Innovation and Industry Development: Lessons from the British Cotton Textile Industry During the U.S. Civil War

This dissertation uses the large shock to the British cotton textile industry in the 19th century, caused by the U.S. Civil War (1861-1865), in order to address three long-running questions about technological progress and industry development.;The first chapter investigates the theory of directed technical change. The leading theory of directed technical change, developed by Acemoglu (2002), offers two main predictions. First, when inputs are sufficiently substitutable, a change in relative input supplies will generate technical change directed towards the inputs which become more abundant. Second, if technical change is strongly directed towards the more abundant inputs, the relative price of these inputs will increase -- the strong induced-bias hypothesis. The chapter provides the first empirical test of these predictions. I extend the theory to a setting in which input quantities are endogenous and affected by international transport cost shocks, such as that caused by the war. Using detailed new patent data, I show that there was a burst of cotton textile innovation in Britain during the war directed towards taking advantage of one input---Indian cotton---which became relatively more abundant. Next, I show that the relative price of Indian cotton first declined and then rebounded, consistent with the strong induced-bias hypothesis. These results provide support for the theory. My extended model also predicts that technical change directed towards the more abundant input will be magnified by a higher elasticity of input supply. This may explain why inventors chose to focus on innovations for Indian cotton, rather than Brazilian or Egyptian cotton, since I find evidence that the elasticity of supply was higher for Indian cotton.;In the second chapter, I look at whether the stock of available knowledge about a particular type of technology can influence the rate of innovation in that technology. The answer to this question has significant implications for how we think about technological progress and economic growth. This chapter provides a theory which describes how the stock of knowledge can influence the innovation rate, which I call path dependence in innovation. The theory suggests that path dependence in innovation may occur at multiple levels of aggregation, such as specific types of technologies within an industry. This motivates an empirical exercise in which I search for path dependence at multiple technology levels. I introduce an empirical methodology that addresses two potential sources of bias in generating evidence of path dependence in innovation by using a temporary observable shock to innovation rates. My results provide no evidence of path dependence in innovation for cotton textile technologies. However, I do find suggestive evidence of path dependence in innovation for specific subsets of technologies within the cotton textile industry. This illustrates the importance of looking at multiple levels of aggregation when studying path dependence in innovation.;Chapter 3 provides causal evidence that inter-industry connections can influence the geographic location of economic activity. To do so, it compares the impact of the shock caused by the U.S. Civil War on towns in Lancashire County, the center of Britain's cotton textile industry, to towns in neighboring Yorkshire County, where wool textiles dominated. The results suggest that the shock reduced employment and employment growth in industries related to the cotton textile industry, in towns that were more severely impacted by the shock, relative to less affected towns. The impact still appears over two decades after the end of the U.S. Civil War. This suggests that temporary shocks, acting through inter-industry connections, can have long-term impacts on the distribution of industrial activity across locations. (Abstract shortened by UMI.)...