Кто читает:: Департамент экономики и финансов

Статус:: Курс по выбору

Когда читается:: 4-й курс, 1, 2 модуль

Преподаватель

Шенкман (Попова) Евгения Андреевна

Full Syllabus

Abstract

The course aims to provide students with a theoretical understanding of the basics of time series modeling and demonstrate their application on real data. This course is blended. Students learn theory from the online course “Macroeconometric forecasting” on the EDX platform, developed by the International monetary fund. On practical session, they will apply models to macroeconomic and financial data. The course begins with essentials of working with time series data. The next part of the course covers all basic time series models, such as: ARIMA, SARIMA, ARCH and GARCH, VAR and VECM. As a result of the course, student will make a project on real data: prepare data for analysis, choose appropriate model, apply it and interpret results. The practical session R language is applied, some basics of it are trained through DataCamp cources.

Learning Objectives

Analyze economic data in accordance with the task, make preliminary data analysis.
Build appropriate econometric time series models for the research question, analyze and interpret results.
Understand limitation and relevance of the models.

Expected Learning Outcomes

Know basic concepts of multivariate time series analysis, build appropriate econometric time series models.
Know basic concepts of univariate time series analysis, build appropriate econometric time series models.

Course Contents

Univariate time series analysis
Mutivariate time series analysis

Assessment Elements

Test
Exam
Reports
DC (DataCamp)

Interim Assessment

2022/2023 2nd module
0.25 * Test + 0.05 * DC (DataCamp) + 0.15 * Reports + 0.4 * Exam

Bibliography

Recommended Core Bibliography

Klaus Neusser. (2016). Time Series Econometrics. Springer. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsrep&AN=edsrep.b.spr.sptbec.978.3.319.32862.1
Palma, W. (2016). Time Series Analysis. Hoboken: Wiley. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1229817

Recommended Additional Bibliography

Bleikh, H. Y., & Young, W. (2013). Time Series Analysis and Adjustment : Measuring, Modelling and Forecasting for Business and Economics. Farnham: Routledge. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=531761
Montgomery, D. C., Jennings, C. L., & Kulahci, M. (2015). Introduction to Time Series Analysis and Forecasting (Vol. Second edition). Hoboken, New Jersey: Wiley-Interscience. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=985114

Бакалаврская программа «Экономика»

Time Series Analysis