Estimating Aggregate Autoregressive Processes When Only Macro Data are Available

22 Pages Posted: 12 Jul 2014 Last revised: 9 Feb 2016

See all articles by Eric Jondeau

Eric Jondeau

University of Lausanne - Faculty of Business and Economics (HEC Lausanne); Swiss Finance Institute

Florian Pelgrin

EDHEC Business School; EDHEC Business School

Date Written: July 1, 2014

Abstract

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

Jondeau, Eric and Pelgrin, Florian, Estimating Aggregate Autoregressive Processes When Only Macro Data are Available (July 1, 2014). Economics Letters, Vol. 124, No. 3, 2014; Swiss Finance Institute Research Paper No. 14-43. Available at SSRN: https://ssrn.com/abstract=2464621 or http://dx.doi.org/10.2139/ssrn.2464621

Eric Jondeau (Contact Author)

University of Lausanne - Faculty of Business and Economics (HEC Lausanne) ( email )

Extranef 232
Lausanne, 1012
Switzerland
+41 21 692 33 49 (Phone)

HOME PAGE: http://www.hec.unil.ch/ejondeau/

Swiss Finance Institute

c/o University of Geneva
40, Bd du Pont-d'Arve
CH-1211 Geneva 4
Switzerland

Florian Pelgrin

EDHEC Business School ( email )

France
Switzerland

EDHEC Business School ( email )

58 rue du Port
Lille, 59046
France

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