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dc.contributor.advisorXu, Ke-Li
dc.creatorMa, Guangyi
dc.date.accessioned2012-10-19T15:30:51Z
dc.date.accessioned2012-10-22T18:03:11Z
dc.date.available2014-11-03T19:49:14Z
dc.date.created2012-08
dc.date.issued2012-10-19
dc.date.submittedAugust 2012
dc.identifier.urihttps://hdl.handle.net/1969.1/ETD-TAMU-2012-08-11768
dc.description.abstractIn this dissertation, I focus on the development and application of nonparametric methods in econometrics. First, a constrained nonparametric regression method is developed to estimate a function and its derivatives subject to shape restrictions implied by economic theory. The constrained estimators can be viewed as a set of empirical likelihood-based reweighted local polynomial estimators. They are shown to be weakly consistent and have the same first order asymptotic distribution as the unconstrained estimators. When the shape restrictions are correctly specified, the constrained estimators can achieve a large degree of finite sample bias reduction and thus outperform the unconstrained estimators. The constrained nonparametric regression method is applied on the estimation of daily option pricing function and state-price density function. Second, a modified Cumulative Sum of Squares (CUSQ) test is proposed to test structural changes in the unconditional volatility in a time-varying coefficient model. The proposed test is based on nonparametric residuals from local linear estimation of the time-varying coefficients. Asymptotic theory is provided to show that the new CUSQ test has standard null distribution and diverges at standard rate under the alternatives. Compared with a test based on least squares residuals, the new test enjoys correct size and good power properties. This is because, by estimating the model nonparametrically, one can circumvent the size distortion from potential structural changes in the mean. Empirical results from both simulation experiments and real data applications are presented to demonstrate the test's size and power properties. Third, an empirical study of testing the Purchasing Power Parity (PPP) hypothesis is conducted in a functional-coefficient cointegration model, which is consistent with equilibrium models of exchange rate determination with the presence of trans- actions costs in international trade. Supporting evidence of PPP is found in the recent float exchange rate era. The cointegration relation of nominal exchange rate and price levels varies conditioning on the real exchange rate volatility. The cointegration coefficients are more stable and numerically near the value implied by PPP theory when the real exchange rate volatility is relatively lower.en
dc.format.mimetypeapplication/pdf
dc.language.isoen_US
dc.subjectConstrained nonparametric regressionen
dc.subjectCUSUM of squares testen
dc.subjectderivative estimationen
dc.subjectempirical likelihooden
dc.subjectfunctional-coefficient cointegrationen
dc.subjectnonparametric alternativeen
dc.subjectoption pricingen
dc.subjectpurchasing power parityen
dc.subjectstate-price densityen
dc.subjectstructural changeen
dc.subjecttime-varying coefficient modelen
dc.subjectvolatility break.en
dc.titleThree Essays on Estimation and Testing of Nonparametric Modelsen
dc.typeThesisen
thesis.degree.departmentEconomicsen
thesis.degree.disciplineEconomicsen
thesis.degree.grantorTexas A&M Universityen
thesis.degree.nameDoctor of Philosophyen
thesis.degree.levelDoctoralen
dc.contributor.committeeMemberLi, Qi
dc.contributor.committeeMemberJansen, Dennis W.
dc.contributor.committeeMemberKim, Hwagyun
dc.type.genrethesisen
dc.type.materialtexten
local.embargo.terms2014-10-22


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