Teacher(s)
Language
English
Main themes
In the first part of the course, we shall study the main behavioral equations of a standard macroeconomic model: aggregate supply and factor demands, consumption (and saving), external trade, wages and prices. The emphasis will be on the eco-nomic foundations of the econometric specifications (including the global coherence of the model and its characteristics on a steady state growth path), the interpretation and the policy implications of the results.
Next, we shall select and discuss some important issues in (applied) macroeconomics, integrating case studies and pub-lished papers.
Learning outcomes
At the end of this learning unit, the student is able to : | |
| 1 | The course builds on the core course in macroeconomics. It provides an experience in the modeling of a small open econ-omy and therefore should yield a better understanding of its functioning, a better appreciation of the magnitude of key ratios and elasticities and their implications for economic policy. |
Content
The course will explore topics in applied macroeconomics, with emphasis on the intersection between the empirical analysis and the theory. The objective of the course is to develop an understanding of the connection between the economic theory and real-world policy issues, an ability to apply the empirical methods to critically analyze the macroeconomic environment surrounding the policy decisions.
The course will cover the estimation and identification of vector autoregressions (VARs) and local projections, focusing specifically on how these models are applied to understand the macroeconomic and financial impact of monetary and fiscal policies. I will also provide a brief introduction to Bayesian time-series econometrics.
If time permits, we will also discuss the use of structural macro models policy analysis and forecasting. We will select and discuss some important issues in (applied) macroeconomics, integrating case studies and published papers.
The course will cover the estimation and identification of vector autoregressions (VARs) and local projections, focusing specifically on how these models are applied to understand the macroeconomic and financial impact of monetary and fiscal policies. I will also provide a brief introduction to Bayesian time-series econometrics.
If time permits, we will also discuss the use of structural macro models policy analysis and forecasting. We will select and discuss some important issues in (applied) macroeconomics, integrating case studies and published papers.
Teaching methods
The course is taught in person, if possible. (Subject to changes due to the covid situation). Students will receive home assignments and will work individually and/or in groups.Students are supposed to be able to use an econometric software (e.g. Matlab or R) and some meetings may take place in the computing room.
Evaluation methods
The grade will be based on the home assignments (40%) and a written exam at the end of the term (60%).
Online resources
See Moodle https://moodle.uclouvain.be/?redirect=0
Bibliography
There is no required textbook. However, I plan to draw material from the following books and papers:
Kilian, Lutz and Lütkepohl, Helmut, Structural Vector Autoregressive Analysis (as of July 2018, chapters can be downloaded freely on Kilian’s webpage: http://www-personal.umich.edu/~lkilian/book.html)
Ramey, Valerie, Macroeconomic Shocks and Their Propagation 2016 Handbook of Macroeconomics.
Leeper, Eric and Sims, Christopher A., and Zha, Tao, What Does Monetary Policy Do? 1996 Brookings Papers on Economic Activity, 2, 1-78
Del Negro, M. and F. Schorfheide (2013) “DSGE Model-Based Forecasting” Handbook of Economic Forecasting, Volume 2, Part A, 2013, Pages 57-140
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.
Forni and Gambetti “Sufficient information in structural VARs” Journal of Monetary Economics, Volume 66, September 2014, Pages 124-136
Jordà, Ò. (2005). Estimation and Inference of Impulse Responses by Local Projections. American Economic Review, 95 (1), 161–182.
Uhlig, H. 2005. What are the Effects of Monetary Policy on Output? Results from an Agnostic Identification Procedure. Journal of Monetary Economics 52, 381-419.
Silvia Miranda-Agrippino, Giovanni Ricco, Bayesian Vector Autoregressions: Estimation, Oxford Research Encyclopedia of Economics and Finance (forthcoming), Oxford University Press. doi:10.1093/acrefore/9780190625979.013.164
Silvia Miranda-Agrippino, Giovanni Ricco, Bayesian Vector Autoregressions: Applications, Oxford Research Encyclopedia of Economics and Finance (forthcoming), Oxford University Press. doi:10.1093/acrefore/9780190625979.013.478
Kilian, Lutz and Lütkepohl, Helmut, Structural Vector Autoregressive Analysis (as of July 2018, chapters can be downloaded freely on Kilian’s webpage: http://www-personal.umich.edu/~lkilian/book.html)
Ramey, Valerie, Macroeconomic Shocks and Their Propagation 2016 Handbook of Macroeconomics.
Leeper, Eric and Sims, Christopher A., and Zha, Tao, What Does Monetary Policy Do? 1996 Brookings Papers on Economic Activity, 2, 1-78
Del Negro, M. and F. Schorfheide (2013) “DSGE Model-Based Forecasting” Handbook of Economic Forecasting, Volume 2, Part A, 2013, Pages 57-140
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.
Forni and Gambetti “Sufficient information in structural VARs” Journal of Monetary Economics, Volume 66, September 2014, Pages 124-136
Jordà, Ò. (2005). Estimation and Inference of Impulse Responses by Local Projections. American Economic Review, 95 (1), 161–182.
Uhlig, H. 2005. What are the Effects of Monetary Policy on Output? Results from an Agnostic Identification Procedure. Journal of Monetary Economics 52, 381-419.
Silvia Miranda-Agrippino, Giovanni Ricco, Bayesian Vector Autoregressions: Estimation, Oxford Research Encyclopedia of Economics and Finance (forthcoming), Oxford University Press. doi:10.1093/acrefore/9780190625979.013.164
Silvia Miranda-Agrippino, Giovanni Ricco, Bayesian Vector Autoregressions: Applications, Oxford Research Encyclopedia of Economics and Finance (forthcoming), Oxford University Press. doi:10.1093/acrefore/9780190625979.013.478
Faculty or entity
