Download or read book Essays on Nonparametric Structural Econometrics written by Zhutong Gu and published by . This book was released on 2017 with total page 172 pages. Available in PDF, EPUB and Kindle. Book excerpt: My dissertation contains three papers in the theory and applications of nonparametric structural econometrics. In chapter 1, I propose a nonparametric test for additive separability of unobservables of unrestricted dimensions with average structural functions. Chapter 2 considers identification and estimation of fully nonparametric production functions and empirically tests for the Hicks-neutral productivity shocks, a direct application of the test proposed in chapter 1. In chapter 3, my authors and I study the semiparametric ordered response models with correlated unobserved thresholds and investigate the issue of corporate bond rating biases due to the sharing of common investors between bond-issuing firms and credit rating agencies. Brief abstracts are presented in order below. Additive separability between observables and unobservables is one of the essential properties in structural modeling of heterogeneity in the presence of endogeneity. In this chapter, I propose an easy-to-compute test based on empirical quantile mean differences between the average structural functions (ASFs) generated by nonparametric nonseparable and separable models with unrestricted heterogeneity. Given identification, I establish conditions under which structural additivity can be linked to the equality of ASFs derived from the two commonly employed competing specifications. I estimate the reduced form regressions by Nadaraya-Watson estimators and control for the asymptotic bias. I show that the asymptotic test statistic follows a central Chi-squred distribution under the null hypothesis and has power against a sequence of root N-local alternatives. The proposed test statistic works well in a series of finite sample simulations with analytic variances, alleviating the computational burden often involved in bootstrapped inferences. I also show that the test can be straightforwardly extended to semiparametric models, panel data and triangular simultaneous equations frameworks. Hicks-neutral technology implies the substitution pattern of labor and capital in a production function is not affected by technological shocks, first put forth by John Hicks in 1932. In this chapter, I consider the identification and estimation of fully nonparametric firm-level production functions and empirically test the Hicks-neutral productivity in the U.S. manufacturing industry during the period from 1990 to 2011. Firstly, I extend the proxy variable approach to fully nonparametric settings and propose a robust estimator of average output elasticities in non-Hick-neutral scenarios. Secondly, I show that the Hicks-neutral restriction can be converted to the additive separability between inputs and unobservables in a monotonic transformed model for which the proposed testing procedure can be directly applied. It turns out that there is substantial heterogeneity in the nonparametric output elasticities over various counterfactual input amounts. I also find that there were periods in the 90s when the non-Hicks technological shocks occur which coincide with the mass adoption of computing technology. However, the productivity has thereafter become Hicks-neutral into the 2000s. Controlling for sector-specific effects mitigate the non-Hicks-neutrality to some extend. Previous literature on bond rating indicates that credit rating agencies (CRAs) may assign favorable ratings to bond-issuing firms that have a closer relationship. This not only implies the existence of firm-specific unobserved heterogeneity in the rating criteria but also makes some bond/firm characteristics endogenous, which is confirmed by our empirical results. In this chapter, my coauthors and I propose a semiparametric two-step index and location estimator of ordered response models that explicitly incorporates endogenous regressors and correlated random thresholds. We apply our model in the application of assessing bond rating bias of credit rating agencies. Methodologically, we first show that the heterogeneous relative thresholds can be identified using conditional shift restrictions in conjunction with the control variables for the firm-CRA liaison. Then, we illustrate the estimation strategy in a heuristic manner and derive the asymptotic properties of the suggested estimator. In the application, we find significant overrating bias through varying thresholds as the liaison strengthens and those biases display heterogeneous patterns with respect to rating categories.

Download or read book Essays on Nonparametric Econometrics written by Young Jun Lee and published by . This book was released on 2019 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation consists of three chapters that focus on the nonparametric method on time-varying parameter models and optimal transport problem. // The first chapter, which is jointly authored with Dennis Kristensen, develops a novel asymptotic theory for local polynomial (quasi-) maximum-likelihood estimators of time-varying parameters in a broad class of nonlinear time series models. Under weak regularity conditions, we show the proposed estimators are consistent and follow normal distributions in large samples. We demonstrate the usefulness of our general results by applying our theory to local (quasi-) maximum-likelihood estimators of a time-varying VAR's, ARCH and GARCH, and Poisson autogressions. // The second chapter proposes a sieve M-estimation of the solution to the optimal transport problem. Many problems in economics, including matching models and quantile methods, have the structure of an optimal transport problem. The sieve M-estimator is consistent under very little structure on the underlying optimal transport problem being solved. I then derive convergence rates for the estimator and its derivative when the surplus function Φ(X, Y) = X"2Y. The derived convergence rates are the same as the optimal rate in the context of regression and density estimations. The results can be extended to the conditional optimal transport problem having the conditional vector quantiles as an application. // In the third chapter, I consider the multidimensional matching as one of the primary applications of the optimal transport problem. We employ the sieve simultaneous minimum distance estimation method to estimate the parameters in the equilibrium wage and assignment functions. Our estimation results show that worker-job complementarities in manual skills strongly decreased, whereas complementarities in cognitive skills increased. This phenomenon is consistent with the one of Lindenlaub (2017).

