Southern Tier West al Planning & Development Board James Cooper, Chairman Richard T. Zink, Executive Director Southern Tier West al Innovation Analysis Southern Tier West al Planning and Development Board Economic Development Advisory Committee May 2012 EDA had funded two economic studies undertaken by Purdue University, Indiana University, and other partner organizations to explore recent analytical advances in the science of economic development. The studies goals included determining the causes of economic growth in regions, and learning how regions can use an understanding of their region s industry clusters, occupation clusters, and capacity for innovation to inform strategic economic development thinking at the regional level. This presentation relates to this last goal, the understanding of the Southern Tier West region s capacity for innovation. One of the central tenets of two research projects was that a region s capacity to innovate is a precursor to the development of a healthy, competitive, sustainable regional economy. Further, regional economic growth is a function of the level of innovation present in a given regional economy. The research team looked at both inputs to innovation and innovation related outputs in regional economies, and developed a database of relevant data, which is available on a web site (www.statsamerica.org) served by Indiana University. s such as the Southern Tier West region can visit this web site and obtain relevant data, which they can use in the development of their Comprehensive Economic Development Strategies (CEDS). The research team also developed a data driven analytical tool (the Innovation Index ) to evaluate the innovative capacity of regions across the USA. This tool is available on the Internet for use by regions such as the Southern Tier West region for evaluating their capacity to innovate. Innovation Index The cumulative Innovation Index consists of five components, weighted as follows: 1. Human Capital: 30% 2. Economic Dynamics: 30% 3. Productivity and Employment: 30% 4. Economic Well Being: 10% 5. State Context (for reference only) The Innovation Index takes a broad look at indicators related to innovation from both the input and output perspectives, to provide a descriptive analysis of a region s capacity for innovation. The Innovation Index comprises two broad categories: inputs to innovation, which measure innovation Center for al Excellence, 4039 Route 219, Suite 200, Salamanca, NY 14779 1493 Tel (716) 945 5301 * Fax (716) 945 5550 * Hearing Impaired (716) 945 2266 www.southerntierwest.org
capacity (#1 and #2 above), and outputs of innovation, which measure the results (#3 and #4 above). Within each broad category, the index provides additional detail and individual measures (sub indices) that collectively comprise the category. The Innovation Index is designed to highlight factors that indicate a region is more or less ready to participate in the knowledge economy. The Innovation Index can help a region to: Understand how a region compares to the nation, other regions and states in terms of innovation capacity and innovation performance results. Identify the individual indicators that are driving innovation in a region. Communicate the need for new development using the economic well being sub index. Test regional scenarios with different sets of county partners. The following is a breakdown of the two Input Indices and the two Output Indices: Inputs: 1. Human Capital A. Educational Attainment B. Population Growth Rates C. High Tech Employment Share D. Technology Based Knowledge Occupations 2. Economic Dynamics A. Average Venture Capital B. Broadband Density and Penetration C. Establishment Churn D. Establishment Sizes Outputs: 3. Productivity and Employment A. Change in High Tech Employment B. Job Growth C. Gross Domestic Product per Worker D. Average Patents per 1,000 Workers 4. Economic Well Being A. Average Poverty Rate B. Average Unemployment Rates C. Average Net Migration D. Average PCPI Growth E. Compensation State data also is provided as a reference point. The balance of this presentation is the data results for each of these components of the Innovation Index for the three county Southern Tier West (called the Custom region in the charts below), in comparison with New York State and the U.S. as a whole. The source of all of the data and charts in this section is www.statsamerica.org.
The Southern Tier West s Cumulative Innovation Index (Normalized so that U.S. is equal to 100) The above chart representing the cumulative Innovation Index shows that the three county Southern Tier West region is less prepared to innovate than the State or country as a whole. The following is a presentation of, first, the two input categories that affect innovation, and second, the two output categories.
