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

David Berger, Ricardo J. Caballero, Eduardo Engel

NBER Working Paper No. 9898
Issued in August 2003, Revised in June 2017
NBER Program(s):Economic Fluctuations and Growth, Labor Studies, Productivity, Innovation, and Entrepreneurship

The estimated persistence of macro aggregates involving lumpy microeconomic adjustment is biased downward when inferred from VAR estimates. The extent of this “missing persistence bias” decreases with the level of aggregation, yet convergence is very slow. Paradoxically, while idiosyncratic 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 a method to estimate the true speed of adjustment and illustrate its effectiveness via simulations and applications to real data.

The missing persistence bias is relevant for macroeconomists on many grounds. First, when calibrating or estimating models via simulation based methods, macroeconomists should pay attention to the number of agents used in simulations for otherwise they are likely to obtain systematic biases in their parameter estimates. Second, results purporting to find persistence measures that vary systematically with levels of aggregation should be examined with care since the differential speeds may disappear when using estimation methods robust to the missing persistence bias. To illustrate the latter, we show 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.

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Document Object Identifier (DOI): 10.3386/w9898

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