Empirical Macroeconomics


This course provides a non-systematic account of a range of research methods in empirical macroeconomics. It is intended as an apprenticeship to students interested in working in research departments. The course concentrates on the replication of existing and validated methods with a focus on causality and identification in macroeconomics. It covers a wide range of methodologies and requires some preliminary knowledge in time-series. The availability of computer codes and programs complements the practical angle of the course.

General characterization





Responsible teacher

Francesco Franco


Weekly - Available soon

Total - Available soon

Teaching language





Sims Cristopher A., Statistical Modeling of Monetary Policy and its Effects, Nobel Lecture 2011.

James D. Hamilton Time Series Analysis 1994 Princeton University Press.

Sims, Christopher A. 1980. Macroeconomics and Reality. Econometrica. January, 48:1, pp. 1– 48.

The Dynamic Effects of Aggregate Demand and Supply Disturbances Olivier Jean Blanchard and Danny Quah. The American Economic Review , Vol. 79, No. 4 (Sep., 1989), pp. 655-673.

James H. Stock, Dynamic Factor Models . Oxford Handbook of Economic Forecasting, Michael P. Clements and David F. Hendry (eds), Oxford University Press. 2011.

Lippi, Marco and Lucrezia Reichlin. The Dynamic Effects of Aggregate Demand and Supply Disturbances: Comment. American Economic Review 83(3), 644-652.

Fernández-Villaverde, Jesús, Juan F. Rubio-Ramírez, Thomas J. Sargent and Mark W. Watson. 2007. ABCs (and Ds) of Understanding VARs." American Economic Review, 97(3):1021-1026.

Bernanke, Ben, Jean Boivin, and Piotr Eliasz. 2005. Measuring the Effects of Monetary Policy: A Factor-Augmented Vector Autoregressive (FAVAR) Approach. Quarterly Journal of Economics 120(1), 387-422.

Blanchard, Olivier J., Jean-Paul L'Huillier and Guido Lorenzoni. 2013. News, Noise, and Fluctuations: An Empirical Exploration. American Economic Review, 103(7):3045-70.


Web site with codes and notes.

Teaching method

The course presents three key papers on each part and the students reproduce the results  of the papers during the course. This approach implies that the students must not only understand but also practically implement the methods of each part. The papers are integrated with a set of class notes and codes to reproduce the papers.

Evaluation method

The Final Exam is mandatory and covers the entire span of the course. Its weight in the final grade is 55%. The remainder of the evaluation consists of class participation, 5%, and three problem sets, 60%, one on each of the parts. I know it sums to 120…

Subject matter

The course is divided in three parts. The first part presents the standard methods based on structural VAR (SVAR) to identify fundamental shocks that drive the economy at an aggregate level. For example we are interested in identifying the effects of a monetary policy (fiscal policy, technology) shock. The second part presents the possibility for the economy to be driven by non-fundamental shocks which are not recoverable through standard SVAR methods. For example shocks that represent expectations of economic agents (think of the announcement of a future change in taxation that has not yet occurred). The third part is more advanced and more exploratory and presents methods to identify shocks that are not fully observed by economic agents. For example shocks that arise when agents are uncertain if the macroeconomy is driven by a new fundamental productivity or a temporary event.


Programs where the course is taught: