Postgraduate course
2023/2024![Learning Objectives](/f/src/global/i/edu/objectives.svg)
![Expected Learning Outcomes](/f/src/global/i/edu/results.svg)
![Course Contents](/f/src/global/i/edu/sections.svg)
![Interim Assessment](/f/src/global/i/edu/intermediate_certification.svg)
![Bibliography](/f/src/global/i/edu/library.svg)
Postgraduate seminar
Type:
Compulsory course
Area of studies:
Postgraduate Studies
Delivered by:
Department of Economics
When:
2 year, 1 semester
Mode of studies:
offline
Open to:
students of one campus
Instructors:
Leonid V. Azarnert
Language:
English
ECTS credits:
4
Contact hours:
48
Course Syllabus
Abstract
The course is designed for first-year graduate (PhD) students in Economics and Management. Its main goal is to familiarize the students with contemporary methods of econometric research in economics and management. The course is of applied nature: The material is presented, whenever possible, in a non-technical way, examples of empirical studies published in leading international journals are discussed, and the lectures are supplemented by exercises in the computer lab.
The topics covered include: A review of the classical linear regression model; Instrumental variables methods; Baseline models for panel data: pooled OLS, FE and RE; Advanced models with panel data, including dynamic panel data models; Overview of key models for limited dependent variables.
Learning Objectives
- Computer exercises using the statistical software package “Stata” are an integral part of the course, which ensures that the students get hands-on experience of analyzing real world data.
Expected Learning Outcomes
- Be able to apply the methods learnt when conducting own empirical analysis
- Be familiar with key methods of (micro-)econometric research
- Be familiar with and be able to use key capabilities of the statistical package “Stata”, including its programming options (do-files)
Course Contents
- The classical linear regression model: overview of specification, estimation and inference
- Instrumental variables methods
- Models with panel data: pooled OLS, FE and RE
- Advanced models with panel data, incl. the Hausman-Taylor, Anderson and Hsiao and Arellano-Bond models
- Overview of key models for limited dependent variables
- First Part of the Course
Interim Assessment
- 2022/2023 1st semester0.5 * An empirical project + 0.5 * Exam
- 2023/2024 1st semester1 * Attestation of other Seminar's parts
Bibliography
Recommended Core Bibliography
- Bruce E. Hansen. (2013). Econometrics. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.C0DB9E1E
- Data analysis using stata, Kohler, U., 2012
- Jeffrey M. Wooldridge. (2019). Introductory Econometrics: A Modern Approach, Edition 7. Cengage Learning.
Recommended Additional Bibliography
- Microeconometrics using Stata, Cameron, A.C., 2010
- Microeconometrics: methods and applications, Cameron, A., 2005
- Wooldridge, J. M. (2002). Econometric Analysis of Cross Section and Panel Data. Cambridge, Mass: MIT Press. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=78079