Forecasting
This course
studies methods for constructing forecasts, with applications in
macroeconomics. The emphasis is on time series statistical forecasting tools
and their application to practical forecasting. The approaches covered span single
equation time series to large, complex, simultaneous equations systems.
Different measures to assess the forecasting accuracy of these approaches are
addressed. A discussion of these approaches and their relevance for policy
recommendations is also covered.
Textbook:
Elements
of Forecasting,
Francis X. Diebold (South-Western Cengage Learning)
Topics:
·
first week: Modeling and forecasting trend. Lecture Slides
o
Principles
to forecasting
o
Modeling,
estimating and forecasting trend
o
Selecting
forecasting models
·
second week: Forecasting cycles . Lecture Slides
o
Modeling
cycles: MA, AR, ARMA
o
Optimal
forecast
o
Forecasting
Moving Average Process
·
third week:
Forecasting with large information set. Lecture
Slides
o
Dynamic
Factor Model
o
Bridge
equations
o
Combining
forecast
·
forth week:
Real Time data analysis . Lecture Slides
Problem Sets:
·
Problem Set 3 (Data; General Notes)