was released on 2018 with total page 45 pages. Available in PDF, EPUB and Kindle. Book excerpt: In structural dynamic discrete choice models, the presence of serially correlated unobserved states and state variables that are measured with error may lead to biased parameter estimates and misleading inference. In this paper, we show that instrumental variables can address these issues, as long as measurement problems involve state variables that evolve exogenously from the perspective of individual agents (i.e., market-level states). We define a class of linear instrumental variables estimators that rely on Euler equations expressed in terms of conditional choice probabilities (ECCP estimators). These estimators do not require observing or modeling the agent’s entire information set, nor solving or simulating a dynamic program. As such, they are simple to implement and computationally light. We provide constructive identification arguments to identify the model primitives, and establish the consistency and asymptotic normality of the estimator. A Monte Carlo study demonstrates the good finite-sample performance of the ECCP estimator in the context of a dynamic demand model for durable goods.
Book Synopsis Linear IV Regression Estimators for Structural Dynamic Discrete Choice Models by : Myrto Kalouptsidi
Download or read book Linear IV Regression Estimators for Structural Dynamic Discrete Choice Models written by Myrto Kalouptsidi and published by . This book was released on 2020 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Instrumental Variable Estimation of Dynamic Linear Panel Data Models with Defactored Regressors and a Multifactor Error Structure by : Milda Norkute
Download or read book Instrumental Variable Estimation of Dynamic Linear Panel Data Models with Defactored Regressors and a Multifactor Error Structure written by Milda Norkute and published by . This book was released on 2019 with total page 98 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper develops two instrumental variable (IV) estimators for dynamic panel data models with exogenous covariates and a multifactor error structure when both crosssectional and time series dimensions, N and T respectively, are large. Our approach initially projects out the common factors from the exogenous covariates of the model, and constructs instruments based on this defactored covariates. For models with homogeneous slope coe_cients, we propose a two-step IV estimator: the _rst step IV estimator is obtained using the defactored covariates as instruments. In the second step, the entire model is defactored by the extracted factors from the residuals of the _rst step estimation and subsequently obtain the _nal IV estimator. For models with heterogeneous slope coe _cients, we propose a mean-group type estimator, which is the cross-sectional average of _rst-step IV estimators of cross-section speci_c slopes. It is noteworthy that our estimators do not require us to seek for instrumental variables outside the model. Furthermore, our estimators are linear hence computationally robust and inexpensive. Moreover, they require no bias correction, and they are not subject to the small sample bias of least squares type estimators. The _nite sample performances of the proposed estimators and associated statistical tests are investigated, and the results show that the estimators and the tests perform well even for small N and T.
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 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 784 pages. Available in PDF, EPUB and Kindle. Book excerpt: Handbook of Industrial Organization Volume 4 highlights new advances in the field, with this new volume presenting interesting chapters. Each chapter is written by an international board of authors. Part of the renowned Handbooks in Economics series Chapters are contributed by some of the leading experts in their fields A source, reference and teaching supplement for industrial organizations or industrial economists
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 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 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 The Relative Efficiency of Instrumental Variables Estimators for the Linear Simultaneous Equations Model by : James McConnell Brundy
Download or read book The Relative Efficiency of Instrumental Variables Estimators for the Linear Simultaneous Equations Model written by James McConnell Brundy and published by . This book was released on 1974 with total page 298 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Dynamic Linear Models with R by : Giovanni Petris
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.
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 A Comparison of Alternative Instrumental Variables Estimators of a Dynamic Linear Model by : Kenneth David West
Download or read book A Comparison of Alternative Instrumental Variables Estimators of a Dynamic Linear Model written by Kenneth David West and published by . This book was released on 1995 with total page 76 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Health, Economic Resources and the Work Decisions of Older Men by : John Bound
Download or read book Health, Economic Resources and the Work Decisions of Older Men written by John Bound and published by . This book was released on 2007 with total page 78 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this paper, we specify a dynamic programming model that addresses the interplay among health, financial resources, and the labor market behavior of men in the later part of their working lives. Unlike previous work which has typically used self reported health of disability status as a proxy for health status, we model health as a latent variable, using self reported disability status as an indicator of this latent construct. Our model is explicitly designed to account for the possibility that the reporting of disability may be endogenous to the labor market behavior we are studying. The model is estimated using data from the Health and Retirement Study. We compare results based on our model to results based on models that treat health in the typical way, and find large differences in the estimated effect of health on behavior. While estimates based on our model suggest that health has a large impact on behavior, the estimates suggest a substantially smaller role for health than we find when using standard techniques. We use our model to simulate the impact on behavior of raising the normal retirement age, eliminating early retirement altogether and eliminating the Social Security Disability Insurance program.
