Course Description
The characteristics of macroeconomic and financial time series data. Discussion of stationarity and non-stationarity as they relate to economic time series. Linear models for stationary economic time series: autoregressive moving average (ARMA) models; vector autoregressive (VAR) models. Linear models for nonstationary data: deterministic and stochastic trends; cointegration. Methods for capturing volatility of financial time series such as autoregressive conditional heteroscedasticity (ARCH) models. Generalized Method of Moments estimation of nonlinear dynamic models.
Spring 2026
Instructors
Meeting Patterns
Classes Start:
January 12, 2026
Classes End:
April 28, 2026
Location:
00143 D S Weaver Labs
Class Days:
M W
Class Start Time:
11:45am
Class End Time:
1:00pm
Class Type:
Lecture
Credits:
3.00
Restrictions:
Restricted to students in Graduate Economics programs
