Estimating Aggregate Autoregressive Processes When Only Macro Data are Available

Eric Jondeau and Florian Pelgrin
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Florian Pelgrin: EDHEC Business School and EDHEC Business School

No 14-43, Swiss Finance Institute Research Paper Series from Swiss Finance Institute

Abstract: The aggregation of individual random AR(1) models generally leads to an AR(infinity) 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 (search for similar items in EconPapers)
JEL-codes: C13 C2 (search for similar items in EconPapers)
Pages: 22 pages
Date: 2014-06
New Economics Papers: this item is included in nep-ecm and nep-ets
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http://ssrn.com/abstract=2464621 (application/pdf)

Related works:
Journal Article: Estimating aggregate autoregressive processes when only macro data are available (2014)
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Persistent link: https://EconPapers.repec.org/RePEc:chf:rpseri:rp1443

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