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Three Essays in Nonparametric Econometrics

dc.contributor.advisorVogt, Michael
dc.contributor.authorKhismatullina, Marina
dc.date.accessioned2021-09-02T11:13:26Z
dc.date.available2021-09-02T11:13:26Z
dc.date.issued02.09.2021
dc.identifier.urihttps://hdl.handle.net/20.500.11811/9289
dc.description.abstractThis thesis consists of three self-contained essays in econometrics and statistics. In these essays, I am interested in the nonparametric regression models and in developing new methods for testing various qualitative hypotheses about the trend functions in these models. Each of the three chapters proposes a novel multiscale testing procedure that is used either for investigating the properties of one time series (Chapter 1), or for comparison of the regression curves between multiple time series (Chapters 2 and 3). The underlying idea of any multiscale test is to consider a number of test statistics (each corresponding to a different set of values of some tuning parameters) simultaneously rather than to perform a separate test for each single test statistics, which leads to a well-known multiple testing problem. All of the proposed tests account for this problem by picking appropriate critical values, and the main methodological contributions of the current thesis are the theoretical results that these test all have (asymptotically) correct size and good power properties. Even though there are many similarities between the chapters, the research questions are quite distinct. In Chapter 1, the method is designed to determine whether the trend in one time series is decreasing or increasing, whereas in Chapters 2 and 3 the testing procedures were designed for comparison of multiple time trends and locating the differences. Moreover, the difference between Chapters 2 and 3 lies in the models under consideration: Chapter 2 deals with epidemic time trends in a simple nonparametric regression and places certain restrictions on the error terms in the observed times series, whereas Chapter 3 considers a very general model that allows for including covariates and fixed effects. The first two chapters are also completed by extensive simulation studies and the applications to the real-life data: temperature time series in Chapter 1 and the data on the new cases of COVID-19 in Chapter 2.en
dc.language.isoeng
dc.rightsIn Copyright
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/
dc.subjectMultiscale statistics
dc.subjectlong-run variance
dc.subjectnonparametric regression
dc.subjecttesting
dc.subjecttime series errors
dc.subject.ddc310 Allgemeine Statistiken
dc.subject.ddc330 Wirtschaft
dc.titleThree Essays in Nonparametric Econometrics
dc.typeDissertation oder Habilitation
dc.publisher.nameUniversitäts- und Landesbibliothek Bonn
dc.publisher.locationBonn
dc.rights.accessRightsopenAccess
dc.identifier.urnhttps://nbn-resolving.org/urn:nbn:de:hbz:5-63653
ulbbn.pubtypeErstveröffentlichung
ulbbnediss.affiliation.nameRheinische Friedrich-Wilhelms-Universität Bonn
ulbbnediss.affiliation.locationBonn
ulbbnediss.thesis.levelDissertation
ulbbnediss.dissID6365
ulbbnediss.date.accepted20.08.2021
ulbbnediss.instituteRechts- und Staatswissenschaftliche Fakultät / Fachbereich Wirtschaftswissenschaften : Bonn Graduate School of Economics (BGSE)
ulbbnediss.fakultaetRechts- und Staatswissenschaftliche Fakultät
dc.contributor.coRefereeKneip, Alois
ulbbnediss.contributor.gnd1240621272


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