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Explaining Investment Dynamics in U.S. Manufacturing: A Generalized (S, s) Approach

Econometrica 1999 67(4), 783-826 open access
In this paper we derive a model of aggregate investment that builds from the lumpy microeconomic behavior of firms facing stochastic fixed adjustment costs. Instead of the standard sharp (S,s) bands, firms' adjustment policies take the form of a probability of adjustment (adjustment hazard) that responds smoothly to changes in firms' capacity gap. The model has appealing aggregation properties, and yields nonlinear aggregate time series processes. The passivity of normal times is, occasionally, more than offset by the brisk response to large accumulated shocks. Using within and out-of-sample criteria, we find that the model performs substantially better than the standard linear models of investment for postwar sectoral U.S. manufacturing equipment and structures investment data.

Dynamic (S, s) Economies

Econometrica 1991 59(6), 1659 open access
In this paper we provide a framework to study the aggregate dynamic behavior of an economy where individual units follow (S, s) policies. We characterize structural and stochastic heterogeneities that ensure convergence of the economy's aggregate to that of its frictionless counterpart, determine the speed at which convergence takes place, and describe the transitional dynamics of this economy. In particular, we consider a dynamic economy where agents differ in their initial positions within their bands and face both stochastic and structural heterogeneity; where the former refers to the presence of (unit specific) idiosyncratic shocks, and the latter to differences in the widths of units' (S, s) bands and their response to aggregate shocks. We study the evolution of the economy's aggregate and the evolution of the difference between this aggregate and that of an economy without macroeconomic friction, where the latter pertains to a situation where individual units adjust with no delay to all shocks. We also examine the sensitivity of this difference to common shocks. For example, in the retail inventory problem the aggregate deviation and sensitivity to common shocks correspond to the aggregate inventory level and its sensitivity to aggregate demand shocks, respectively.