| General Description
The third EABCN training school was five-day
course on “Topics in applied time series and
forecasting”.
Professor Mark W. Watson,
from Princeton University, instructed the course.
The course consisted of five days lectures
(approximately 6 hours per day). The objective was to introduce
the students to the topic and enable them to apply the methods
to empirical data. For each topic, there have been lecturing and
applications on the computer. Class notes and codes will be made
available before the beginning of the course.
The following topics were covered.
1. Business cycle descriptive statistics in
the time and frequency domain.
2. Detecting and modeling parameter Instability
3. Unit Roots in Autoregressions
4. Filtering, State Space Models and the Kalman Filter
5. Forecasting using a large number of variables
Course Material
About the instructor
Mark Watson is a Professor of Economics and
Public Affairs at Princeton University and a research associate
at the National Bureau of Economic Research. His research focuses
on time-series econometrics, empirical macroeconomics, and macroeconomic
forecasting. He has published over sixty scientific articles in
these areas and is the author (with James Stock) of Introduction
to Econometrics, a leading undergraduate textbook. Watson has
served on the editorial board of several journals including the
American Economic Review, Applied Econometrics, Econometrica,
the Journal of Business and Economic Statistics, the Journal of
Monetary Economics, and Macroeconomic Dynamics. He has served
as a consultant for the Federal Reserve Banks of Chicago and Richmond.
Before coming to Princeton, Watson served on the economics faculty
at Harvard and Northwestern. Watson did his undergraduate work
at Pierce Junior College and California State University at Northridge,
and completed his Ph.D. at the University of California at San
Diego. |
