NBER Working Papers by Nicolas Vincent

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.

Do prices respond to macro shocks? Does the mere presence of international frontiers hinder trade? We revisit these questions by studying a dataset of online book prices for a number of US and Canadian retailers. We believe our dataset is well suited to this task for a number of reasons: (1) data for multiple retailers are available; (2) the products sold are identical across retailers; (3) the sample spans a period of large fluctuations in the bilateral exchange rate; (4) the nature of the industry is such that physical distance is irrelevant beyond shipping costs which are observable; (5) nominal frictions in the form of menu costs are arguably minimal; and (6) proxies for sales are available for most retailers. Given the unique nature of our dataset, the first objective of the paper is ...

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.