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Abstract. The location quotient is a widely used index to measure agglomeration. However, a problem concerning the usefulness of the location quotient is how to obtain an objective cut-off value to identify the existence of agglomeration for an industry in a region. This paper extends the idea of O'Donoghue and Gleave (2004) and proposes a bootstrap method to determine the cut-off value based on the standardized location quotient. The advantage of our method is that the bootstrap method does not rely on any assumption regarding the statistical distribution of the location quotient, which is a major limitation of O'Donoghue and Gleave's (2004) approach. Then we apply the method to measure agglomeration of manufacturing industries at the county level in the United States.
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1. Introduction
The phenomenon of industrial agglomeration1 has drawn interest from both researchers and policy makers during the last few decades. In the academic field voluminous theoretical and empirical studies on industrial agglomeration have been emerging, motivated by the New Economic Geography, since the 1990's (Krugman, 1991). Policymakers, inspired by the idea of industrial clustering (Porter, 1990), have adopted the cluster-based economic develop- ment strategy (Carroll et al., 2008) as a policy tool to promote the local economy. For both researchers and practitioners, it is critical to first have some styl- ized facts about industrial agglomeration. One of the questions of the stylized facts is to understand the extent to which industrial agglomeration occurs, that is, how to measure agglomeration.
Constructing an index to measure industrial ag- glomeration is an important aspect of empirical studies in regional economics. Economists have long been seeking to develop an index that can accu- rately reflect the degree of agglomeration across industries, time, and space. Among many indices that have been discovered, we focus on the location quotient (LQ), which is used widely in regional sci- ence due to its computational simplicity and low data requirements. The LQ measures the ratio be- tween the local and national share of productive ac- tivities of a particular industry in a region, usually using employment to represent productive activi- ties. LQ > 1 can be interpreted as indicating that the industry under study is more concentrated in the region than the national average....