Essays In Semiparametric And Nonparametric Microeconometrics

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Essays In Semiparametric And Nonparametric Microeconometrics

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Author : Matias Damian Cattaneo
language : en
Publisher:
Release Date : 2008

Essays In Semiparametric And Nonparametric Microeconometrics written by Matias Damian Cattaneo and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008 with categories.

Essays On Semiparametric And Nonparametric Methods In Econometrics

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Author : Sokbae Lee
language : en
Publisher:
Release Date : 2002

Essays On Semiparametric And Nonparametric Methods In Econometrics written by Sokbae Lee and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002 with Econometrics categories.

Nonparametric And Semiparametric Methods In Econometrics And Statistics

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Author : William A. Barnett
language : en
Publisher: Cambridge University Press
Release Date : 1991-06-28

Nonparametric And Semiparametric Methods In Econometrics And Statistics written by William A. Barnett and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1991-06-28 with Business & Economics categories.

Papers from a 1988 symposium on the estimation and testing of models that impose relatively weak restrictions on the stochastic behaviour of data.

Semiparametric And Nonparametric Econometrics

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Author : Aman Ullah
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06

Semiparametric And Nonparametric Econometrics written by Aman Ullah and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Business & Economics categories.

Over the last three decades much research in empirical and theoretical economics has been carried on under various assumptions. For example a parametric functional form of the regression model, the heteroskedasticity, and the autocorrelation is always as sumed, usually linear. Also, the errors are assumed to follow certain parametric distri butions, often normal. A disadvantage of parametric econometrics based on these assumptions is that it may not be robust to the slight data inconsistency with the particular parametric specification. Indeed any misspecification in the functional form may lead to erroneous conclusions. In view of these problems, recently there has been significant interest in 'the semiparametric/nonparametric approaches to econometrics. The semiparametric approach considers econometric models where one component has a parametric and the other, which is unknown, a nonparametric specification (Manski 1984 and Horowitz and Neumann 1987, among others). The purely non parametric approach, on the other hand, does not specify any component of the model a priori. The main ingredient of this approach is the data based estimation of the unknown joint density due to Rosenblatt (1956). Since then, especially in the last decade, a vast amount of literature has appeared on nonparametric estimation in statistics journals. However, this literature is mostly highly technical and this may partly be the reason why very little is known about it in econometrics, although see Bierens (1987) and Ullah (1988).

Essays In Applied Microeconometrics

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Author : Axel Werwatz
language : en
Publisher:
Release Date : 2003*

Essays In Applied Microeconometrics written by Axel Werwatz and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003* with categories.

Essays On Semi Non Parametric Methods In Econometrics

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Author : Sungwon Lee
language : en
Publisher:
Release Date : 2018

Essays On Semi Non Parametric Methods In Econometrics written by Sungwon Lee and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with categories.

My dissertation contains three chapters focusing on semi-/non-parametric models in econometrics. The first chapter, which is a joint work with Sukjin Han, considers parametric/semiparametric estimation and inference in a class of bivariate threshold crossing models with dummy endogenous variables. We investigate the consequences of common practices employed by empirical researchers using this class of models, such as the specification of the joint distribution of the unobservables to be a bivariate normal distribution, resulting in a bivariate probit model. To address the problem of misspecification, we propose a semiparametric estimation framework with parametric copula and nonparametric marginal distributions. This specification is an attempt to ensure robustness while achieving point identification and efficient estimation. We establish asymptotic theory for the sieve maximum likelihood estimators that can be used to conduct inference on the individual structural parameters and the average treatment effects. Numerical studies suggest the sensitivity of parametric specification and the robustness of semiparametric estimation. This paper also shows that the absence of excluded instruments may result in the failure of identification, unlike what some practitioners believe. The second chapter develops nonparametric significance tests for quantile regression models with duration outcomes. It is common for empirical studies to specify models with many covariates to eliminate the omitted variable bias, even if some of them are potentially irrelevant. In the case where models are nonparametrically specified, such a practice results in the curse of dimensionality. I adopt the integrated conditional moment (ICM) approach, which was developed by Bierens (1982) and Bierens (1990) to construct test statistics. The proposed test statistics are functionals of a stochastic process which converges weakly to a centered Gaussian process. The test has non-trivial power against local alternatives at the parametric rate. A subsampling procedure is proposed to obtain critical values. The third chapter considers identification of treatment effect and its distribution under some distributional assumptions. I assume that a binary treatment is endogenously determined. The main identification objects are the quantile treatment effect and the distribution of the treatment effect. I construct a counterfactual model and apply Manski's approach (Manski (1990)) to find the quantile treatment effects. For the distribution of the treatment effect, I adapt the approach proposed by Fan and Park (2010). Some distributional assumptions called stochastic dominance are imposed on the model to tighten the bounds on the parameters of interest. It also provides confidence regions for identified sets that are pointwise consistent in level. An empirical study on the return to college confirms that the stochastic dominance assumptions improve the bounds on the distribution of the treatment effect.

