This paper studies the nature of capital adjustment at the plant level. We use an indirect inference procedure to estimate the structural parameters of a rich specification of capital adjustment costs. In effect, the parameters are optimally chosen to reproduce a set of moments that capture the non-linear relationship between investment and profitability found in plant-level data. Our findings indicate that a model, which mixes both convex and non-convex adjustment costs, fits the data best.1. Holt et al. (1960) found a quadratic specification of adjustment costs to be a good approximation of hiring and lay-off costs, overtime costs, inventory costs, and machine set-up costs in selected manufacturing industries. These components of adjustment costs for changing the level of production are relevant here but are by no means the only relevant costs. In terms of changes in the level of capital services, Peck (1974) studies investment in turbo-generator sets for a panel of 15 electric utility firms and found that "The investments in turbogenerator sets undertaken by any firm took place at discrete and often widely dispersed points of time". In their study of investment in large scale computer systems, Ito et al. (1999) also find evidence of lumpy investment. Their analysis of the costs of adjusting the stock of computer 611 612 REVIEW OF ECONOMIC STUDIES Despite this perspective from the industry case studies, the workhorse model of the investment literature has been a standard neoclassical model with convex costs (often approximated to be quadratic) of adjustment. This model has not performed that well even at the aggregate level (see Caballero, 1999), but the recent development of longitudinal establishment databases has raised even more questions about the standard convex cost model.An alternative approach, highlighted in the work of Abel and Eberly (1994, 1996), Doms and Dunne (1994), Haltiwanger (1995), andPower (1999), argues that non-convexities and irreversibilities play a central role in the investment process. The primary basis for this view, reviewed in detail in the following, is plant-level evidence of a non-linear relationship between investment and measures of fundamentals, including investment bursts (spikes) as well as periods of inaction.One limitation of this recent empirical literature is that it has focused primarily on reducedform implications of non-convex vs. convex models. The results that emerge reject the reducedform implications of a pure convex model and are consistent with the presence of non-convexities. The reduced-form nature of the results have left us with several important, unresolved questions: what is the nature of the capital adjustment process at the micro-level? Does the micro-evidence support the presence of both convex and non-convex components of adjustment costs as might be expected based upon the limited number of industry case studies? More specifically, what are the structural estimates of the convex and non-convex components of adjustment costs that are consistent with ...

No abstract

No abstract

This paper explores investment fluctuations due to discrete changes in a plant's capital stock. The resulting aggregate investment dynamics are surprisingly rich, reflecting the interaction between a replacement cycle, the cross-sectional distribution of the age of the capital stock, and an aggregate shock. Using plant-level data, lumpy investment is procyclical and more likely for older capital. Further, the predicted path of aggregate investment that neglects vintage effects tracks actual aggregate investment reasonably well. However, ignoring fluctuations in the cross-sectional distribution of investment vintages can yield predictable nontrivial errors in forecasting changes in aggregate investment.