Universität Wien
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040067 UK Applied Economics (BA) (2021S)

4.00 ECTS (2.00 SWS), SPL 4 - Wirtschaftswissenschaften
Continuous assessment of course work
REMOTE

Summary

1 Zejcirovic , Moodle
2 Zejcirovic , Moodle
3 Holzner , Moodle

Registration/Deregistration

Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).
Registration information is available for each group.

Groups

Group 1

max. 30 participants
Language: English
LMS: Moodle

Lecturers

Classes (iCal) - next class is marked with N

  • Tuesday 02.03. 11:30 - 13:00 Digital
  • Tuesday 09.03. 11:30 - 13:00 Digital
  • Tuesday 16.03. 11:30 - 13:00 Digital
  • Tuesday 23.03. 11:30 - 13:00 Digital
  • Tuesday 13.04. 11:30 - 13:00 Digital
  • Tuesday 20.04. 11:30 - 13:00 Digital
  • Tuesday 27.04. 11:30 - 13:00 Digital
  • Tuesday 04.05. 11:30 - 13:00 Digital
  • Tuesday 11.05. 11:30 - 13:00 Digital
  • Tuesday 18.05. 11:30 - 13:00 Digital
  • Tuesday 01.06. 11:30 - 13:00 Digital
  • Tuesday 08.06. 11:30 - 13:00 Digital
  • Tuesday 15.06. 11:30 - 13:00 Digital
  • Tuesday 22.06. 11:30 - 13:00 Digital
  • Tuesday 29.06. 11:30 - 13:00 Digital

Aims, contents and method of the course

ATTENTION: Students need computer access to be able to work with the statistical program we will discuss in class. If the students lose access to the University PC-labs (due to corona restrictions), they should make sure that they have access to a PC at home, to be able to work on the problem sets.

This group is solely for students majoring in Economics. Students majoring in Economic History (or Economics), please attend Mario Holzner's Group.

This is a course in which students will reinforce the tools learned in Introductory Econometrics (BA) by applying them to real-world data sets using econometric software. Prior knowledge at the level will be assumed throughout the course. The aim of the course is for students to get hands-on experience in analyzing observational data using econometric software and acquire the tools to carry out empirical research projects on their own.

Assessment and permitted materials

Four problem sets (total of 60%), final exam (40%).

Minimum requirements and assessment criteria

Students should hand in all problem sets and attend the final exam. A minimum of 51% is required to pass the course.

Examination topics

We will seek to cover the following topics in this course:
1. Introduction
2. Review of the Linear Regression Model and Inference
4. Multiple Linear Regression Model
5. Endogeneity

Reading list

The following textbooks are available in the library:

1) Hill R. C., Griffiths W. E., Lim G. C. (2018). Principles of Econometrics. (Fifth edition)

2) Wooldridge, J. (2015). Introductory econometrics: A modern approach (Sixth edition, student ed.).

Group 2

max. 30 participants
Language: English
LMS: Moodle

Lecturers

Classes (iCal) - next class is marked with N

  • Monday 01.03. 09:45 - 11:15 Digital
  • Monday 08.03. 09:45 - 11:15 Digital
  • Monday 15.03. 09:45 - 11:15 Digital
  • Monday 22.03. 09:45 - 11:15 Digital
  • Monday 12.04. 09:45 - 11:15 Digital
  • Monday 19.04. 09:45 - 11:15 Digital
  • Monday 26.04. 09:45 - 11:15 Digital
  • Monday 03.05. 09:45 - 11:15 Digital
  • Monday 10.05. 09:45 - 11:15 Digital
  • Monday 17.05. 09:45 - 11:15 Digital
  • Monday 31.05. 09:45 - 11:15 Digital
  • Monday 07.06. 09:45 - 11:15 Digital
  • Monday 14.06. 09:45 - 11:15 Digital
  • Monday 21.06. 09:45 - 11:15 Digital
  • Monday 28.06. 09:45 - 11:15 Digital

Aims, contents and method of the course

ATTENTION: Students need computer access to be able to work with the statistical program we will discuss in class. If the students lose access to the University PC-labs (due to corona restrictions), they should make sure that they have access to a PC at home, to be able to work on the problem sets.