1. Human Capital The above chart shows a representation of the region s human capital inputs Index, which is cumulative a measure of the region s population's relative capacity to contribute to innovation. The index shows that the three county Southern Tier West region is less prepared to innovate than the State or country as a whole. Human capital inputs are those characteristics that describe the ability of the population and labor force to innovate. They include: A. Educational Attainment B. Population Growth Rates C. High Tech Employment Share D. Technology Based Knowledge Occupations
A. Educational Attainment Educational attainment is a measure of the population's capacity to contribute to innovation with necessary skills and knowledge. This measure is comprised of two component indicators that measure not only highly educated residents (ages 25 to 64) with a bachelor's degree or higher, but also residents with some college. Research shows that the some college/ associate's degree indicator has a significant effect on the growth of GDP per worker. Percent of Adult Population With Some College or an Associate's Degree, 2000 Percent of Population Population Ages 25 64 Ages 25 to 64 with Some with Some College Total Population College or an Associate's Degree or Associate's Degree Ages 25 64 STW 30.2% 40,374 133,738 NY 26.2% 2,642,182 10,091,839 U.S. 29.6% 43,521,981 147,232,667 Percent of Population Population Ages 25 64 Ages 25 to 64 with Some with Some College Total Population County College or an Associate's Degree or Associate's Degree Ages 25 64 Allegany County 29.5% 6,794 23,007 Cattaraugus County 27.8% 11,632 41,837 Chautauqua County 31.9% 21,948 68,894
Percent of Adult Population With a Bachelor's Degree or Higher, 2000 Percent of Population Population Ages 25 64 Ages 25 to 64 with a with a Bachelor s Total Population Bachelor s Degree or Higher Degree or Higher Ages 25 64 STW 17.9% 23,875 133,738 NY 30.0% 3,031,927 10,091,839 U.S. 26.5% 39,078,598 147,232,667 Percent of Population Population Ages 25 64 Ages 25 to 64 with a with a Bachelor s Total Population County Bachelor s Degree or Higher Degree or Higher Ages 25 64 Allegany County 18.3% 4,208 23,007 Cattaraugus County 16.5% 6,906 41,837 Chautauqua County 18.5% 12,761 68,894 The above data indicate that the region is competitive with the State and country as a whole in terms of persons having some college or an associate s degree, but is less competitive in terms of having bachelor s degrees or higher. This lower incidence of bachelor s degrees or higher in part explains the region s lower human capital index.
B. Population Growth Rates High population growth rates for younger working age persons (ages 25 to 44) suggest new residents are attracted to an area, growing the workforce, adding to the innovative base and launching new businesses. Research shows this indicator has a significant effect on the growth of GDP per worker. Percent Change in Young Adult Population, 1997 2009 Average Annual Change in Young Adult Population Young Adult Population Young Adult Population 2009 1997 STW 2.1% 58,183 75,148 NY 0.9% 5,351,598 5,937,916 U.S. 0.2% 83,096,278 85,573,378 Average Annual Change in Young Adult Population Young Adult Population County Young Adult Population 2009 1997 Allegany County 1.7% 10,297 12,649 Cattaraugus County 2.5% 17,272 23,446 Chautauqua County 2.0% 30,614 39,053 The above chart shows that the region is experiencing a higher decline in its young adult population than either the State or country as a whole. This higher decline in young adult population in part explains the region s lower human capital index.
C. High Tech Employment Share Firms requiring a highly skilled and specialized workforce contribute to innovation in a region by providing a resource for workers, other firms and other industries. (This metric measures the point in time innovative capacity of the region as opposed to the growth of innovative capacity in the productivity and employment index.) Average High Tech Employment Share, 1997 2009 Average High Tech Average High Tech Average High Tech Employment Share, Employment Share, Employment Share, 1997 2009 1997 2002 2003 2009 Custom 2.8% 3.3% 2.4% NY 4.5% 4.7% 4.3% U.S. 4.9% 5.1% 4.6% Average High Tech Average High Tech Average High Tech Employment Share, Employment Share, Employment Share, County 1997 2009 1997 2002 2003 2009 Allegany County 3.5% 4.0% 3.1% Cattaraugus County 2.6% 2.9% 2.4% Chautauqua County 2.8% 3.3% 2.3% The three county region has a much lower percentage representation of high tech employees in the employment base, indicating that the pool of tech skilled workers available to support innovation and tech based business development is smaller in the region as compared to the state and nation as a whole, on a relative size basis.
D. Technology Based Knowledge Occupations This measure provides a related analysis of the tech employment base in the region, by providing a descriptive index of the following six occupation clusters, which are often thought to be closely associated with the production of innovations: information technology; engineering; health care and medical science practitioners and scientists; mathematics, statistics, data and accounting; natural science and environmental management; and postsecondary education and knowledge creation. Technology Based Knowledge Occupations Share of Total Employment, 2009 STW 6.1% NY 9.8% U.S. 8.4% Technology based Knowledge Occupation Cluster Share of Total Employment, 2009 Technology based Knowledge County Occupation Cluster Share of Total Employment, 2009 Allegany County 6.8% Cattaraugus County 6.3% Chautauqua County 5.7% Although the state has a larger tech based knowledge occupation cluster employment share than does the nation as a whole, the region lags both the state and nation significantly in this regard, giving further demonstration of the inadequacy of the labor pool to support tech based and knowledge based business development and innovation.
