Universität Wien FIND

040067 UK Applied Economics (BA) (2019S)

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

Summary

1 Zejcirovic, Moodle
2 Zejcirovic, Moodle
3 Holzner

Registration/Deregistration

Groups

Group 1

max. 30 participants
Language: English
LMS: Moodle

Lecturers

Classes (iCal) - next class is marked with N

Tuesday 19.03. 11:30 - 13:00 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Tuesday 26.03. 11:30 - 13:00 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Tuesday 02.04. 11:30 - 13:00 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Tuesday 09.04. 11:30 - 13:00 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Tuesday 30.04. 11:30 - 13:00 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Tuesday 07.05. 11:30 - 13:00 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Tuesday 14.05. 11:30 - 13:00 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Tuesday 21.05. 11:30 - 13:00 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Tuesday 28.05. 11:30 - 13:00 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Tuesday 04.06. 11:30 - 13:00 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Tuesday 18.06. 11:30 - 13:00 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Monday 24.06. 09:45 - 11:15 Hörsaal 7 Oskar-Morgenstern-Platz 1 1.Stock

Aims, contents and method of the course

This group is for Students majoring in Economics. Students majoring in Economic History, please attend Mario Holzner's Group 3.

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

Computer exercises, final exam, participation.

Minimum requirements and assessment criteria

Minimum of 51 points to obtain a positive grade.

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 18.03. 09:45 - 11:15 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Monday 25.03. 09:45 - 11:15 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Monday 01.04. 09:45 - 11:15 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Monday 08.04. 09:45 - 11:15 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Monday 29.04. 09:45 - 11:15 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Monday 06.05. 09:45 - 11:15 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Monday 13.05. 09:45 - 11:15 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Monday 20.05. 09:45 - 11:15 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Monday 27.05. 09:45 - 11:15 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Monday 03.06. 09:45 - 11:15 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Monday 17.06. 09:45 - 11:15 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Monday 24.06. 09:45 - 11:15 Hörsaal 7 Oskar-Morgenstern-Platz 1 1.Stock

Aims, contents and method of the course

Diese Gruppe ist für Studierende der Volkswirtschaftslehre. Studierende der Wirtschaftsgeschichte mögen bitte die Gruppe von Herrn Mario Holzner besuchen.

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

Computer exercises, final exam, participation.

Minimum requirements and assessment criteria

Minimum of 51 points to obtain a positive grade.

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

Lecturers

Classes (iCal) - next class is marked with N

Wednesday 06.03. 18:30 - 20:00 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Wednesday 27.03. 18:30 - 20:00 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Wednesday 03.04. 18:30 - 20:00 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Wednesday 10.04. 18:30 - 20:00 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Wednesday 08.05. 18:30 - 20:00 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Wednesday 15.05. 18:30 - 20:00 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Wednesday 22.05. 18:30 - 20:00 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Wednesday 29.05. 18:30 - 20:00 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Wednesday 05.06. 18:30 - 20:00 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Wednesday 12.06. 18:30 - 20:00 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Monday 17.06. 16:45 - 18:15 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Tuesday 18.06. 18:30 - 20:00 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Wednesday 19.06. 18:30 - 20:00 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Wednesday 26.06. 18:30 - 20:00 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß

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

Last modified: Fr 06.09.2019 09:47