ENSAE Paris - École d'ingénieurs pour l'économie, la data science, la finance et l'actuariat

Applied macroeconometrics


The aim of this course is firstly to introduce a set of statistical and modelling techniques used in constructing and estimating macroeconomic models, and secondly to describe the conditions for their use in both empirical macroeconomic research and an operational forecasting context. The technical aspects of econometrics, generally tackled in other courses in the second or third year, will be briefly demonstrated.

After an introduction looking at the history and varying aims of macroeconometric modelling (testing economic theories, forecasting, simulating economic policies), the different types of approach and methods will be presented. They will be illustrated with examples from the fields of economic policy and forecasting.



  1. Introduction
  2. Descriptive statistical models: VAR and VECM models, the "General to Specific" approach- Estimating techniques. Specification tests. Forecasting. Causality tests, response functions.
  3. "Traditional" structural macroeconometric models- Accounting framework, organisation of equations and equation blocks, usual specifications of important equations. Resolution analysis methods and properties of the models. Use as variant and for forecasting. Illustrations.
  4. Rational anticipation models and DSGE model- Resolution methods, estimation techniques (GMM, ML, indirect inference, Bayesian approach). Properties. Examples of use (new Phillips curve, monetary policy rules and shock).


De Jong  et C. Dave (2007) Structural macroeconometrics, Princeton University Press Canova F. (2005)

Methods for Applied Macroeconomic Research, Princeton University Press Hamilton J. (1994)

Time Series Analysis, Princeton University Press