2. Economic Dynamics The above chart shows a representation of the region s Economic Dynamics inputs Index, which provides a cumulative measure of local resources available to regional entrepreneurs and businesses that encourage innovation close to home. The index also shows that the three county Southern Tier West region is less prepared to innovate than the State or country as a whole. The Economic Dynamics inputs index is a composite of the following four regional resources: A. Average Venture Capital B. Broadband Density and Penetration C. Establishment Churn D. Establishment Sizes
A. Average Venture Capital Venture capital provides a source of funds to launch new ideas or expand innovative companies. Average Venture Capital Investment per $10,000 GDP, 2003 2008 Average Venture Capital Investment per $10,000 GDP STW $ 0.00 NY $25.44 U.S. $52.56 County Average Venture Capital Investment per $10,000 GDP Allegany County $0.00 Cattaraugus County $0.00 Chautauqua County $0.00 The data indicate that venture capital is essentially not available or else not being utilized in the three county region. In fact, statewide, the incidence of utilization of venture capital appears to be less than half of the national rate, as measured per $10,000 GDP.
B. Broadband Density and Penetration Innovation and knowledge are linked to widespread Internet usage for individuals and businesses. There are two measures, both from the Federal Communication Commission (FCC), to gauge Internet usage. One measure is the level of Internet penetration, or broadband density. This measure is residential broadband fixed connections per 1,000 households in 2009, a new data series the FCC first released in early 2010. The FCC reports these data in ranges, not as a specific number of connections per 1000 households in a particular county. The midpoint in the range is graphically presented here. For a custom region an aggregation of two or more counties the midpoint for the region is calculated as the weighted average of the midpoints of all the counties in the region. The second measure is a proxy for the rate of Internet adoption. This indicator is defined as the change in the number of broadband providers available to residents in a given county from 2000 to 2009. (The FCC did not collect data on broadband connections before 2009. The change in broadband connections would have been the preferred measure for the rate of internet adoption.) Broadband Density, 2009 Midpoint Weighted Connections Residential Fixed Connections per 1,000 Households, 2009 per 1,000 Households, 2009 STW 638 601 800 NY 700 601 800 U.S. 700 601 800 Midpoint Weighted Connections Residential Fixed Connections County per 1,000 Households, 2009 per 1,000 Households, 2009 Allegany County 700 601 800 Cattaraugus County 500 401 600 Chautauqua County 700 601 800
Average Annual Percent Change in Broadband Providers, 2000 to 2009 Average Annual Percent Broadband Providers Broadband Providers Change, 2000 2009 2000 2009 STW 22.6% 6.0 46.0 NY 18.6% 19.0 101.0 U.S. 29.8% 106.0 1,543.0 Average Annual Percent Broadband Providers Broadband Providers County Change, 2000 2009 2000 2009 Allegany County 20.8% 2.0 13.0 Cattaraugus County 23.8% 2.0 17.0 Chautauqua County 23.1% 2.0 16.0 The data indicate that broadband penetration rates in the three county region are lower than they are at the state and national levels. However, the options for broadband availability, as measured by the number of providers available, are increasing within the region. Southern Tier West s efforts in serving dark areas of the region with wireless broadband service have had some impact in this regard.
C. Establishment Churn Innovative and efficient companies replace outdated establishments, or those firms unable to modernize techniques and processes. Average churn is a measure of total establishment births and deaths, and expansions and contractions, relative to the total number of firms in a region for all years available. Average Establishment Churn, 1999 2006 Average Establishment Churn STW 70.4% NY 72.6% U.S. 77.5% County Allegany County 69.3% Cattaraugus County 70.9% Chautauqua County 70.4% Average Establishment Churn Churn rates are lower in the region than in the state and nation as a whole. However, without additional data, the reasons for this are not entirely clear: the results may indicate healthier businesses, or a less efficient marketplace that results in the creation of fewer new businesses when old ones terminate operations.
D. Establishment Sizes The sizes of establishments provide an indication of a regional economy's structural composition. Small establishments with fewer than 20 employees are flexible and not overburdened by a bureaucratic organizational structure enabling rapid changes to implement new ideas and evolve with technology. On the other end of the spectrum, large establishments with more than 500 employees have both the capital and labor resources to fund research and other innovative activities. Research shows that the average share of small establishments has a significant effect on GDP per worker growth. Average Small Establishments per 10,000 Workers, 1997 2008 Average Small Establishments per Worker STW 376.0 NY 422.4 U.S. 373.0 County Average Small Establishments per Worker Allegany County 361.5 Cattaraugus County 379.9 Chautauqua County 378.0
Average Large Establishments per 10,000 Workers, 1997 2008 Average Large Establishments per Worker STW 1.37 NY 1.31 U.S. 1.10 County Allegany County 1.89 Cattaraugus County 1.34 Chautauqua County 1.23 Average Large Establishments per Worker The data above indicate that the three county region is represented by a healthy percentage of small establishments, as compared to the nation as a whole, but lags behind the state in this regard. On the other hand, there is a higher incidence of large establishments in the region than at the state and local level. The research team indicates that the impact of this latter data is lower innovation levels in the region. Also, the regional economy becomes more sensitive to dislocations by individual companies as a consequence of this higher incidence of larger employers.