Essays On Nonparametric Econometrics With Applications To Consumer And Financial Economics

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Author : Yi Zheng
language : en
Publisher:
Release Date : 2008

Essays On Nonparametric Econometrics With Applications To Consumer And Financial Economics written by Yi Zheng and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008 with Credit categories.

Abstract: This dissertation is composed of three chapters centering on nonparametric econometrics with applications to consumer demand system analysis, value-at-risk analysis of commodity future prices, and credit risk analysis of home mortgage portfolios. The first chapter, based on my joint research with Abdoul Sam considers a semiparametric estimation model for a censored consumer demand system with micro data. A common attribute of disaggregated household data is the censoring of commodities. Maximum likelihood and existing two-step estimators of censored demand systems yield biased and inconsistent estimates when the assumed joint distribution of the disturbances is incorrect. This essay proposes a semiparametric estimator that retains the computational advantage of the two-step methods while circumventing their potential distributional misspecification. The key difference between the proposed estimator and existing two-step counterparts is that the parameters of the binary censoring equations are estimated using a distribution-free single-index model. We implement the proposed estimator using household-level data obtained from the Hainan province in China. Horrowitz and Härdle (1994)'s specification test lends support to our approach. The second chapter is an empirical application of a nonparametric estimator of Value-at-Risk on the cattle feeding margin. Value-at-Risk, known as VaR is a common measure of downside market risk associated with an asset or a portfolio of assets. It has been used as a standard tool of predicting potential portfolio losses for twenty years in the financial industry. Recently VaR has gained popularity in agricultural economics literature since the market price risks associated with agricultural commodities are under evaluation. As initial empirical findings suggest that the performance of any VaR estimation technique is sensitive to the types of data set (portfolio composition) used in developing and evaluating the estimates, agricultural data provides a unique laboratory to further explore VaR and its estimation approaches. This essay as a first attempt applies a distribution-free nonparametric kernel estimator of VaR in an agricultural context, the cattle feeding margin using futures data. The empirical results suggest that the nonparametric VaR estimates enjoy a significant efficiency gain without losing much accuracy compared to the parametric estimates. The third chapter measures credit risks associated with residential mortgage loans. Credit risk is the primary source of risk for real estate lenders. Recent advancements in the measurement and management of credit risk give lenders with sophisticated internal risk models a significant comparative advantage over other lenders in terms of capital optimization and risk controlling. This manuscript helps understand the determinants of credit risk and acquire perspectives on how it is distributed in the current or future loan portfolios. This essay contributes to the existing volume of literature as it incorporates the nonparametric estimation technique into default risk analysis. The CreditRisk model is modified and estimated using the consumer side of information. The model identifies the factors determining household default risks and generates a full loan loss distribution at the portfolio level using consumer finance survey data. In the end, portfolio management strategies are discussed.

Essays On Nonparametric And Semiparametric Econometric Models

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Author : Kirill Evdokimov
language : en
Publisher:
Release Date : 2010

Essays On Nonparametric And Semiparametric Econometric Models written by Kirill Evdokimov and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010 with categories.

The Oxford Handbook Of Applied Nonparametric And Semiparametric Econometrics And Statistics

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Author : Jeffrey Racine
language : en
Publisher: Oxford University Press
Release Date : 2013-12-31

The Oxford Handbook Of Applied Nonparametric And Semiparametric Econometrics And Statistics written by Jeffrey Racine and has been published by Oxford University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-12-31 with Business & Economics categories.

This volume, edited by Jeffrey Racine, Liangjun Su, and Aman Ullah, contains the latest research on nonparametric and semiparametric econometrics and statistics. These data-driven models seek to replace the classical parametric models of the past, which were rigid and often linear. Chapters by leading international econometricians and statisticians highlight the interface between econometrics and statistical methods for nonparametric and semiparametric procedures. They provide a balanced view of new developments in the modeling of cross-section, time series, panel, and spatial data. Topics of the volume include: the methodology of semiparametric models and special regressor methods; inverse, ill-posed, and well-posed problems; methodologies related to additive models; sieve regression, nonparametric and semiparametric regression, and the true error of competing approximate models; support vector machines and their modeling of default probability; series estimation of stochastic processes and their application in Econometrics; identification, estimation, and specification problems in semilinear time series models; nonparametric and semiparametric techniques applied to nonstationary or near nonstationary variables; the estimation of a set of regression equations; and a new approach to the analysis of nonparametric models with exogenous treatment assignment.

Micro Econometrics

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Author : Myoung-jae Lee
language : en
Publisher: Springer Science & Business Media
Release Date : 2009-09-28

Micro Econometrics written by Myoung-jae Lee and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-09-28 with Business & Economics categories.

Up-to-date coverage of most micro-econometric topics; first half parametric, second half semi- (non-) parametric Many empirical examples and tips in applying econometric theories to data Essential ideas and steps shown for most estimators and tests; well-suited for both applied and theoretical readers