Uncertainty varies strongly over time, rising by 50% to 100% in recessions and by up to 200% after major economic and political shocks. This paper shows that higher uncertainty reduces the responsiveness of R&D to changes in business conditions - a “caution-effect” - making it more persistent over time. Thus, uncertainty will play a critical role in shaping the dynamics of R&D through the business cycle, and its response to technology policy. I also show that if firms are increasing their level of R&D then the effect of uncertainty will be negative, while if firms are reducing R&D then the effect of uncertainty will be positive.

This paper shows that, with (partial) irreversibility, higher uncertainty reduces the impact effect of demand shocks on investment.Uncertainty increases real option values making firms more cautious when investing or disinvesting.This is confirmed both numerically for a model with a rich mix of adjustment costs, time-varying uncertainty, and aggregation over investment decisions and time, and also empirically for a panel of manufacturing firms.These cautionary effects of uncertainty are large -going from the lower quartile to the upper quartile of the uncertainty distribution typically halves the first year investment response to demand shocks.This implies the responsiveness of firms to any given policy stimulus may be much lower in periods of high uncertainty, such as after major shocks like OPEC I and 9/11.

This paper investigates the relationship between product market competition and innovation. We find strong evidence of an inverted-U relationship using panel data. We develop a model where competition discourages laggard firms from innovating but encourages neck-and-neck firms to innovate. Together with the effect of competition on the equilibrium industry structure, these generate an inverted-U. Two additional predictions of the model-that the average technological distance between leaders and followers increases with competition, and that the inverted-U is steeper when industries are more neck-and-neck-are both supported by the data. © 2005 by the President and Fellows of Harvard College and the Massachusetts Institute of Technology.