Download or read book Essays in Nonparametric Econometrics written by Daniel Santiago Morillo and published by . This book was released on 2000 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Essays on Nonparametric Econometrics with Applications to Consumer and Financial Economics written by Yi Zheng and published by . This book was released on 2008 with total page 98 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Essays in Nonparametric Econometrics written by Tomasz Olma 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 Nonparametric and High Dimensional Econometrics written by Jesper Riis-Vestergaard Soerensen and published by . This book was released on 2018 with total page 227 pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation studies questions related to identification, estimation, and specification testing of nonparametric and high-dimensional econometric models. The thesis is composed by two chapters. In Chapter 1, I propose specification tests for two formally distinct but related classes of econometric models: (1) semiparametric conditional moment restriction models dependent on conditional expectation functions, and (2) a class of high-dimensional unconditional moment restriction models dependent on high-dimensional best linear predictors. These classes may be motivated by economic models in which agents make choices under uncertainty and therefore have to predict payoff-relevant variables such as the behavior of other agents. The proposed tests are shown to be both asymptotically correctly sized and consistent. Moreover, I establish a bound on the rate of local alternatives for which the test for high-dimensional unconditional moment restriction models is consistent. These results allow researchers to test the specification of their models without introducing additional parametric, typically ad hoc, assumptions on expectations. In Chapter 2, I show that it is possible to identify and estimate a generalized panel regression model (GPRM) without imposing any parametric structure on (1) the function of observable explanatory variables, (2) the systematic function through which the function of observable explanatory variables, fixed effect, and disturbance term generate the outcome variable, or (3) the distribution of unobservables. I proceed with estimation using a series maximum rank correlation estimator (SMRCE) of the function of observable explanatory variables and provide conditions under which L2-consistency is achieved. I also provide conditions under which both L2 and uniform convergence rates of the SMRCE may be derived.

Download or read book Essays in Nonparametric Econometrics written by Michael Vogt and published by . This book was released on 2011 with total page 143 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Essays on Identification Estimation and Testing Using Nonparametric Methods written by Liquan Huang and published by . This book was released on 2015 with total page 105 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This dissertation is a collection of two papers studying the identification, estimation and testing of Econometrics problems using nonparametric methods. In Chapter 1, we study the estimation and testing of structural changes in panel data models with cross-sectional dependence and local stationarity. Instead of focusing on detection of abrupt structural changes, we consider smooth structural changes for which model parameters are unknown deterministic smooth functions of time, except for a finite number of time points. Such smooth alternatives are expected to be more realistic than sudden structural changes. We use nonparametric local smoothing method to consistently estimate the smooth changing parameters and develop two consistent tests for smooth structural changes in panel data models. The first test is to check whether all model parameters are stable over time. The second test is to check potential time-varying interaction while allowing for a common trend. Both tests have an asymptotic N (0, 1) distribution under the null hypothesis of parameter constancy and are consistent against a vast class of smooth structural changes as well as abrupt structural breaks with possibly unknown break points alternatives. Simulation studies show that the tests provide reliable inference in finite samples. Applying our tests to the cross-country growth accounting model using 14 OECD (Organisation for Economic Co-operation and Development) countries, we find instability in the model parameters. In Chapter 2, we study an under-identified triangular system of equations model that has k endogenous variables, but only strictly less than k excluded instrumental variables (k = 1, 2, ...). We consider a partially linear model. The endogenous variables for which excluded instruments are available are allowed to have a non-parametric effect. The linear part contains the endogenous variables (and higher order moments and interactions of these) for which we have no excluded instruments. Without the availability of additional instrumental variables, we exploit the additive separability in the partially linear model to generate additional exogenous variation that allows us to identify the coefficients of the endogenous regressors for which no excluded instruments are available. An easy-to-implement consistent estimator for the parametric part is presented. By applying the empirical process methods, we show that the estimator retains ?n-convergence rate and asymptotic normality even with the presence of generated regressors (when k > 1). The nonparametric part of the model is identified, and can be estimated with the standard nonparametric convergence rate. Monte Carlo simulation demonstrates our estimator performs well in finite samples."--Pages v-vi.

