Which investment model best fits firm-level data? To answer this question we estimate alternative models using Compustat data. Surprisingly, the two best-performing specifications are based on Hayashi's (1982) model. This model's foremost implication, that Q is a sufficient statistic for determining a firm's investment decision, has been often rejected because cash-flow and lagged-investment effects are present in investment regressions. However, we find that these regression results are quite fragile and ineffectual for evaluating model performance. So, forget what investment regressions tell you. Models based on Hayashi (1982) provide a very good description of investment behavior at the firm level.
as well as conference and seminar participants at many places for helpful comments about earlier version of this project. All errors are our own. We thank Xian Jiang and Vytautas Valaitis for excellent research assistance. Financial support from the Fondation HEC Montréal (Vincent) and the National Science Foundation under NSF grant No. SES-1758426 (Kehrig) are gratefully acknowledged. Any opinions and conclusions expressed herein are those of the authors and do not necessarily represent the views of the U.S. Census Bureau or the National Bureau of Economic Research. All results have been reviewed to ensure that no confidential information is disclosed. NBER working papers are circulated for discussion and comment purposes. They have not been peer-reviewed or been subject to the review by the NBER Board of Directors that accompanies official NBER publications.
The best predictor of current investment at the firm level is lagged investment. This lagged-investment effect is empirically more important than the cash-flow and Q effects combined. We show that the specification of investment adjustment costs proposed by Christiano, Eichenbaum and Evans (2005) predicts the presence of a lagged-investment effect and that a generalized version of their model is consistent with the behavior of firm-level data from Compustat.
The labor share in U.S. manufacturing declined from 61% in 1967 to 41% in 2012. The labor share of the typical U.S. manufacturing establishment, in contrast, rose by over 3 percentage points during the same period. Using micro-level data, we document five salient facts: (i) since the 1980s, there has been a dramatic reallocation of value added toward the lower end of the labor share distribution; (ii) this aggregate reallocation is not due to entry/exit, to “superstars” growing faster, or to large establishments lowering their labor shares, but is instead due to units whose labor share fell as they grew in size; (iii) low labor share (LL) establishments benefit from high revenue labor productivity, not low wages; (iv) they also enjoy a product price premium relative to their peers; and (v) they have only temporarily lower labor shares that rebound after five to eight years. This transient pattern has become more pronounced over time, and the dynamics of value added and employment are increasingly disconnected. Taken together, we interpret these facts as pointing to a significant role for demand-side forces.
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