Estimating aggregate autoregressive processes when only macro data are available

Autor:	Eric Jondeau, Florian Pelgrin
Rok vydání:	2014
Předmět:	Economics and Econometrics Distribution (mathematics) Autoregressive model Aggregate (data warehouse) Minimum distance Econometrics Estimator Macro Finance Regression Parametric statistics Mathematics
Zdroj:	Economics Letters. 124:341-347
ISSN:	0165-1765
DOI:	10.1016/j.econlet.2014.06.012
Popis:	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.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::cbc28301efae0dd547cd08e688176b7f https://doi.org/10.1016/j.econlet.2014.06.012 Zobrazit plný text záznamu Full Text from ScienceDirect