Bachelor
2020/2021![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)
![Assessment Elements](/f/src/global/i/edu/controls.svg)
![Interim Assessment](/f/src/global/i/edu/intermediate_certification.svg)
![Bibliography](/f/src/global/i/edu/library.svg)
Panel Data
Type:
Elective course (Economics)
Area of studies:
Economics
Delivered by:
Department of Economics
When:
3 year, 4 module
Mode of studies:
offline
Language:
English
ECTS credits:
3
Contact hours:
32
Course Syllabus
Abstract
The course is designed for third-year undergraduate students in Economics. The course is of applied nature: The material is presented, whenever possible, in a non-technical way, with examples of empirical studies published in leading international economics and finance journals discussed in class. Lectures are supplemented by computer labs, which ensures that the students get hands-on experience of analyzing real world panel data using Stata 14/15. The topics covered include: pooled OLS model, fixed- and random-effects models, dealing with unbalanced panels, measurement error in panel data, endogenous explanatory variables, the Hausman-Taylor model, and an overview of dynamic panel data models (the Nickel bias, Anderson-Hsiao estimator and Arellano-Bond estimator).
Learning Objectives
- familiarize the students with contemporary methods of panel data analysis, starting with the pooled OLS model and ending with dynamic panel data models
Expected Learning Outcomes
- Students should have a firm grasp of the key methods of panel data analysis
- Students should be able to effectively apply these methods in own empirical research.
- Students should be familiar with and be able to use key capabilities of the statistical package “Stata”, including its programming options (the so-called do-files).
Course Contents
- Panel data and pooled OLS model
- The fixed effects model
- The random-effects model
- Further topics in the analysis of linear panel data models
- Dynamic panel data
Assessment Elements
- homework assignmentThe home assignment includes problems and/or computer exercises in Stata. The assignment will be distributed in class and will be due in approximately two weeks. The homework (only paper versions, files sent by email will not be accepted!) is to be handed in before class on the day it is due. No late homework is accepted
- midterm examThe midterm exam is a closed book, closed notes test scheduled in the middle of the course
- final examThe duration of the final exam is two academic hours. The examination is conducted in writing using synchronous proctoring. The exam is conducted on the online HSE Moodle platform (https://hse.student.examus.net). You must connect to the exam 15 minutes before the start. On the Examus platform, system testing is available. Student's computer must meet the requirements: (https://elearning.hse.ru/data/2020/05/07/1544135594/Технические%20требования%20к%20ПК%20студента.pdf) To participate in the exam, the student must: go to the proctoring platform in advance, conduct a system test, turn on the camera and microphone, and verify identity. During the exam, students are prohibited from: communicating (on social networks, with people in the room), writing off. During the exam, students are allowed to: use A4 sheets. The completed task must be photographed or scanned and downloaded to the Moodle system. Click the Finish Exam button to successfully save your answer. A short-term communication disruption during the exam is considered interruption of communication up to 10 minutes. A long-term communication disorder during an exam is considered to be a communication interruption of 10 minutes or more. In case of a long-term communication disruption, the student cannot continue to participate in the exam. The transfer procedure is similar to the surrender procedure.
Interim Assessment
- Interim assessment (4 module)0.5 * final exam + 0.25 * homework assignment + 0.25 * midterm exam
Bibliography
Recommended Core Bibliography
- Patrick Sevestre, & Laszlo Matyas. (2008). The Econometrics of Panel Data. Post-Print. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsrep&AN=edsrep.p.hal.journl.halshs.00279977
Recommended Additional Bibliography
- David Roodman. (2006). How to Do xtabond2: An Introduction to ‘Difference’ and ‘System. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.BDA319DD
- Mátyás, L. (2017). The Econometrics of Multi-dimensional Panels : Theory and Applications. [N.p.]: Springer. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1565303