By Russell Cooper, John Haltiwanger and Jonathan Willis
This paper studies capital adjustment at the establishment level. Our goal is to characterize capital adjustment costs, which are important for understanding both the dynamics of aggregate investment and the impact of various policies on capital accumulation. Our estimation strategy searches for parameters that minimize ex post errors in an Euler equation. This strategy is quite common in models for which adjustment occurs in each period. Here, we extend that logic to the estimation of parameters of dynamic optimization problems in which non-convexities lead to extended periods of investment inactivity. In doing so, we create a method to take into account censored observations stemming from intermittent investment. This methodology allows us to take the structural model directly to the data, avoiding time-consuming simulation based methods. To study the effectiveness of this methodology, we first undertake several Monte Carlo exercises using data generated by the structural model. We then estimate capital adjustment costs for U.S. manufacturing establishments in two sectors.
Capital adjustement costs (and often other adjustment costs) are an important ingredient of many business cycle models. Yet, we have very poor estimates of how important they are. Typically, they are calibrated such that some measure of volatility is matched. This paper takes Euler equation estimation seriously and develops a method to estimate from micro data capital adjustment costs, in particular taking into account the irreversability of investment.