Modulhandbuch_BWL_WiWi_WS 12_13.pdf - Fachbereich ...

Wahlpflichtbereich WahlpflichtbereichÖkonometrieRahmen von Masterstudiengängen der verschiedenenwissenschaftlichen Disziplinen.Students know what kind of data it takes to analyse economicproblems empirically. They are able to set up a linear model, toevaluate the (multivariate) model by means of regression analysis andto check the underlying assumptions. They are used to calculate andinterpret partial effects of the regressors, and they can test forsignificance of these effects. Hence, they can both carry outregression analyses themselves and also assess the validity ofempirical studies as reported elsewhere.InhalteContents of the courseInformation is the foundation of any “knowledge society”, and in thiscourse students learn how to quantitatively evaluate informationinherent in multivariate data. The statistical production process isreviewed starting from operationalization up to decision supportaspects. This knowledge will turn out to be helpful in the students’future occupational activities, in particular whenever economicproblems have to be solved by means of multivariate data analysis.Moreover, the course provides a fundamental understanding of thequantitative topics covered in various courses in masters’ programs ofany scientific discipline.Der Inhalt der Lehrveranstaltung ergibt sich aus derGliederung:1. Problemorientierte Einführung2. Grundlagen2.1 Einfachregression und Kleinst-Quadrat-Methode2.2 Das bivariate Lineare Modell2.3 Das multivariate Lineare Modell3. Statistische Analyse im multivariaten Linearen Modell3.1 Hypothesentests3.2 Multilkollinearität3.3 Binäre 0/1-Variablen als Regressoren3.4 Wahl der Kurvenform3.5 Fehlspezifikation4. Überprüfung der Annahmen im Linearen Modell4.1 Normalverteilung der Störgrößen4.2 Fehlende Autokorrelation der Störgrößen4.3 Homoskedastizität der StörgrößenThe outline of the course shows the lecture’s content:1. Problem-oriented Introduction2. Basic econometric methods2.1. Simple regression and the least squares principle2.2. The bivariate Linear Model2.3. The Multivariate Linear Model3. Statistical Inference in the Linear Model3.1. Hypotheses testing3.2. Multicollinearity3.3. Dummy regressors3.4. Choice of functional form3.5. Misspecification4. Checking the assumptions of the Linear Model4.1. Normal distribution of errors180