Macroeconometrics (Y1/E1, 5op)

NB1: This an advanced course primarily intended for major subject students of economics. It is possible for students of other faculties to apply for a study right for advanced studies, but the applicant must have a well-grounded reason for her/his application (for instance, post-graduate studies at another faculty of the University). Before applying, the student should have completed the intermediate studies in economics. Further information can be found here. Also, it is expected that the student has acquired the basic skills listed under ‘Prerequisites’ below.

Lecturer: Professor Markku Lanne, consultation hour Wednesdays 13 – 14 (office: B307).

Teaching assistants: Henri Nyberg (office: A310) and Matthijs Lof (office: A312)

Overview: The goal of the course is to provide an introduction to the methods of modern applied macroeconometrics. The different approaches currently used in applied work are reviewed, including the basics of the empirical dynamic stochastic general equilibrium models, but the main emphasis is on the analysis of vector autoregressive models. In particular, the identification of economic shocks by various methods and the use of the vector autoregressive framework in policy analysis are discussed.

Prerequisites: Basic knowledge of macroeconomics, econometrics and time series analysis (for example, Advanced Econometrics or the course in the analysis of stationary time series offered by the Department of Mathematics and Statistics, or equivalent) is assumed. JMulTi is the software package that will be used to demonstrate the methods in class, but any available computer program may be used for the assignments and the term paper. For the benefit of students with inadequate prerequisites, the basics of time series analysis and univariate time series models are reviewed at the beginning of the course.

Textbooks: The lectures will not directly follow any textbook, but the relevant parts of the following may be useful as supplementary reading. In addition, a number of relevant journal articles (to be listed below) will be discussed.

  • Favero (2001): Applied Macroeconometrics. Oxford University Press.
  • Hamilton (1994): Time Series Analysis. Princeton University Press.
  • Lütkepohl (2005): New Introduction to Multiple Time Series Analysis. Springer.
  • Lütkepohl & Krätzig (eds.) (2004): Applied Time Series Econometrics. Cambridge University Press.

Software: JMulTi is the software package used in the course. For most purposes other packages, such as Eviews, can also be used. While Eviews can only be used in the computer lab of the Department of Economics, JMulTi can be downloaded for free from

Lectures: 17.9. – 16.10.2009 Thursdays and Fridays 10 – 12, ECONOMICUM SH 1. In addition, the use of JMulTi software is demonstrated on Monday 21 September, 10 – 12 in the computer lab of the Department of Economics.
Lecture slides as well as links to supplementary material such as programs and data used in class will be posted here in advance. Skimming through the slides before the lecture is highly advisable, and you should have the printouts available in class.

Slides Data and Programs Supplemental Material
Slides 1 (added 9.9.) Calibration of an RBC Model, U.S. Consumption Vintages, Finnish GDP Series, Kydland & Prescott (1996)
Slides 2 (added 16.9.) U.S. Investment JMulTi Manual: Initial Analysis, Cecchetti & Debelle (2006)
Slides 3 (added 22.9.) PPP Data Set with description, U.S. Term Structure Data with description JMulTi Manual: VAR Analysis
Slides 4 (added 30.9.) Campbell & Shiller (1987)
Slides 5 (added 7.10.) Stock & Watson (2001)
Slides 6 (added 13.10.) German interest rate and inflation data JMulTi manual: VECM Analysis

Assignments and Exercise Sessions: There will be four homework assignments during the course, each consisting of a number of exercises. The assignments and the data sets will be posted here.

Assignment 1 (due 30.9.) West German Macrodata (Excercise 2), CPI Data (Exercise 3)
Assignment 2 (due 7.10.) West German Macrodata
Assignment 3 (due 14.10.) West German Macrodata
Assignment 4 (due 20.10.) PPP Data Set with description, U.S. Term Structure Data with description

Typically the exercises will involve small-scale empirical analyses employing methods presented in class, but there may be some analytical problems as well. In class, I will demonstrate the practical implementation of econometric methods with JMulTi, but you are free to use any software package for the assignments. There will be four exercise sessions: Thursdays 1.10., 8.10., 15.10. and Wednesday 21.10., 12 – 14 in the computer lab of the Department of Economics. For credit, the solution of the assignment should be uploaded to the BSCW area of the course (see below) by 1 p.m. on the day preceding the excercise session, and you must also be prepared to present your solution at the exercise session. The assignments are graded on a scale the from 0 to 5 (see Grading below). It is possible to revise the solutions to exercises submitted by each deadline; the grading is based on the final solutions resubmitted by Monday 2 November, 2009 (1 p.m.). The grading criteria are the following:

