We analyze the job matching process for skilled labor using an extensive panel dataset of naval officer careers during the Second Industrial Revolution. We find strong separation effects for officers with accumulated skills in technology-focused work and/or those with formal training as...

This paper explores the roles of capital- and technology-skill complementarities in labor allocation decisions within the U.S. Navy. During the latter 19th century the ocer corps was highly specialized, and was split between groups of line and sta ocers. This was also a time of dramatic...

This paper explores the role of human capital on earnings and other measures of job performance during the late 19th century. During this time, U.S. Naval ocers belonged either to a regular or an engineer corps and had tasks assigned to their specialized training and experience. To test for the...

This paper presents a model of a developing economy that endogenizes both technological biases and demographic trends. As knowledge diffuses from foreign R&D-producing regions, potential innovators decide which technologies to develop after considering available factors of production, and...

Over the past half-century there have been over three hundred instances of nation building initiatives, episodes where countries jointly give military and economic aid to a country embroiled in conflict. Despite the prevalence and expense of this foreign policy, little research has explored the...

Technological change was unskilled-labor-biased during the early Industrial Revolution of the late eighteenth and early nineteenth centuries, but is skill-biased today. This fact is not embedded in extant unified growth models. We develop a model of the transition to sustained economic growth...

Technological change was unskilled-labor-biased during the early Industrial Revolution, but is skill-biased today. This is not embedded in extant unified growth models. We develop a model which can endogenously account for these facts, where factor bias reflects profit-maximizing decisions by...