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Course Syllabus

Master 2022/2023

Econometrics (Advanced Level)

Type: Compulsory course (Master of Finance)
Area of studies: Finance and Credit
Delivered by: HSE Banking Institute
Where: HSE Banking Institute
When: 1 year, 3 module
Mode of studies: distance learning
Online hours: 20
Open to: students of one campus
Instructors: Elena V. Semerikova
Master’s programme: Finance
Language: English
ECTS credits: 6
Contact hours: 18

Course Syllabus

Full Syllabus

Abstract

The course will be a core one for the Banking Institute Master program “Financial Analyst”. The course is intended for studying during the first and the second semester of the Master level education. The course is a prerequisite for some both core and specialized courses of the curriculum. Because of study of material of the course, a student should master and be able to prove the basic facts of strict development of classical econometrics. She/he should also know main ideas of univariate and multivariable time-series analysis including Box-Jenkins approach, ARIMA (p, d, q) models, non-stationary time-series, unit root tests, co-integration, VAR and VECM.
Learning Objectives

Learning Objectives

  • The purpose of the course is to give students new and extended skills in both econometric tools and their application to contemporary economic problems. The main studying purpose of such topics is to clear understanding of econometric ideas, assumptions under which econometric approaches can be applied. The student should have skills of application of the indicated tools and methods to researches in problems of Micro-, Macroeconomics and Finance. The student should have knowledge and skills of “Econometrics” (Bachelor level) and a number of mathematical and statistical courses such that “Linear algebra”, “Statistics”, “Probability theory”.
Expected Learning Outcomes

Expected Learning Outcomes

  • The student should have skills of application of the indicated tools and methods to researches in problems of Micro-, Macroeconomics and Finance
Course Contents

Course Contents

  • OLS
  • Model Specification
  • Multicollinearity, Heteroskedasticity and Autocorrelation
  • Endogeneity and Instrumental Variables
  • Project Assignment 1
  • Maximum Likelihood and Models with Limited Dependent Variables
  • Time-series econometrics. Univariate time series
  • Time-series econometrics. Multivariate time series
  • Panel Data Analysis
  • Project Assignment 2
Assessment Elements

Assessment Elements

  • non-blocking Project Assignment 2
  • non-blocking Project Assignment 1
  • non-blocking Еженедельные тесты
Interim Assessment

Interim Assessment

  • 2022/2023 3rd module
    0.64 * Еженедельные тесты + 0.16 * Project Assignment 1 + 0.2 * Project Assignment 2
Bibliography

Bibliography

Recommended Core Bibliography

  • Verbeek, M. (2017). A Guide to Modern Econometrics (Vol. 5th edition). Hoboken, NJ: Wiley. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1639496
  • Verbeek, M. (DE-588)170802655, (DE-576)164668535. (2012). A guide to modern econometrics / Marno Verbeek. Chichester: Wiley. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edswao&AN=edswao.357323661

Recommended Additional Bibliography

  • Enders, W. (2015). Applied Econometric Time Series (Vol. Fourth edition). Hoboken, NJ: Wiley. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1639192