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Course Syllabus

Master 2021/2022

Econometrics (Advanced Level)

Category 'Best Course for Broadening Horizons and Diversity of Knowledge and Skills'
Category 'Best Course for New Knowledge and Skills'
Type: Compulsory course (Financial Analyst)
Area of studies: Finance and Credit
Delivered by: HSE Banking Institute
Where: HSE Banking Institute
When: 1 year, 2, 3 module
Mode of studies: distance learning
Online hours: 28
Open to: students of one campus
Instructors: Elena V. Semerikova
Master’s programme: Financial Analyst
Language: English
ECTS credits: 5
Contact hours: 44

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 not only to give students new skills in both econometric tools and their application to contemporary economic problems, especially in financial economics, but also to study theoretically econometric methods and to review some sections of econometrics on a solid theoretical background. The structure of the course includes strict derivation of basic properties of estimation methods but excludes proofs of the most analytically sophisticated results. The main studying purpose of such topics is to clear understanding of econometric ideas, assumptions under which econometric approaches can be applied. At the same time, the students should get skills in reading and understanding of the most advance econometric articles.
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

  • Introduction. General concept of regression.
  • The geometry of linear regression
  • Classical linear regression (CLR)
  • OLS under assumption of normality
  • Multicollinearity
  • Models with stochastic repressors
  • Maximum likelihood (ML) estimators and OLS-estimators under normality assumption
  • Linear regression with heterogeneous observations
  • Linear regression under non-spherical disturbances. GLS
  • Linear regression under serial correlation
  • Linear regression diagnostics. Specification errors. Model selection
  • Dynamic regression with lagged variables
  • Time series econometrics
  • Panel Data Models. Fixed effects. Random effects
  • Two-stage least squares. Three-stage least squares
Assessment Elements

Assessment Elements

  • non-blocking the assessment of students' activity during classes
  • non-blocking the grades for mid-term exams
  • blocking final exam
Interim Assessment

Interim Assessment

  • 2021/2022 3rd module
    0.1 * the assessment of students' activity during classes + 0.2 * the grades for mid-term exams + 0.7 * final exam
Bibliography

Bibliography

Recommended Core Bibliography

  • A guide to modern econometrics, Verbeek, M., 2008
  • Jaksa Cvitanic, & Fernando Zapatero. (2004). Introduction to the Economics and Mathematics of Financial Markets. The MIT Press. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsrep&AN=edsrep.b.mtp.titles.0262532654
  • 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

  • Applied econometric time series, Enders, W., 2004
  • Mills, T. C., & Markellos, R. N. (2008). The Econometric Modelling of Financial Time Series: Vol. 3rd ed. Cambridge University Press.