Book Synopsis An Efficient Decomposition of the Expectation of the Maximum with Normally Distributed Errors by : Jonathan Eggleston
Download or read book An Efficient Decomposition of the Expectation of the Maximum with Normally Distributed Errors written by Jonathan Eggleston and published by . This book was released on 2016 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: In structural dynamic discrete choice models, one way to allow correlation across errors associated with different choices is to use the multivariate normal distribution. Unfortunately, the expectation of the maximum with normally distributed errors is relatively difficult to evaluate. In this paper, however, I show that this expectation can be decomposed as a linear combination of multivariate normal CDFs. With simulated data, I show that an estimation algorithm based on this decomposition can estimate a model both more quickly and more accurately than an algorithm based on Monte Carlo integration.
Book Synopsis Microeconometrics by : A. Colin Cameron
Download or read book Microeconometrics written by A. Colin Cameron and published by Cambridge University Press. This book was released on 2005-05-09 with total page 1058 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides the most comprehensive treatment to date of microeconometrics, the analysis of individual-level data on the economic behavior of individuals or firms using regression methods for cross section and panel data. The book is oriented to the practitioner. A basic understanding of the linear regression model with matrix algebra is assumed. The text can be used for a microeconometrics course, typically a second-year economics PhD course; for data-oriented applied microeconometrics field courses; and as a reference work for graduate students and applied researchers who wish to fill in gaps in their toolkit. Distinguishing features of the book include emphasis on nonlinear models and robust inference, simulation-based estimation, and problems of complex survey data. The book makes frequent use of numerical examples based on generated data to illustrate the key models and methods. More substantially, it systematically integrates into the text empirical illustrations based on seven large and exceptionally rich data sets.
Book Synopsis Structural Estimation of Real Options Models by : Andrea Gamba
Download or read book Structural Estimation of Real Options Models written by Andrea Gamba and published by . This book was released on 2019 with total page 42 pages. Available in PDF, EPUB and Kindle. Book excerpt: We propose a numerical approach for structural estimation of a class of Discrete (Markov) Decision Processes emerging in real options applications. The approach is specifically designed to account for two typical features of aggregate data sets in real options: the endogeneity of firms' decisions; the unobserved heterogeneity of firms. The approach extends the Nested Fixed Point algorithm by Rust (1987,1988) because both the nested optimization algorithm and the integration over the distribution of the unobserved heterogeneity are accommodated using a simulation method based on a polynomial approximation of the value function and on recursive least squares estimation of the coefficients. The Monte Carlo study shows that omitting unobserved heterogeneity produces a significant estimation bias because the model can be highly non-linear with respect to the parameters.
Book Synopsis Optimal Adaptive Estimation: Structure and Parameter Adaptation. Part I. Linear Models by : D. G. Lainiotis
Download or read book Optimal Adaptive Estimation: Structure and Parameter Adaptation. Part I. Linear Models written by D. G. Lainiotis and published by . This book was released on 1969 with total page 36 pages. Available in PDF, EPUB and Kindle. Book excerpt: A Bayesian approach to optimal adatpive estimation with continuous as well as discrete data is presented. Both structure and parameter adaptation are considered and specific recursive adaptation algorithms are derived for gaussian process models and linear dynamics. Specifically, for the class of adaptive estimation problems with linear dynamic models and gaussian excitations, a form of the 'partition' theorem is given that is applicable both for structure and parameter adaptation. The 'partition' or 'decomposition' theorem effects the partition of the essentially nonlinear estimation problem into two parts, a linear non-adaptive part consisting of ordinary Kalman estimators and a nonlinear part that incorporates the adaptive or learning nature of the adaptive estimator. In addition, simple performance measures are introduced for the on-line performance evaluation of the adaptive estimator. The on-line performance measure utilize quantities available from the adaptive estimator and hence a minimum of additional computational effort is required for evaluation. Adaptive estimators are given for filtering, prediction, as well as smoothing. (Author).
