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Macroeconometrics

  • Teacher(s): J.Renne
  • Course given in: English
  • ECTS Credits: 6 credits
  • Schedule: Spring Semester 2018-2019, 4.0h. course (weekly average)
  •  séances
  • site web du cours course website
  • Related programme: Master of Science (MSc) in Economics

 

Objectives

This course proposes an introduction to time series analysis. Time series constitute a prevalent data type that arises in several disciplines, notably in macroeconomics and finance. The modelling of time series is crucial for many purposes, including forecasting, the understanding of macroeconomic mechanisms and risk assessment.

The theoretical presentation of standard and more advanced modelling tools will be complemented with laboratory sessions. The latter will in particular bring students to implement time series tools on real data.

Contents

The notions covered by the course are the following:

A- Modelling of univariate processes:

  • ARMA processes: presentation, estimation and forecasting.
  • Stochastic-volatility models (ARCH and GARCH models): presentation, estimation and forecasting.

B- Modelling of multivariate processes:

  • Vector autoregressive models (VAR).
  • Derivation of impulse-response functions, which are key tools in macroeconomic analysis. The issue of the structural-shock identification will notably be explored.
  • Cointegration issues.

C- If time allows, regime-switching models will be studied.

Laboratory sessions will illustrate the preceding items. Students will learn and use the R software.

References

* Gourieroux, C., and A. Monfort (1995), Statistics and Econometrics Models, volumes 1 and 2, Cambridge University Press.

* Hamilton, J. (1994), Time Series Analysis, Princeton University Press.

* Stock, J., and Watson, M. (2003), Introduction to Econometrics, Addison-Wesley Series in Economics.

Pre-requisites

Introductory econometrics and statistics.

Evaluation

First attempt

Exam:
Written 2h00 hours
Documentation:
Allowed with restrictions
Calculator:
Not allowed
Evaluation:

The final grade is an equally-weighted average of two grades:

  1. The first grade is based on a 2-hour paper-and-pen exam. For this exam, an A4 sheet (home-made) with all pertinent information is allowed.
  2. The second grade is based on a project making use of real data. This project is carried out by groups of up to three individuals. Students will be encouraged to begin their project relatively early in the semester (mid-term) to benefit from a few laboratory sessions that will be dedicated to the projects. The groups will present their results during the last sessions. A report (pdf file) as well as the codes and data file will be sent to the professor one week ahead of the presentation.

Retake

Exam:
Written 2h00 hours
Documentation:
Allowed with restrictions
Calculator:
Not allowed
Evaluation:

  • In the re-take session, the final grade will be equal to the grade of the re-take exam only, i.e. the previous grades (project and end-of-semester exam) do not affect the final re-trake grade.
  • An A4 sheet (home-made) with all pertinent information is allowed.



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