MISSING AGGREGATE DYNAMICS: ON THE SLOW CONVERGENCE OF LUMPY ADJUSTMENT MODELS

When applying conventional VAR procedures to aggregate variables with lumpy micro adjust-ment, estimated persistence of shocks is biased downwards. This is relevant for non-, semi- and structural models in macroeconomics. The extent to which persistence is underestimated 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 aggregate data as well. Paradoxically, while idiosyn-cratic 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 find that the difference in the speed with which inflation responds to sectoral and aggre-gate shocks disappears once we correct for the missing persistence bias