Bachelor 2022/2023

Times Series Econometrics

Type: Elective course (Economics)

Area of studies: Economics

Delivered by: School of Finance

Where: Faculty of Economic Sciences

When: 4 year, 1, 2 module

Mode of studies: offline

Open to: students of one campus

Instructors: Madina Karamysheva, Matvei Sergeevich Zekhov

Language: English

ECTS credits: 6

Contact hours: 56

Course Syllabus

Abstract

We first review the basics of time series econometrics. Then, in more details, we look at the VAR class of models, including VAR, VARX, VECM, GVAR, and its rather broad application to macroeconomics, including fiscal and monetary policy and some finance applications. After that, we cover ARCH, GARCH with its application to value at risk and contagion. Course Prerequesites: Linear Algebra, Probability Theory, Mathematical Analysis, Basic Econometrics

Learning Objectives

• The objective of this course is to provide the student with tools for empirical analysis of time series and to show how econometric models can be applied to empirical models in macroeconomics and finance.
• to provide the student with tools for empirical analysis of time series and to show how econometric models can be applied to empirical models in macroeconomics and finance

Expected Learning Outcomes

• Apply econometric models to empirical models in macroeconomics and finance

Course Contents

• Introduction/reviewing of time series econometrics
• Non-stationarity: trends (deterministic and stochastic) and unit root tests: conse- quences, detection, remedies, breaks
• ARIMA Processes, Trend-cycle decompositions (Beveridge-Nelson, Hodrik-Prescott)
• Multivariate Time Series Models. VAR
• VAR applications
• Modeling the conditional variance (ARCH, GARCH, Multivariate GARCH)

Assessment Elements

• Quizzes
• Home assignments
• Big practical homework
  big practical homework in the end of the course
• Midterm test
  Midterm test is not compalsory, it works only for your benet, if you would like to take it
• Final test
  (if the grade of midterm is higher than the nal grade) and 60% other wise.
• Quizzes
• Home assignments
• Big practical homework
  big practical homework in the end of the course
• Midterm test
  Midterm test is not compalsory, it works only for your benet, if you would like to take it
• Final test
  (if the grade of midterm is higher than the nal grade) and 60% other wise.

Interim Assessment

• 2022/2023 2nd module
  0.2 * Big practical homework + 0.05 * Quizzes + 0.15 * Home assignments + 0.3 * Final test + 0.3 * Midterm test

Bibliography

Recommended Core Bibliography

• Applied econometric time series, Enders, W., 2004

Recommended Additional Bibliography

• Bruce E. Hansen. (2001). The New Econometrics of Structural Change: Dating Breaks in U.S. Labour Productivity. Journal of Economic Perspectives, (4), 117. https://doi.org/10.1257/jep.15.4.117
• Cochrane, J. H. (1994). Permanent and Transitory Components of GNP and Stock Prices. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.C46CF1D7
• Galí, J. (1996). Technology, Employment, and the Business Cycle: Do Technology Shocks Explain Aggregate Fluctuations? CEPR Discussion Papers. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsrep&AN=edsrep.p.cpr.ceprdp.1499
• Marianne Baxter, & Robert G. King. (1999). Measuring Business Cycles: Approximate Band-Pass Filters For Economic Time Series. The Review of Economics and Statistics, (4), 575. https://doi.org/10.1162/003465399558454
• Sims, C. A., Stock, J. H., & Watson, M. W. (1990). Inference in Linear Time Series Models with Some Unit Roots. Econometrica, (1), 113. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsrep&AN=edsrep.a.ecm.emetrp.v58y1990i1p113.44

Authors

• KARAMYSHEVA MADINA RINATOVNA