Estimating Aggregate Autoregressive Processes When Only Macro Data are Available
22 Pages Posted: 12 Jul 2014 Last revised: 9 Feb 2016
Date Written: July 1, 2014
The aggregation of individual random AR(1) models generally leads to an AR(∞∞) process. We provide two consistent estimators of aggregate dynamics based on either a parametric regression or a minimum distance approach for use when only macro data are available. Notably, both estimators allow us to recover some moments of the cross-sectional distribution of the autoregressive parameter. Both estimators perform very well in our Monte-Carlo experiment, even with finite samples.
Keywords: Autoregressive process, Aggregation, Heterogeneity
JEL Classification: C2, C13
Suggested Citation: Suggested Citation