This group is solely for students majoring in Economics. Students majoring in Economic History (or Economics), please attend Mario Holzner's Group.

This is a course in which students will reinforce the tools learned in Introductory Econometrics (BA) by applying them to real-world data sets using econometric software. Prior knowledge at the level will be assumed throughout the course. The aim of the course is for students to get hands-on experience in analyzing observational data using econometric software and acquire the tools to carry out empirical research projects on their own.

Assessment and permitted materials

Four problem sets (total of 60%), final exam (40%).

Minimum requirements and assessment criteria

Students should hand in all problem sets and attend the final exam. A minimum of 51% is required to pass the course.

Examination topics

We will seek to cover the following topics in this course:
1. Introduction
2. Review of the Linear Regression Model and Inference
4. Multiple Linear Regression Model
5. Endogeneity

Reading list

The following textbooks are available in the library:
1) Hill R. C., Griffiths W. E., Lim G. C. (2018). Principles of Econometrics. (Fifth edition)

2) Wooldridge, J. (2015). Introductory econometrics: A modern approach (Sixth edition, student ed.).

Group 3

max. 30 participants
Language: English
LMS: Moodle

Lecturers

Classes (iCal) - next class is marked with N

  • Wednesday 03.03. 18:30 - 20:00 Digital
  • Wednesday 10.03. 18:30 - 20:00 Digital
  • Wednesday 17.03. 18:30 - 20:00 Digital
  • Wednesday 24.03. 18:30 - 20:00 Digital
  • Wednesday 14.04. 18:30 - 20:00 Digital
  • Wednesday 21.04. 18:30 - 20:00 Digital
  • Wednesday 28.04. 18:30 - 20:00 Digital
  • Wednesday 05.05. 18:30 - 20:00 Digital
  • Wednesday 12.05. 18:30 - 20:00 Digital
  • Wednesday 19.05. 18:30 - 20:00 Digital
  • Wednesday 26.05. 18:30 - 20:00 Digital
  • Wednesday 02.06. 18:30 - 20:00 Digital
  • Wednesday 09.06. 18:30 - 20:00 Digital
  • Wednesday 16.06. 18:30 - 20:00 Digital
  • Wednesday 23.06. 18:30 - 20:00 Digital
  • Wednesday 30.06. 18:30 - 20:00 Digital

Aims, contents and method of the course

Abstract: The course introduces the main workhorse of applied empirical research in economics, linear regression by ordinary least squares (OLS). After having taken the course, students should understand and be able to evaluate applied analysis of cross-section data and be able to undertake such analysis themselves. A major focus of the course is on historical data and cliometric research questions. Thus, the course is also relevant for students of economic history interested in quantitative methods. The main output shall be an independent research paper on a data set of own choice. Basic theoretical knowledge as well as computer skills are required.

Outline: Introduction to econometrics and cliometrics; Review of probability and statistics; How to find and handle (historical) economic data; Linear regression with one regressor; Hypothesis testing; Linear regressions with multiple regressors; Introduction to the general-purpose statistical software package STATA; Nonlinear regression functions; Assessing statistical studies; Introduction to instrumental variable regressions; Estimation of popular economic models such as the Cobb-Douglas production function; Introduction to LaTeX; Presentation and discussion of the independent research papers.

Assessment and permitted materials

Assessment: Test (20 points), participation in class (35 points) and an independent research paper (45 points) to be handed in in written form and to be presented at the end of the term.

Minimum requirements and assessment criteria

A minimum of 51 points is needed for a positive evaluation.

Examination topics

Correct interpretation of the results of concrete OLS cross country models, such as the goodness-of-fit of the model and the estimated coefficients.

Association in the course directory

MA Geschichte (Version 2019): PM 2 und PM 3, Methodenworkshop (5 ECTS), Schwerpunkt Wirtschafts- und Sozialgeschichte

Last modified: Fr 12.05.2023 00:12