Download or read book Essays on Semiparametric and Nonparametric Methods in Econometrics written by Sokbae Lee and published by . This book was released on 2002 with total page 334 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Essays on Nonparametric and Semiparametric Econometrics written by Eduardo García Echeverri and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This dissertation consists of three chapters on nonparametric and semiparametric econometrics. Chapter 1 introduces the estimators used in the empirical applications of Chapter 2 and therefore should be read first. Chapter 3 is independent from the first two. The first chapter introduces a measure of intergenerational social mobility based on [phi]-divergences. The measure can be decomposed to study mobility in population subgroups of interest and can be used to describe mobility of multiple outcome variables across an arbitrary number of generations, unlike most indicators in the literature. The measure also fully controls for marginal distributions, meaning it is not affected by income growth or changes in income inequality. I propose two estimators for the measure: a non-parametric estimator and an estimator based on the mobility matrix. I provide conditions under which these estimators are n-consistent and asymptotically normal. In the second chapter, I use a specific [phi]-divergence (the Hellinger distance) to measure multidimensional social mobility in the USA and Germany. For this purpose, I use the Panel Study of Income Dynamics (PSID), the German Socio-Economic Panel (SOEP), and US administrative tax data. The measure reveals lower income and health mobility in the USA than Germany, but the opposite for educational mobility. It also shows income mobility for both countries is lowest in the tails of the parental income distribution and greatest in the centre. This inverted U-pattern is more pronounced in the USA. Most of these empirical findings for population subgroups are hidden to the existing indicators in the literature. Chapter 3 introduces a Low CPU Cost Semiparametric (LCS) estimator for linear single index models. The LCS estimator significantly reduces estimation time when compared to the standard semiparametric estimator in Ichimura (1993). It does so by more than 90% in medium sample sizes. Moreover, it makes estimation feasible in a regular PC when the sample size exceeds 10,000 observations. We provide conditions for consistency and asymptotic normality of the LCS estimator based on spline function theory. In our empirical application, we study determinants of expenditures in vocational rehabilitation (VR) programs using the RSA-911 data, containing information on more than 900,000 workers with disabilities. We find that minorities such as African Americans, Hispanic or females have lower expenditures in VR programs. On the other hand, expenditure is greater for more educated workers."--Pages viii-ix.

Download or read book Essays in Applied Econometrics written by Gurleen Kaur Popli and published by . This book was released on 2002 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Essays on Nonparametric and Applied Econometrics PHD written by Ahmet T. Ergun and published by . This book was released on with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Essays in Honor of Jerry Hausman written by Badi H. Baltagi and published by Emerald Group Publishing. This book was released on 2012-12-17 with total page 576 pages. Available in PDF, EPUB and Kindle. Book excerpt: Aims to annually publish original scholarly econometrics papers on designated topics with the intention of expanding the use of developed and emerging econometric techniques by disseminating ideas on the theory and practice of econometrics throughout the empirical economic, business and social science literature.

Download or read book Essays in Econometrics Nonparametrics and Robustness written by Benjamin William Deaner and published by . This book was released on 2021 with total page 212 pages. Available in PDF, EPUB and Kindle. Book excerpt: Heterogeneity and my key identifying assumptions follow from restrictions on the serial dependence structure.

Download or read book Essays on Semi non parametric Methods in Econometrics written by Sungwon Lee and published by . This book was released on 2018 with total page 416 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Essays on Nonparametric Estimation of Dynamic Models written by David Minkee Kang and published by . This book was released on 2012 with total page 72 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this dissertation we describe conditions for nonparametric identification and methods for estimating dynamic simultaneous equation models. These models have two distinct sources of endogeneity: lagged dependent variables that are related to autocorrelated unobservable variables and endogeneity through a simultaneous equations structure. Until now, nonparametric estimation has been limited to models with either one or the other. In the first chapter we show that the structural functions in such models are identified with panel data under assumptions commonly made in nonparametric econometrics. We do so by borrowing intuition from existing literature on dynamic panel models. In the second chapter of the dissertation we describe conditions needed for consistent and asymptotically normal nonparametric estimation of dynamic simultaneous equations models. In the third chapter we nonparametrically estimate dynamic demand functions for airline travel using recent data.

Download or read book Essays on Applied Nonparametric Econometrics written by Sabrina Dorn and published by . This book was released on 2015 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: