316202 Statistical and Econometric Models (V) (SoSe 2025)

Contents, comment

This course differs from other courses as its main objective is to convey the ideas of statistical modeling. These use methods such as estimation and testing.
However the focus is on applying these methods in order to obtain a statistical model for a given problem.

Different tools in this respect are discussed including
+ different classes of models (including models for count data, categorical data and panel data)
+ various diagnostic tools (hypothesis tests; AIC, stepwise selection procedures)
+ modelling tools such as non-parametric estimation methods

The course will mostly use likelihood maximization as estimation methods. But also econometric estimation tools like GMM (of which instrumental variables are a special case) are discussed to support modelling. The main reference is thr book by Cameron and Trivedi.

The course is quite intense as it features 4 hours of lectures each week supplement with a problem solving session/tutorial.

Exams: The course features a mid term exam and a final exam.

Bibliography

Colin Cameron and Pravin Trivedi: Microeconometrics: Methods and Applications. Cambridge University Press, 2005.

Teaching staff

Dates ( Calendar view )

Frequency Weekday Time Format / Place Period  
weekly Mo 14-16 S1-209 07.04.-18.07.2025
not on: 4/21/25 / 6/9/25
weekly Fr 12-14 U2-223 07.04.-18.07.2025
not on: 4/18/25

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Subject assignments

Module Course Requirements  
31-M-Ectr1 Econometrics 1 Statistical and Econometric Models Graded examination
Student information

The binding module descriptions contain further information, including specifications on the "types of assignments" students need to complete. In cases where a module description mentions more than one kind of assignment, the respective member of the teaching staff will decide which task(s) they assign the students.

Degree programme/academic programme Validity Variant Subdivision Status Semester LP  
Studieren ab 50    
Wirtschaftswissenschaften - Angebote für Erasmus / Incomings (Bachelor)    

Basic knowledge of statistics (such as the BA courses 31-M3 and 31-M9) is required. All prerequisites are covred with material in the lecture, however, the lectures will be hard to follow without sufficient prior knowledge.

The first two weeks in the course will provide hints on whether the prior knowledge is sufficient.

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SS2025_316202@ekvv.uni-bielefeld.de
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Last update basic details/teaching staff:
Friday, November 22, 2024 
Last update times:
Thursday, February 6, 2025 
Last update rooms:
Thursday, February 6, 2025 
Type(s) / SWS (hours per week per semester)
lecture (V) / 4
Language
This lecture is taught in english
Department
Faculty of Business Administration and Economics
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