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Missing Aggregate Dynamics: On the Slow Convergence of Lumpy Adjustment Models

David Berger, Ricardo Caballero () and Eduardo Engel

Working Papers from University of Chile, Department of Economics

Abstract: When microeconomic adjustment is lumpy, the VAR-estimated persistence of the corresponding aggregated variable is downward biased. The extent of this bias decreases with the level of aggregation, yet convergence is very slow and the bias is likely to be present for sectoral data in general and, in many cases, for fully aggregated data as well. Paradoxically, while idiosyncratic productivity and demand shocks smooth away microeconomic non-convexities and are often used to justify approximating aggregate dynamics with linear models, their presence exacerbates the bias. We propose procedures to correct for the bias and provide various applications. In one of them, we account for the persistence-gap behind Bils and Klenow’s (2004) rejection of the Calvo model. In another, we find that the difference in the speed with which inflation responds to sectoral and aggregate shocks (Boivin et al 2009; Mackoviak et al 2009) disappears once we correct for the missing persistence bias.

Pages: 44 pages
Date: 2015-11
New Economics Papers: this item is included in nep-mac
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Citations: View citations in EconPapers (4)

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Related works:
Working Paper: Missing aggregate dynamics: on the slow convergence of lumpy adjustment models (2013) Downloads
Working Paper: Missing Aggregate Dynamics: On the Slow Convergence of Lumpy Adjustment Models (2008) Downloads
Working Paper: Missing Aggregate Dynamics: On the Slow Convergence of Lumpy Adjustment Models (2003) Downloads
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