Missing aggregate dynamics: on the slow convergence of lumpy adjustment models

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 slowand 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 bia.