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Course Syllabus

2022/2023

Econometrics (Advanced Level)

Type: Mago-Lego
Delivered by: Department of Economics
When: 2, 3 module
Open to: students of one campus
Instructors: Alexander Muravyev
Language: English
ECTS credits: 6
Contact hours: 46

Course Syllabus

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Abstract

The course is designed for first-year graduate (Master) students following the program “Finance”. Its main goal is to familiarize the students with advanced methods of econometric research in economics and finance. In particular, the course accentuates the problem of endogeneity and the ways to address it in the analysis of cross-sectional and panel data. 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 economics and finance 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; Causes and consequences of endogeneity; Instrumental variables methods; Key panel data techniques; Difference-in-difference estimation techniques; An overview of the matching models and regression discontinuity designs. 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.
Learning Objectives

Learning Objectives

  • Familiarize the students with advanced methods of econometric research in economics and finance.
  • A review of the classical linear regression model
  • Familiarize the students with advanced methods of econometric research in economics and finance.
  • Key panel data techniques
  • An overview of the matching models and regression discontinuity designs
  • 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

Expected Learning Outcomes

  • Be able to apply the methods learnt when conducting own empirical analysis
  • Be familiar with and be able to use key capabilities of the statistical package “Stata”, including its programming options (the so-called do-files)
  • Know key methods of econometric research, understand the causes and consequences of endogeneity, know the main methods for addressing this problem
  • Understand endogeneity as a key issue affecting causal inference; be able to critically examine existing research from this angle
  • Understand the limits of interpreting regression results in most settings (the ceteris paribus clause).
Course Contents

Course Contents

  • Overview of the classical linear regression model
  • Introduction to econometric package Stata
  • Endogeneity. Instrumental variables methods
  • Analysis of panel (longitudinal) data
  • Estimation of treatment effects. The difference-in-difference estimator
  • Propensity score matching and regression discontinuity models
Assessment Elements

Assessment Elements

  • non-blocking Four home assignments
    Students’ progress is monitored during the course by four home assignments (two problem sets, one computer exercise in Stata and one empirical project). The assignments will be distributed in class and will be due in approximately two weeks. Homework assignments (only paper versions!) are to be handed in before class on the day they are due. No late homework will be accepted. The weights of the four homeworks in the final grade are 6%, 6%, 6% and 12% for homeworks 1, 2, 3 and 4, respectively.
  • non-blocking Mid-term test
    After the first seven classes, there is a closed book, closed notes mid-term written test that accounts for 20% of the final grade.
  • non-blocking Final exam
    At the end of the course there is a final exam, which is a closed book, closed notes test held in the classroom. The duration of the final exam is two academic hours. It accounts for 50% to the final grade.
Interim Assessment

Interim Assessment

  • 2022/2023 3rd module
    0.5 * Final exam + 0.2 * Four home assignments + 0.3 * Mid-term test
Bibliography

Bibliography

Recommended Core Bibliography

  • Giovanni Cerulli. (2015). Econometric Evaluation of Socio-Economic Programs. Springer. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsrep&AN=edsrep.b.spr.adstae.978.3.662.46405.2
  • Manuel, K. M., & Lunder, E. K. (2015). Contracting with Inverted Domestic Corporations: Answers to Frequently Asked Questions. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.28A2DA72

Recommended Additional Bibliography

  • Atanasov, V., & Black, B. (2016). Shock-Based Causal Inference in Corporate Finance and Accounting Research. Critical Finance Review, (2), 207. https://doi.org/10.1561/104.00000036
  • Bruce E. Hansen. (2013). Econometrics. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.C0DB9E1E
  • Roberts, M. R., & Whited, T. M. (2013). Endogeneity in Empirical Corporate Finance1. Handbook of the Economics of Finance, 493. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsrep&AN=edsrep.h.eee.finchp.2.a.493.572

Authors

  • MURAVEV ALEKSANDR ALEKSANDROVICH
  • POLYAKOVA EVGENIYA YUREVNA