Input-output analyses of the structure and dynamics of economic systems recently have entered into a new phase of development, as more sophisticated modelling techniques have been used to evaluate larger and more complex data sets. A particularly promising line of inquiry has been the development of probabilistic distribution approaches to provide operational solutions for models. This project will continue development of these new probabilistic solution techniques in order to examine the regional variation in input-output coefficients, which reflect the ratios of transaction flows to total outputs for different sectors in specific locales over given time periods. The main thrust of the research will be analyses of U.S. national input-output data in order to refine solution techniques and to estimate probability density-derived coefficients of industry sectors for different regions and for the nation as a whole. The geographic variation of the coefficients will be analyzed to determine patterns of cross-regional variation and other sources of systematic variation, such as the size or type of industrial establishment. Analyses also will be made of the impacts of differences in regional technological development on economic activity. By exploring new techniques of input-output analyses on a previously untapped set of national industrial data, this project will be valuable from theoretical, methodological, and empirical perspectives. The enhancement of techniques based on probabilistic distributions will further general understandings of the utility of these types of techniques in comparison with more conventional forms of stochastic model solution procedures. Methodological developments will provide a foundation for future work on data sets for all scales, locations, and time periods, and the outcome of these tests should contribute new knowledge about the changing regional composition of the contemporary American economy.