0 1 2 3 4 5
Less than 50% of the exercises done At least 50% of the exercises done showing good effort At least 50% of the exercises done and some solutions are very good At least 75% of the exercises done showing good effort or at least 50% of the exercises done and some solutions are excellent At least 90% of the exercises done showing good effort and the solutions are mostly very good At least 90% of the exercises done showing good effort and the solutions are mostly excellent

Tutorials: On Mondays 28.9., 5.10., 12.10. and 19.10, 10 – 12, Matthijs Lof will be in the computer lab of the Department of Economics to help with the assignments and the use of the JMulTi software package.

Timetable of Lectures and Other Sessions

Thursday 17 September, 10 – 12 Lecture 1 (ECONOMICUM SH 1)
Friday 18 September, 10 – 12 Lecture 2 (ECONOMICUM SH 1)
Monday 21 September, 10 – 12 JMulTi demo (COMPUTER LAB)
Thursday 24 September, 10 – 12 Lecture 3 (ECONOMICUM SH 1)
Friday 25 September, 10 – 12 Lecture 4 (ECONOMICUM SH 1)
Monday 28 September, 10 – 12 Tutorial 1 (COMPUTER LAB)
Thursday 1 October, 10 – 12 Lecture 5 (ECONOMICUM SH 1)
Thursday 1 October, 12 – 14 Exercise session 1 (COMPUTER LAB)
Friday 2 October, 10 – 12 Lecture 6 (ECONOMICUM SH 1)
Monday 5 October, 10 – 12 Tutorial 2 (COMPUTER LAB)
Thursday 8 October, 10 – 12 Lecture 7 (ECONOMICUM SH 1)
Thursday 8 October, 12 – 14 Exercise session 2 (COMPUTER LAB)
Friday 9 October, 10 – 12 Lecture 8 (ECONOMICUM SH 1)
Monday 12 October, 10 – 12 Tutorial 3 (COMPUTER LAB)
Thursday 15 October, 10 – 12 Lecture 9 (ECONOMICUM SH 1)
Thursday 15 October, 12 – 14 Exercise session 3 (COMPUTER LAB)
Friday 16 October, 10 – 12 Lecture 10 (ECONOMICUM SH 1)
Monday 19 October, 10 – 12 Tutorial 4 (COMPUTER LAB)
Wednesday 21 October, 12 – 14 Exercise session 4 (COMPUTER LAB)

Term Paper: 35% of the grade is based on a term paper (see below) that is an emprical research report written on a given topic, employing the methods covered in the course. The term paper should be returned by e-mail to Henri Nyberg by Monday 2 November, 2009 (1 p.m.).

Grading: The final grade of the course is computed as the weighted average of the grades of the final exam (45%), the term paper (35%) and the homework assignments (20%). All three parts are separately graded on a scale from 0 to 5, and in order to pass the course you must get at least 1 in each.

Exams: See the Study guide.

BSCW: All learning material will be made available through the BSCW (Basic Support for Cooperative Work) tool. The BSCW folder of the course can be found at For the access right to this folder, send an e-mail message containing your own e-mail address (of the form if you are a student at the University of Helsinki) to Henri Nyberg. Instructions on the BSCW are available at (in Finnish) and at (in English).

Tentative Outline

Depending on time constraints, the list of topics is subject to change. The material marked with an asterisk (*) is required reading for the exam (only the parts covered in class).

1. Introduction to Macroeconometrics

2. Review of Univariate ARIMA Processes

3. Vector Autoregression (VAR)

4. Cointegration and Vector Error Correction (VEC) Models

  • Hamilton, Chapters 18 – 20.
  • Lütkepohl, Chapters 6 – 8.
  • Lütkepohl & Krätzig, Chapter 3.

5. Structural VAR and VEC models

  • Lütkepohl, Chapter 9.
  • Lütkepohl & Krätzig, Chapter 4
  • Favero, Chapter 6.