Download or read book Essays on Estimation of Discrete Choice Models with Endogeneity written by Nese Yildiz and published by . This book was released on 2005 with total page 298 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Essays on Semiparametric Estimation of Multinomial Discrete Choice Models written by and published by . This book was released on 2013 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the first chapter I propose a semiparametric estimator that allows for a flexible form of heteroskedasticity for multinomial discrete choice (MDC) models. Despite being semiparametric, the rate of convergence of the smoothed maximum score (SMS) estimator is not affected by the number of alternative choices. I show the strong consistency and asymptotic normality of the proposed estimator. The rate of convergence of the SMS estimator for MDC models can be made arbitrarily close to the inverse of the square root of the sample size, which is the same as the rate of convergence of Horowitz's (1992) SMS estimator for the binary response model. Monte Carlo experiments provide evidence that the proposed estimator has a smaller mean squared error than both the conditional logit estimator and the maximum score estimator when heteroskedasticity exists. I apply the SMS estimator to study the college decisions of high school graduates using a subset of Chilean data from 2011. The estimation results of the SMS estimator differ significantly from the results of the conditional logit estimator, which suggests possible misspecification of parametric models and the usefulness of considering the SMS estimator as an alternative for estimating MDC models. Many MDC applications include potentially endogenous regressors. To allow for endogeneity, in the second chapter I propose a two-stage instrumental variables estimator where the endogenous variable is replaced by a linear estimate, and then the preference parameters in the MDC equation are estimated by the SMS estimator described in the first chapter. In neither stage do I specify the distribution of the error terms, so this two-stage estimation method is semiparametric. This estimator is a generalization of the estimator proposed by Fox (2007). Fox suggests applying the maximum score estimator in the second stage of estimation. This chapter is the first to derive the statistical properties of an estimator allowing for endogeneity in this semiparametric setting. The two-stage instrument variables estimator is consistent when the linear function of instrument variables and other covariates can rank order the choice probabilities. The second chapter also provides results of some Monte Carlo experiments.
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:
Download or read book Essays on Discrete Choice Models written by Joonmo Kang and published by . This book was released on 2016 with total page 112 pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation consists of three essays divided into chapters. In chapter 1, I analyze the identification of a simultaneous binary response model without nonadditive unobservable random terms, and suggest an estimation method. In particular, the derivatives of structural equations are identified and estimated. The identification relies on a special regressor, which enters the underlying structural equation linearly. All other exogenous variables held constant, variation on this special regressor generates variation on the structural equation which determines the latent endogenous variable in a known way, so we can recover the conditional distribution of the structural equations. The estimator can be constructed using a least-squares method, after replacing the elements of a matrix with kernel density and density derivative estimates. The estimator is shown to be consistent and asymptotically normal. In chapter 2, I examine the determinants smartphone adoption among the elderly in South Korea. The advent of smartphones has caused a dramatic change in access to information and media, leading to a super-connected world of real-time services. Meanwhile, the constant dissemination of new technologies makes the digital divide multi-layered. In particular, older persons fall far behind the overall population in the access and use of new devices. To understand the technological environment following the introduction of smartphones and other smart mobile devices, I examine individual, household, and regional factors that can influence the preferences of the elderly with regard to obtaining a smartphone. I find that smartphone ownership among the elderly is mainly determined by personal rather than family characteristics. Also, I find that the area where a person lives has a significant effect on the probability of their owning a smartphone. In chapter 3, I analyze the evolution of preferences for brands in digital camera market. A consumer considers the value of a brand, as well as product characteristics when deciding which product to buy. One way to capture this effect is to use brand-specific dummy variables. However, including brand-specific dummy variables does not fully account for the variation of the unit sales of compact digital cameras, since the preference for digital camera brands evolves over time. Assuming that the brand preference is affected by the advertising expenditure of each brand and the reputation among consumers, I suggest a method to capture the time-varying brand preference under the specification of BLP model.
Download or read book Essays on Discrete Choice Models written by Wei Song and published by . This book was released on 2017 with total page 162 pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation focuses on the identification and estimation of discrete choice models. In practice, if the error term is independent of the covariates and follows some known distribu- tion, the discrete choice model is usually estimated using some parametric estimator, such as Probit and Logit. However, when the distribution of the error is unknown, misspecification would in general cause the estimators inconsistent even if the independence between the covariates and the error still holds. The two chapters relax the assumptions on the error distribution in the discrete choice models and propose semiparametric estimators.
