Module 31-M-Ectr1 Econometrics 1

Faculty

Faculty of Business Administration and Economics

Person responsible for module

Herr Prof. Dr. Dietmar Bauer

Regular cycle (beginning)

Every summer semester

Credit points and duration

7 Credit points

For information on the duration of the modul, refer to the courses of study in which the module is used.

Competencies

Non-official translation of the module descriptions. Only the German version is legally binding.

Students are introduced to the crucial concepts of point and interval estimation - in a descriptive and inferential sense - as well as hypothesis testing in the context of multiple linear regression models. In particular, they learn about different views on the associated data processing strategies. This should provide a deep understanding and allows to circumvent many common traps in empirical research. Furthermore, techniques are implemented using common statistical software to allow students to pursue their own empirical research projects.

Content of teaching

The course focusses on the multiple linear regression model. Its clear structure allows introducing students to estimation and inference techniques in an intuitive manner while its flexibility still makes it a valuable tool for empirical research. The course starts with ordinary least-squares as a baseline and introduces extensions to cope with unequal variances and parameter constraints.
Classical results such as least squares projections and Gauss-Markov theory are introduced. Indispensable linear algebra results such as the QR decomposition are reviewed and basic programming skills are developed. Nonlinear models and more advanced estimation methodology are treated if time permits.

Recommended previous knowledge

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Necessary requirements

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Explanation regarding the elements of the module

In the second part of the lecture, the competences acquired in the first part (definitions, methods, models, etc.) are significantly incorporated, so that the acquisition of these competences is tested in the midterm.

Module structure: 1 bPr ¹

Courses

Statistical and Econometric Models

Type lecture

Regular cycle SoSe

Workload⁵ 150 h (60 + 90)

LP 5 [Pr]

Tutorial

Type tutorial

Regular cycle SoSe

Workload⁵ 60 h (30 + 30)

LP 2

Examinations

written examination o. e-oral examination o. oral examination o. portfolio

Allocated examiner Teaching staff of the course Statistical and Econometric Models (lecture)

Weighting 1

Workload -

LP² -

The module examination consists of a portfolio of midterm (seventh / eighth week of classes, in case of blocked course: contents of the first half of the course) and Final (each 90-minute exam or 20-minute oral (e-)exam), such that the grade for the module is awarded by the teacher of the course, a 90 to 120-minute exam or a 15 to 25-minute oral (e-)exam.

The module is used in these degree programmes:

Degree programme	Profile	Recommended start ³	Duration	Mandatory option ⁴
Data Science / Master of Science [FsB vom 06.04.2018 mit Änderungen vom 01.07.2019, 02.03.2020, 21.03.2023 und 10.12.2024]	Variante 2	2.	one semester	Obligation
Mathematical Economics / Master of Science [FsB vom 28.02.2025]	Mathematics	1. o. 2.	one semester	Compulsory optional subject
Mathematical Economics / Master of Science [FsB vom 28.02.2025]	Economics	1. o. 2.	one semester	Compulsory optional subject
Mathematical Economics / Master of Science [FsB vom 28.02.2025]	Finance	1. o. 2.	one semester	Compulsory optional subject
Quantitative Economics / Master of Science [FsB vom 15.02.2013 mit Änderungen vom 01.07.2015 und 31.03.2023]		2.	one semester	Obligation
Quantitative Economics / Master of Science [FsB vom 15.02.2013 mit Änderungen vom 01.07.2015 und 31.03.2023]	International Track	2.	one semester	Obligation
Statistical Science / Master of Science [FsB vom 15.10.2014 mit Änderungen vom 05.09.2016, 21.03.2023 und 10.12.2024 und Berichtigung vom 12.07.2017]	Option 1	2.	one semester	Obligation
Statistical Science / Master of Science [FsB vom 15.10.2014 mit Änderungen vom 05.09.2016, 21.03.2023 und 10.12.2024 und Berichtigung vom 12.07.2017]	Option 2	2.	one semester	Obligation
Mathematical Economics / Master of Science [FsB vom 16.09.2019 mit Änderungen vom 15.11.2022, 01.03.2024 und 10.12.2024]	Mathematics	1. o. 2.	one semester	Compulsory optional subject
Mathematical Economics / Master of Science [FsB vom 16.09.2019 mit Änderungen vom 15.11.2022, 01.03.2024 und 10.12.2024]	Economics	1. o. 2.	one semester	Compulsory optional subject
Mathematical Economics / Master of Science [FsB vom 16.09.2019 mit Änderungen vom 15.11.2022, 01.03.2024 und 10.12.2024]	Finance	1. o. 2.	one semester	Compulsory optional subject
Mathematical Economics / Master of Science [FsB vom 15.02.2013 mit Berichtigungen vom 04.11.2013,15.01.2015 und 15.10.2019 und Änderungen vom 15.01.2014, 15.12.2014, 01.04.2016, 15.05.2017, 01.03.2019 und 16.09.2019]	Finance	1. o. 2.	one semester	Compulsory optional subject
Mathematical Economics / Master of Science [FsB vom 15.02.2013 mit Berichtigungen vom 04.11.2013,15.01.2015 und 15.10.2019 und Änderungen vom 15.01.2014, 15.12.2014, 01.04.2016, 15.05.2017, 01.03.2019 und 16.09.2019]	Mathematics	1. o. 2.	one semester	Compulsory optional subject
Mathematical Economics / Master of Science [FsB vom 15.02.2013 mit Berichtigungen vom 04.11.2013,15.01.2015 und 15.10.2019 und Änderungen vom 15.01.2014, 15.12.2014, 01.04.2016, 15.05.2017, 01.03.2019 und 16.09.2019]	Economics	1. o. 2.	one semester	Compulsory optional subject

Automatic check for completeness

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Legend

1: The module structure displays the required number of study requirements and examinations.
2: LP is the short form for credit points.
3: The figures in this column are the specialist semesters in which it is recommended to start the module. Depending on the individual study schedule, entirely different courses of study are possible and advisable.
4: Explanations on mandatory option: "Obligation" means: This module is mandatory for the course of the studies; "Optional obligation" means: This module belongs to a number of modules available for selection under certain circumstances. This is more precisely regulated by the "Subject-related regulations" (see navigation).
5: Workload (contact time + self-study)
SoSe: Summer semester
WiSe: Winter semester
SL: Study requirement
Pr: Examination
bPr: Number of examinations with grades
uPr: Number of examinations without grades
: This academic achievement can be reported and recognised.