Industry Clusters, Trade, and Growth Economists have long recognized that a central effect of trade is to change the set of industries in an economy. When industries are heterogeneous, either in their potential for productivity growth, or in their ability to generate spillovers that improve productivity in other industries, these changes will affect a country's growth rate. Simple observation, as well as recent empirical evidence, suggests that such heterogeneity exists to a significant degree. The goal of this project is to understand how trade affects growth through its affect on the composition of industries in an economy. Particular attention will be paid to the role of industry clusters, by which is meant groups of industries where each industry in the cluster has significant productivity spillovers to other cluster industries. The PI addresses this problem using both theoretical and empirical tools. The theoretical contribution is fairly well developed. The results suggest that trade may increase the growth rate of all trading economies, if it concentrates industries or strengthens clusters. Conversely, trade may decrease growth in all trading economies if it weakens industry clusters. These results are new and contradict previous studies, such as those by Young (1991) and Matsuyama (1992), who apply more restrictive and less realistic assumptions. An important implication is that the effect of trade on growth depends crucially on the initial set of industries in an economy and the pattern of industry clusters. The empirical portion of this project, which is still in its infancy, involves constructing a new data set describing the evolution of the economy of Lancashire County, England, from the Industrial Revolution to the present. Lancashire County, birthplace of the industrial revolution, is interesting as a clear case of successful trade-driven and cluster-based development. Another reason for choosing this case is the wealth of data available. These data will be used to illustrate the mechanisms described by the theory, and to test its predictions. Intellectual Merit The intellectual merit of this project rests on the importance of the question it addresses. As the world becomes more globalized the decisions countries make regarding trade policy will become more and more important. The recent experience of East Asia suggests that trade can be a powerful engine for growth, yet in other cases we see that trade need not lead to growth. The PI's work provides a new analytical framework for assessing the effects of trade and suggests how trade, technology, and industrial policies can be used to harness the power of trade to create growth. Furthermore, the results suggest that when trading partners coordinate to design proper policies, all trading partners can benefit. Broader Impacts The broader impacts of this work will be felt through its impact on trade policies, and related technology and industrial policies. With nearly every country involved in significant trading relationships, any knowledge that increases the ability of countries to enact trade policies that increase growth will have wide applicability. Once completed, the PI intends to disseminate the results both through academic publication and through channels focused on reaching policymakers.
This project studies the extent to which inter-industry spillovers between industries can influence the geographic location of economic activity. Previous research has suggested that there may be beneficial spillovers between certain industries, for example, if they share new knowledge or technology. The cluster of technology firms in Silicon Valley is one often cited example. However, there is currently little evidence on the causal role that these inter-industry connections may play in determining the geographic location of industries. This project studies the role of inter-industry connections by taking advantage of a large negative shock that struck the British economy in the 19th century. The shock was caused by the U.S. Civil War, which sharply reduced raw cotton supplies, a key input into Britain's cotton large textile industry. The reduction in raw cotton supplies caused a depression in this industry, with production dropping by around half, lasting from 1861-1865. Because the direct effects of this shock were largely confined to the cotton textile industry, we are able to assess the importance of inter-industry connections by looking at whether other industries in the economy also display negative effects. The advantage of this setting is that it provides a very large temporary industry-specific shock. Moreover, despite the large size of the shock, there was virtually no government response. This feature, which is important in allowing us to identify the true effects, was due to the very strong free market ideology prevalent in Britain at this time. It is unlikely that a modern economy could experience a similar shock with so little government response. In order to study this episode, a new data set was collected from original British Censes reports. This dataset includes industry employment data for 171 industry groups, spanning the entire private sector economy, spanning the period 1851-1891. These data are also geographically disaggregated, with data available for towns as small as 50,000 persons. We focus on two industrial counties in the north of England, Lancashire and Yorkshire. Lancashire was the cradle of the industrial revolution and the heart of Britain's cotton textile industry. Yorkshire was a similar industrial county, lying just to the east of Lancashire, but with one crucial difference. While Yorkshire also had a large textile sector, most textile production in Yorkshire was based on wool rather than cotton. Thus, while towns in Lancashire were severely impacted by the U.S. Civil war, towns in Yorkshire were not negatively impacted. Thus, comparing outcomes in Lancashire to those in Yorkshire allows us to better identify the impacts of the cotton shortage. The hypothesis studied is that industries more closely connected to the cotton textile industry should suffer lower employment or employment growth, in those locations more severely impacted by the shock. The Engine and Machinery industry provides a helpful illustration. Engine and Machinery firms provided textile producers with machinery such as spinning mules, weaving looms, and steam engines. There is also some evidence that these industries shared technical knowledge and used complementary labor pools. The data show that Engine and Machinery producers followed similar growth paths in Lancashire and Yorkshire prior to the recession, but that Yorkshire firms gained an advantage after the U.S. Civil War, as reflected by higher employment growth. The results of this study suggest that inter-industry connections can play an important role in influencing the location of industries. We find that industries more closely related to cotton textiles experienced reduced employment growth after 1861, in towns that were more severely impacted by the recession. These effects are still apparent as late as 1881-1891, more than 15 years after the end of the U.S. Civil War. This suggests that temporary economic shocks, working through inter-industry connections, can have long-run impacts on the geographic location of economic activity.
