Global Innovation Races,Offshoring and Wage Inequality

In the 1970s and 1980s the US position as the global technological leader was increasingly challenged by Japan and Europe. In those years the US skill premium and residual wage inequality increased substantially. This paper presents a two‐region, quality‐ladder growth model where the lagging economy progressively catches up with the leader. As the innovation gap closes, the advanced country experiences fiercer foreign technological competition that forces its firms to innovate more. Faster technical change increases the skill premium and residual inequality. Offshoring production and innovation plays a key role in shaping the link between international competition and inequality.     

INTERNATIONAL COMPETITION AND U.S. R&D SUBSIDIES: A QUANTITATIVE WELFARE ANALYSIS*

In the early 1970s U.S. firms were the uncontested world leaders in R&D investment in most manufacturing sectors. Later, led by Japan and Europe, foreign firms began to challenge American R&D leadership in many sectors of the economy. This period of increasing technological competition is contemporaneous with a substantial increase in U.S. R&D subsidies. What is the effect of the observed increase in international competition on U.S. welfare? How does foreign competition affect the optimal R&D subsidy in the United States, and, consequently, how far is this from the subsidy observed in the data? This article addresses these questions in a two‐country quality ladder growth model.     

Demand-Driven Technical Change and Productivity Growth: Theory and Evidence from the Energy Policy Act

We present novel evidence on the effect of market size on technology adoption and productivity. Our tests exploit a natural experiment in the U.S. corn industry where changes to national energy policy created exogenous increases in demand. Difference-in-difference estimates show that the demand shock caused technical change as corn producers adopted higher quality seeds which in turn raised productivity by 7%. We develop a simple model that formalizes the mechanisms underlying our results.