Download or read book Handbook of Choice Modelling written by Stephane Hess and published by Edward Elgar Publishing. This book was released on 2014-08-29 with total page 721 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Handbook of Choice Modelling, composed of contributions from senior figures in the field, summarizes the essential analytical techniques and discusses the key current research issues. The book opens with Nobel Laureate Daniel McFadden calling for d
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 280 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.
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.
Download or read book Essays in Discrete Choice Demand Estimation written by Konstantinos Hatzitaskos and published by . This book was released on 2007 with total page 234 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Essays in Econometrics written by Kirill Ponomarev and published by . This book was released on 2022 with total page 162 pages. Available in PDF, EPUB and Kindle. Book excerpt: The chapters of this dissertation are devoted to three different topics. The first chapter studies estimation of parameters expressed via non-differentiable functions. Such parameters are abundant in econometric models and typically take the form of maxima or minima of some estimable objects. Examples include bounds on the average treatment effects in non-experimental settings, identified sets for the coefficients in regression models with interval-valued data, bounds on the distribution of wages accounting for selection into employment, and many others. I consider estimators of the form $\phi(\hat{\theta}_n + \hat{v}_{1, n}) + \hat{v}_{2, n}$, where $\hat{\theta}_n$ is the efficient estimator for $\theta_0$, and $\hat{v}_{1, n}, \hat{v}_{2, n}$ are suitable adjustment terms. I characterize the optimal adjustment terms and develop a general procedure to compute them from the data. A simulation study shows that the proposed estimator can have lower finite-sample bias and variance than the existing alternatives. As an application, I consider estimating the bounds on the distribution of valuations and the optimal reserve price in English auctions with independent private values. Empirically calibrated simulations show that the resulting estimates are substantially sharper than the previously available ones. The second chapter studies inequality selection in partially identified models. Many partially identified models have the following structure: given a parameter vector and covariates, the model produces a set of predictions while the researcher observes a single outcome. Examples include entry games with multiple equilibria, network formation models, discrete-choice models with endogenous explanatory variables or heterogeneous choice sets, and auctions. Sharp identified sets for structural parameters in such models can be characterized via a special kind of moment inequalities. For a given parameter value, the inequalities verify that the observed conditional distribution of the outcome given covariates belongs to the set of distributions admitted by the model. In practice, checking all of the inequalities is often computationally infeasible, and many of them may not even be informative. Therefore, some inequality selection is required. In this chapter, I propose a new analytical criterion that dramatically reduces the number of inequalities required to characterize the sharp identified set. In settings where the outcome space is finite, I characterize the smallest subset of inequalities that guarantees sharpness and show that it can be efficiently computed using graph propagation techniques. I apply the proposed criterion in the context of market entry games, network formation, auctions, and discrete-choice. The third chapter (coauthored with Liqiang Shi) is about model selection for policy learning. When treatment effects are heterogeneous, a decision-maker that has access to (quasi- )experimental data can attempt to find the optimal policy function, mapping observable characteristics into treatment choices, to maximize utilitarian welfare. When several different policy classes are available, the choice of the policy class poses a model selection problem. In this chapter, following Athey and Wager (2021) and Mbakop and Tabord-Meehan (2021), we propose a policy learning algorithm that leverages doubly-robust estimation and incorporates data-driven model selection. We show that the proposed algorithm automatically selects the best available class of policies and achieves the optimal $n^{-1/2}$ rate of convergence in terms of expected regret. We also refine some of the existing related results and derive a new finite-sample lower bound on expected regret.
Download or read book Essays in Honor of Joon Y Park written by Yoosoon Chang and published by Emerald Group Publishing. This book was released on 2023-04-24 with total page 449 pages. Available in PDF, EPUB and Kindle. Book excerpt: Volumes 45a and 45b of Advances in Econometrics honor Professor Joon Y. Park, who has made numerous and substantive contributions to the field of econometrics over a career spanning four decades since the 1980s and counting.
