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| Semester | spring semester 2022 |
| Course frequency | Every spring sem. |
| Lecturers | Christian Kleiber (christian.kleiber@unibas.ch, Assessor) |
| Content | Introductory econometrics courses mainly cover the linear regression model, which is suitable for modelling response variables that may be considered as continuous. Also, the number of covariates is typically modest. The present course has two parts: * In the first part, the course will cover classical (nonlinear) regression models for applications where data are naturally discrete, e.g. binary or count data. It will use the framework of generalized linear models (GLMs), which provides a unified approach to models such as logit, probit and Poisson regression. Inference will be likelihood based. * In the second part, there will be an introduction to the recent literature on statistical learning (aka machine learning), specifically to the notion of regularisation, with LASSO as the main example. If time permits there will also be a chapter on finite mixture models. Remarks: * All course materials are on OLAT. * Empirical illustrations may include data from labor economics, health economics, or insurance, among further sources. The course will make use of the R language for statistical computing and graphics, hence basic knowledge of this software (including data import, running regressions) is expected. * In order to make room for further (regression) models, there will at most be a brief review of likelihood methods, possibly offered in digital form. Participants are expected to be familiar with these methods at the level of the compulsory MSc level Econometrics course. |
| Bibliography | Main references: Cameron AC, Trivedi PK (2005). Microeconometrics, Cambridge Univ. Press. James G, Witten D, Hastie T, Tibshirani R (2021). An Introduction to Statistical Learning, 2nd ed. New York: Springer. [available in electronic form via the university library!] Winkelmann R, Boes S (2009). Analysis of Microdata, 2nd ed, Springer. Further (topic-specific) references will be indicated in the relevant contexts. |
| Comments | The course will be taught "in class". |
| Weblink | Weblink |
| Admission requirements | Prerequisites: Completed bachelor's degree (for students majoring in Business and Economics). Introduction to Econometrics [BA] (for students from other departments: regression basics). Econometrics [MSc] (for students from other departments: a second course in statistics, notably likelihood methods). |
| Course application | Registration: Please enrol in MOnA. EUCOR-Students and students of other Swiss Universities have to enrol at the students administration office (studseksupport1@unibas.ch) within the official enrolment period. Enrolment = Registration for the exam! |
| Language of instruction | English |
| Use of digital media | No specific media used |
| Interval | Weekday | Time | Room |
|---|---|---|---|
| wöchentlich | Wednesday | 10.15-12.00 | Wirtschaftswissenschaftliche Fakultät, Seminarraum S15 HG.31 |
| Comments | The course will be taught "in class". |
| Modules |
Module: Core Competences in Economics (Master's Studies: Sustainable Development) Module: Field Electives in Economics and Public Policy (Master's Studies: Economics and Public Policy) Module: Non-Life Insurance (Master's Studies: Actuarial Science) Module: Preparation Master's Thesis in Economics (Master's Studies: Sustainable Development) Module: Specific Electives in Data Science and Computational Economics (Master's Studies: Business and Economics) Module: Specific Electives in Marketing and Strategic Management (Master's Studies: Business and Economics) Module: Statistics and Computational Science (Master's Studies: Actuarial Science) Module: Technology Field (Master's Studies: Business and Technology) Specialization Module: Areas of Specialization in International and/or Monetary Economics (Master's Studies: International and Monetary Economics) Specialization Module: Marketing and Strategic Management (Master's Studies: Business and Economics (Start of studies before 01.08.2021)) Specialization Module: Quantitative Methods (Master's Studies: Business and Economics (Start of studies before 01.08.2021)) |
| Assessment format | record of achievement |
| Assessment details | Notes for the Assessment: Written exam; 23.06.22; 10:15-11:45. WWZ S15: A-Z. https://wwz.unibas.ch/de/studium/pruefungen/vorlesungs-und-pruefungsraeume/ In addition, there will be assignments, for which students may work in groups of two. This time, I am aiming for bi-weekly assignments (more frequent but shorter than in previous years). Overall, the assignments will account for 30% of the final grade. |
| Assessment registration/deregistration | Reg.: course registration, dereg: cancel course registration |
| Repeat examination | no repeat examination |
| Scale | 1-6 0,1 |
| Repeated registration | as often as necessary |
| Responsible faculty | Faculty of Business and Economics , studiendekanat-wwz@unibas.ch |
| Offered by | Faculty of Business and Economics |