Delivered at:: International College of Economics and Finance

Course type:: Compulsory course

When:: 1 year, 1-4 module

Instructors

Budanova, Sofya

Slonimczyk, Fabian

Full Syllabus

Abstract

The main objectives of the first part of Econometrics are to introduce students to basic econometric techniques and to prepare them to do their own applied work. Students are encouraged to think of the course as a preparation toward their thesis research project. The course is taught in English. The purpose of the course is not only to develop new skills in 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. In the first module of the semester, we cover fundamental topics in time series analysis, such as ARMA models, non-stationary time-series, Brownian motion and unit root tests, cointegration, VAR and VECM. During the second module students study binary choice models (logit, probit, tobit, Heckman) and basic concepts of panel data analysis (pooled regression, fixed and random effects, dynamic panel models, binary choice panel data). All topics are accompanied with real data examples in R, Stata, EViews, and JMulTi. The course is taught in English. Course Pre-requisites: Calculus, Probability Theory and Statistics at an intermediate level. Completion of Mathematics for Economics and Finance course is required. Successful completion of Econometrics will allow students to take the Financial Econometrics class.

Learning Objectives

During the course students will be introduced to modern approaches in analysing economic and financial data
Upon completion of the course students should be:familiar with the basic tools available to economists for testing theories, estimating the parameters of economic relationships in financial markets and forecasting financial and macroeconomic variables;
ble to read, interpret and replicate the results of published papers in economics and finance using standard computer packages and real-world data

Expected Learning Outcomes

Demonstrate a basic understanding of the SC estimation technique and inference
Differentiate between sharp and fuzzy RD design
Give explanation of conditional expectations and their relationship to the population regression function
Explain the difference between fixed-effect, random-effects, and first-difference models; the parallel trends assumption
Identify assumptions for causal effect estimation in the RD setting
Be able to address endogeneity problems
Construct linear models for time series data and apply the Box-Jenkins procedure
Be able to derive asymptotic distribution of estimators when the standard regularity conditions do not hold
Explain main notions of econometrics.
Explain specifics of working with time series data.

Course Contents

Introduction to Econometrics
The Linear Regression Model
Instrumental Variables and 2SLS
Panel Data Models
Other Common Research Designs
Review of main characteristics of time series
Nonstationary time series. Spurious regressions
Unit roots and tests for stationarity. Structural breaks. ARIMA models. Forecasting
Volatility modelling
Vector autoregressive models
Discrete choice models
Static and dynamic panel data
Optional topics

Assessment Elements

written final exam (Part II)
The lowest threshold for a passing grade on the 100-point scale is 35.
Problem sets I
Problem sets II
midterm test (part II)
The lowest threshold for a passing grade on the 100-point scale is 35.
Midterm test (Part I)
Written exam (part I)
The lowest threshold for a passing grade on the 100-point scale is 35
Homework Assignments

Interim Assessment

2024/2025 2nd module
0.16 * Homework Assignments + 0.29 * Midterm test (Part I) + 0.55 * Written exam (part I)
2024/2025 4th module
0.1 * Problem sets I + 0.1 * Problem sets II + 0.4 * midterm test (part II) + 0.4 * written final exam (Part II)

Bibliography

Recommended Core Bibliography

Analysis of financial time series, Tsay, R. S., 2005
Verbeek, M. (2004). A Guide to Modern Econometrics (Vol. 2nd ed). Southern Gate, Chichester, West Sussex, England: John Wiley and Sons, Inc. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=108185
Wooldridge, J. M. . (DE-588)131680463, (DE-576)298669293. (2006). Introductory econometrics : a modern approach / Jeffrey M. Wooldridge. Mason, Ohio [u.a.]: Thomson/South-Western. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edswao&AN=edswao.250894459

Recommended Additional Bibliography

Cameron, A. C., & Trivedi, P. K. (2005). Microeconometrics : Methods and Applications. New York, NY: Cambridge University Press. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=138992
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
Greene, W. H. (2015). Econometric analysis. Slovenia, Europe: Prentice-Hall International. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.1BF5A5CA
Jeffrey M Wooldridge. (2010). Econometric Analysis of Cross Section and Panel Data. The MIT Press. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsrep&AN=edsrep.b.mtp.titles.0262232588
Morgan, S. L., & Winship, C. (2007). Counterfactuals and Causal Inference : Methods and Principles for Social Research. New York: Cambridge University Press. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=206937
Peter Kennedy. (2003). A Guide to Econometrics, 5th Edition. The MIT Press. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsrep&AN=edsrep.b.mtp.titles.026261183x
Ruud, P. A. (2000). An Introduction to Classical Econometric Theory. Oxford University Press. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsrep&AN=edsrep.b.oxp.obooks.9780195111644
Tsay, R. S. (2002). Analysis of Financial Time Series : Financial Econometrics. New York: John Wiley & Sons, Inc. [US]. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=87319

Authors

BUDANOVA SOFYA ILINICHNA
KOTYRLO ELENA STANISLAVOVNA
SLONIMCZYK FABIAN KOZUEVICH

Master’s Programme 'Financial Economics'

Econometrics. Advanced Level