Method for identifying local and domestic industrial clusters using interregional commodity trade data

Defining geographic as well as industrial boundaries in industrial cluster analysis is a challenging task. The most widely used methods for identifying industrial clusters utilize data from input-output tables. Given that inter-industry linkages are not confined to political boundaries, the questions discussed in the relevant literature on input-output based approaches focus on whether to use a regional or a national input-output framework. But neither framework can capture non-local transactions, which may be of major importance for smaller study regions. In the presented research, we expand the regional Chicago input-output framework to an interregional framework which accounts for both regional and non-local (i.e., commodity imports and exports by industry) inter-industry transactions. Applying factor analytical techniques to the data in this inter-regional framework, we are able to derive two sets of industrial clusters which we refer to as local and domestic clusters. In addition, we also identify the key sectors for each cluster based on indicators for industry backward and forward linkages. A comparison of these local and domestic clusters shows that while there are some similarities between these two types of clusters, there are also some significant differences between them. Thus, we demonstrate that it is important to include non-local inter-industry transactions as well in applied industrial cluster analysis.