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• 1. [Article] Measuring Dynamic Patterns in the Structure of Substate Economies

  The objective of this study was to explore a new method of analyzing the performance of substate economies. A major limitation of conventional analyses of economic diversity and growth is the reliance ...

  Citation × Citation Citation Abstract Copy Title: Measuring Dynamic Patterns in the Structure of Substate Economies Author: McHugh, Richard, Cooper, Ronald, Martin, Sheila A., Otto, Daniel, Johnson, Stanley R. Year: 1990 The objective of this study was to explore a new method of analyzing the performance of substate economies. A major limitation of conventional analyses of economic diversity and growth is the reliance on static measures of economic structure. Such measures do not capture the patterns of growth dynamics or structural change the region may be experiencing. This paper discusses a new measure of dynamic economic diversity and explores its relationship to economic performance. The measure is a statistical index that reflects the degree to which employment in a county's industries move together over time. The more the industries' employment levels move together, the higher the value of the index. A high index indicates a high degree of regional economic integration. The analysis was applied to county-level data from three states: Iowa, Minnesota, and Wisconsin. The findings: • Metro areas showed the highest values of the dynamic coherence index, and farm counties had the lowest values. Nonfarm/nor~etro counties were in the middle range. • High-coherence counties tend to have higher levels of per capita income. • Dynamic coherence appears to be positively related to the rate of economic growth as measured by employment growth rates. These findings may indicate that conventional static measures do not capture the economic linkages between industry sectors that make them move together. The positive correlations between the index of dynamic coherence and both income and employment growth may be reflecting the importance of interindustry linkages to the growth process. Title: Measuring Dynamic Patterns in the Structure of Substate Economies Author: McHugh, Richard, Cooper, Ronald, Martin, Sheila A., Otto, Daniel, Johnson, Stanley R. Year: 1990 The objective of this study was to explore a new method of analyzing the performance of substate economies. A major limitation of conventional analyses of economic diversity and growth is the reliance on static measures of economic structure. Such measures do not capture the patterns of growth dynamics or structural change the region may be experiencing. This paper discusses a new measure of dynamic economic diversity and explores its relationship to economic performance. The measure is a statistical index that reflects the degree to which employment in a county's industries move together over time. The more the industries' employment levels move together, the higher the value of the index. A high index indicates a high degree of regional economic integration. The analysis was applied to county-level data from three states: Iowa, Minnesota, and Wisconsin. The findings: • Metro areas showed the highest values of the dynamic coherence index, and farm counties had the lowest values. Nonfarm/nor~etro counties were in the middle range. • High-coherence counties tend to have higher levels of per capita income. • Dynamic coherence appears to be positively related to the rate of economic growth as measured by employment growth rates. These findings may indicate that conventional static measures do not capture the economic linkages between industry sectors that make them move together. The positive correlations between the index of dynamic coherence and both income and employment growth may be reflecting the importance of interindustry linkages to the growth process. Close

• 2. [Article] Traditional and Nontraditional Data as Indicators of Economic Activity in Rural Communities

  The objective of this study was twofold: (1) to identify nontraditional sources of data that can be used to monitor economic activity in rural areas, and (2) to test the relationship between such data ...

  Citation × Citation Citation Abstract Copy Title: Traditional and Nontraditional Data as Indicators of Economic Activity in Rural Communities Author: McHugh, Richard, Cooper, Ronald, Martin, Sheila A., Otto, Daniel, Johnson, Stanley R. Year: 1990 The objective of this study was twofold: (1) to identify nontraditional sources of data that can be used to monitor economic activity in rural areas, and (2) to test the relationship between such data and trends in traditional measures, such as income and employment. The need for alternative sources of data arises primarily out of the inconsistent quality and availability of traditional economic data at the subs tate level. New sources of data can help reduce this metro-rural data gap and provide a fuller picture of the diverse experience and structure of subs tate economies. Two sources of nontraditional data were explored: state government administrative records, and data from local private and quasi-private companies, such as utilities and banks. In particular, banking data from the Federal Reserve Bank of Chicago, phone connection data from Northwest Bell (U.S. West), and food stamp program data were used. The data series consisted of county-level data for Iowa, Minnesota, and Wisconsin. These data were statistically compared to employment growth levels in each county. Banking data (reflecting bank Willingness and ability to lend), phone data (reflecting new household and business formations), and food stamp participation correlated significantly (though weakly) with growth. The weak correlations are expected because the nontraditional data series are generally more volatile, or erratic, than employment data series. Composite indexes were constructed from the data and correlated with the employment data series. The results showed improved correlations and suggest that such indexes may be useful as leading indicators of economic activity. Overall, the results show that there is considerable potential in the development of economic indicators from nontraditional data. Title: Traditional and Nontraditional Data as Indicators of Economic Activity in Rural Communities Author: McHugh, Richard, Cooper, Ronald, Martin, Sheila A., Otto, Daniel, Johnson, Stanley R. Year: 1990 The objective of this study was twofold: (1) to identify nontraditional sources of data that can be used to monitor economic activity in rural areas, and (2) to test the relationship between such data and trends in traditional measures, such as income and employment. The need for alternative sources of data arises primarily out of the inconsistent quality and availability of traditional economic data at the subs tate level. New sources of data can help reduce this metro-rural data gap and provide a fuller picture of the diverse experience and structure of subs tate economies. Two sources of nontraditional data were explored: state government administrative records, and data from local private and quasi-private companies, such as utilities and banks. In particular, banking data from the Federal Reserve Bank of Chicago, phone connection data from Northwest Bell (U.S. West), and food stamp program data were used. The data series consisted of county-level data for Iowa, Minnesota, and Wisconsin. These data were statistically compared to employment growth levels in each county. Banking data (reflecting bank Willingness and ability to lend), phone data (reflecting new household and business formations), and food stamp participation correlated significantly (though weakly) with growth. The weak correlations are expected because the nontraditional data series are generally more volatile, or erratic, than employment data series. Composite indexes were constructed from the data and correlated with the employment data series. The results showed improved correlations and suggest that such indexes may be useful as leading indicators of economic activity. Overall, the results show that there is considerable potential in the development of economic indicators from nontraditional data. Close