Download or read book Discrete Choice Models with Endogeneity written by Haiqing Xu and published by . This book was released on 2011 with total page 121 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Essays on Discrete Multivalued Treatments with Endogeneity and Heterogeneous Counterfactual Errors written by Ibrahim Kekec and published by . This book was released on 2021 with total page 244 pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation is composed of three chapters, and each one of them studies discrete multivalued treatments with endogeneity and heterogeneous counterfactual errors. The first chapter extends the investigations of average treatment effects (ATEs) in extensively-studied binary treatments to those in discrete multivalued treatments with both endogeneity and heterogeneous counterfactual errors and explores the behavior of control function (CF) and instrumental variables (IV) methods in this framework. Specifically, I offer identification strategies for the ATEs, suggest a consistent estimator for the ATEs, show the asymptotic properties of CF parameter estimates, and derive a score test in order to draw inferences about the ATEs and other parameters of interest. Moreover, using a Monte Carlo simulation analysis, I compare CF method with widely used IV method in terms of asymptotic efficiency, asymptotic unbiasedness, and consistency. Simulation results suggest that CF method can be asymptotically up to 12% more efficient than IV method, and asymptotic bias in parameter estimates of IV method can be as high as 43%. However, when misspecification is introduced, simulation results favor IV method. For the empirical illustration, I apply ordinary least squares (OLS), CF, IV, and nonparametric bound analysis to the estimation of how limited English proficiency (LEP) influences wages of Hispanic workers in the USA. The data come from the 1% Public Use Microdata Series of the 1990 US Census. Utilizing age at arrival as an instrumental variable, both OLS and CF methods indicate that LEP on average imposes a statistically significant wage penalty (up to 79% in some CF estimates)on Hispanic community in the USA. IV method mostly produces insignificant results, and nonparametric bound analysis provides uninformative lower bounds.The second chapter incorporates a structure of correlated random coefficients (CRCs)into the framework introduced in the first chapter. However, in this new setting with CRCs, conventional IV method is suspected to be inconsistent for ATEs. In this chapter, I propose a consistent CF estimation procedure for the ATEs and show the asymptotic properties of CF parameter estimates. In addition, my Monte Carlo simulation analysis suggests that, in the absence of misspecification, CF method is asymptotically unbiased and consistent (but not necessarily more efficient). Whereas, IV method is generally asymptotically biased and inconsistent. In the presence of misspecification, the simulation results show that both CF and IV methods have biased estimates (more on CF estimates). With regard to efficiency, the simulation findings show that none of the methods outperforms the other one clearly.In the third chapter, I take the treatment model from the first chapter to a specific linear high dimensional sparse setting where the high dimensional variables are irrelevant in treatment choice given the instruments and appear only in the outcome equation. Using a detailed simulation analysis, I examine the finite sample properties, model selection features, and prediction capabilities of several machine learning (ML) methods and of the CF method from the first chapter. To estimate the parameters of interest, I use four different ML methods: LASSO; post partial-out LASSO of Belloni et al. (2012); post double selection LASSO of Belloni, Chernozhukov, and Hansen (2014a); and double/debiased ML LASSO of Chernozhukov et al. (2018). The most important simulation result is that, in the presence of enough extra predictive variables that are ignorable in treatment selection and are from a set of high dimensional predictors of outcome, more complicated LASSO-based methods result inefficiency gains in ATE estimates over the simpler CF method although both LASSO-based methods and the CF method perform more or less the same as far as finite sample bias is concerned. As far as model selection goes, the simulations show that the double/debiased MLLASSO both selects the most number of potential variables and correctly selects the most number of variables with true nonzero impact on outcome in estimation. As to prediction, the simulation results suggest that LASSO has the best prediction features.
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:
Download or read book Essays in Honor of Cheng Hsiao written by Dek Terrell and published by Emerald Group Publishing. This book was released on 2020-04-15 with total page 418 pages. Available in PDF, EPUB and Kindle. Book excerpt: Including contributions spanning a variety of theoretical and applied topics in econometrics, this volume of Advances in Econometrics is published in honour of Cheng Hsiao.
Download or read book Essays on Dynamic Discrete Choice Models written by Eliza Da Silva Gomes and published by . This book was released on 2021 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Assessment and Correction of Endogeneity Problems in Discrete Choice Models written by Thomas Edison Guerrero Barbosa and published by . This book was released on 2021 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
