Estimation and Inference in Special Nonparametric Models with Applications to Topics in Development Economics

Wiesenfarth, Manuel

dc.contributor.advisor	Krivobokova, Tatyana Prof. Dr.	de
dc.contributor.author	Wiesenfarth, Manuel	de
dc.date.accessioned	2012-07-04T16:03:16Z	de
dc.date.accessioned	2013-01-18T13:53:52Z	de
dc.date.available	2013-01-30T23:50:56Z	de
dc.date.issued	2012-07-04	de
dc.identifier.uri	http://hdl.handle.net/11858/00-1735-0000-000D-F09E-B	de
dc.identifier.uri	http://dx.doi.org/10.53846/goediss-3021
dc.description.abstract	Semiparametrische additive Regressionsmodelle schw	de
dc.format.mimetype	application/pdf	de
dc.language.iso	eng	de
dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/3.0/	de
dc.title	Estimation and Inference in Special Nonparametric Models with Applications to Topics in Development Economics	de
dc.type	doctoralThesis	de
dc.title.translated	Schätzung und Inferenz in speziellen nichtparametrischen Modellen mit Andwendungen in der Entwicklungsökonomie	de
dc.contributor.referee	Krivobokova, Tatyana Prof. Dr.	de
dc.date.examination	2012-05-11	de
dc.subject.dnb	310 Statistik	de
dc.subject.gok	EGCG 080	de
dc.description.abstracteng	Semiparametric additive regression models relax the common assumption of covariate effects to have a known functional form specified by some polynomial. These models only assume that relationships are smooth and are additively separable and thus are less restrictive than common parametric approaches. Estimation techniques for such models assuming all covariates to be exogenous, i.e. uncorrelated to the error term ruling out the presence of confounding omitted variables, for example, have become widely available. However, additive models with weaker assumptions on the error term and methods for inference such as simultaneous confidence bands and specification tests are still subject to extensive research. Thus, the objectives of the thesis are the development of flexible methods for estimation and inference and their application in various complex data situations. Thereby, particular focus is laid on the computational implementation of all proposed approaches aiming at the provision of user-friendly software packages. First, the determinants of chronic child undernutrition in Kenya are analyzed. Particular research questions include the possibility of catch-up growth, i.e. improvements of the nutritional status over age, and relevance of hypotheses on the functional forms of certain effects. In order to address these questions, simultaneous confidence bands for additive models with locally-adaptive smoothed components and heteroscedastic errors are proposed. These appropriately quantify the estimation uncertainty of function estimates and can be used for assessing the statistical significance of an effect and of certain features in a curve. Further, a powerful nonparametric specification test is introduced that allows to test for polynomial regression versus nonparametric alternatives. Next, the needs-relatedness of relief supply in earthquake-affected communities in Pakistan is studied. Here, non-random sample selection calls for the application of a sample selection model with flexible spatial and time-varying effects accounting for unobserved regional heterogeneity and for varying survivor needs over changing seasonal conditions. A flexible Bayesian approach to correct for the sample selection bias is proposed that allows to simultaneously estimate the determinants of the probability to receive relief supply and of the amount of delivered supply. Finally, the usual assumption of the unobservable error term to be orthogonal to the covariates is relaxed relying on the availability of some instrumental variable. A Bayesian nonparametric instrumental variable approach is proposed where bias correction relies on a simultaneous equations specification with flexible modeling of both the covariate effects and the joint error distribution. The approach is used to analyze the relationship between class size and scholastic achievements of students in Israel.	de
dc.contributor.coReferee	Klasen, Stephan Prof. Dr.	de
dc.contributor.thirdReferee	Kneib, Thomas Prof. Dr.	de
dc.subject.topic	Economics	de
dc.subject.ger	adaptive Glättung	de
dc.subject.ger	additive Modelle	de
dc.subject.ger	bayesianische P-splines	de
dc.subject.ger	Instrumentalvariablen	de
dc.subject.ger	Penalized Splines	de
dc.subject.ger	Simultane Konfidenzbänder	de
dc.subject.ger	Spezifikationstest	de
dc.subject.ger	Unterernährung	de
dc.subject.eng	adaptive smoothing	de
dc.subject.eng	additive model	de
dc.subject.eng	Bayesian P-splines	de
dc.subject.eng	instrumental variables	de
dc.subject.eng	penalized splines	de
dc.subject.eng	sample selection model	de
dc.subject.eng	simultaneous confidence bands	de
dc.subject.eng	specification test	de
dc.subject.eng	undernutrition	de
dc.subject.bk	31.73	de
dc.subject.bk	83.03	de
dc.subject.bk	83.46	de
dc.identifier.urn	urn:nbn:de:gbv:7-webdoc-3599-4	de
dc.identifier.purl	webdoc-3599	de
dc.affiliation.institute	Wirtschaftswissenschaftliche Fakultät	de
dc.identifier.ppn	737899212	de

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