3. State Context The state context level index is a measure of the resources available in a state to entrepreneurs and businesses. The state level indicators total R&D spending and science and technology graduates help evaluate the strength of a state s investments to support innovation. While not part of the calculation of the overall index itself, this section measures state resources available to entrepreneurs and businesses. These resources may not necessarily be used by all businesses, but their proximity and availability provide resources and capacity to innovate. This index is comprised of thee components, as follows: A. Science and Engineering Graduates from All Institutions B. R&D Intensity C. Industry R&D per $1,000 Compensation The above chart indicates that the State as a whole is not as competitive with respect to the resources available in a state to entrepreneurs and businesses. The following describes the data in the three component areas. A.
Science and Engineering Graduates from All Institutions The number of graduates from science and engineering programs within a given state increases the supply of individuals trained to meet growing demands on the skilled labor force. This indicator is provided as graduates per 1,000 members of the population. Science & Engineering Graduates per 1,000 Residents, 2008 Science and Engineering Graduates Total Estimated per 1,000 Residents Total S&E Degrees Population New York 4.5 88,419 19,464,482 United States 4.2 1,269,145 304,059,724 As indicated above, the state actually exceeds the balance of the country in the number of science and engineering graduates per 1,000 residents.
B. Research & Development Expenditures R&D Intensity Research and development investment yields product innovations, adds to the knowledge base of industry, and is a key economic growth driver. R&D intensity is state R&D expenditures as a percent of state GDP. Business provides just under two thirds of all R&D funding. While nonindustry investment in R&D is only about one third as large as industry R&D, federal, state, university, and nonprofit investments in R&D have a substantial effect on innovation. Nonindustry R&D often lays the foundation for profitable future private sector research. Research and Development Intensity, 2007 R&D Intensity New York 1.4 United States N/A The lack of data availability constrains the analysis of relative R&D intensity.
D. Research & Development Expenditures Industry R&D per $1,000 Compensation Industry R&D per $1,000 Compensation, 2007 Industry R&D per Total Compensation $1,000 Compensation Private R&D ($1,000) New York $0.02 $ 10,518,000 $ 633,248,064 United States $0.03 $246,680,000 $7,846,006,000 However, as shown above, the state lags the nation as a whole in the amount of privately funded R&D spending as a percentage of payroll.
Outputs Direct outcomes and economic improvements of innovative activities are displayed in the output indexes. There are two primary output indexes, Productivity and Employment and Economic Well Being. 4. Productivity and Employment This index measures economic improvement, regional desirability, or the direct outcomes of innovation. There are four components to this index, as follows: A. Change in High Tech Employment B. Job Growth C. Gross Domestic Product per Worker D. Average Patents per 1,000 Workers The chart above indicates that although the state exceeds the nation as a whole with respect to this output index, the three county region lags both the state and nation in terms of innovation outputs. The following describes the four components of this index.
A. Change in High Tech Employment Firms requiring a highly skilled and specialized workforce are drawn to innovative areas. Growth in this sector suggests the increasing presence of innovation. High tech employment, derived from a NAICS based definition by Moody s Analytics, measures an aggregation of employment in key sectors (e.g., telecommunications, Internet providers, scientific laboratories) as an average annual rate of change in the share of high tech employment. Research shows this indicator has a significant effect on GDP per worker growth. Percent Change in High Tech Employment Share, 1997 2009 Rate of Change in High Tech High Tech Employment High Tech Employment Employment Share, 1997 2009 Share, 1997 Share, 2009 STW 4.0% 3.3% 2.1% NY 0.6% 4.5% 4.2% U.S. 0.3% 4.9% 4.7% Rate of Change in High Tech High Tech Employment High Tech Employment County Employment Share, 1997 2009 Share, 1997 Share, 2009 Allegany County 3.4% 4.3% 2.8% Cattaraugus County 3.7% 3.1% 2.0% Chautauqua County 4.4% 3.3% 1.9% The data above indicate that although the state and nation as a whole both have experienced a decrease in high tech employment as a percentage of total employment, the decrease in high tech employment as a percentage of total employment has been much greater in the three county region, most notably in Chautauqua County.
B. Job Growth High employment growth relative to population growth suggests jobs are being created faster than people are moving to a region. A high ratio between these 2 variables indicates strong economic growth. Job Growth to Population Growth Ratio, 1997 2008 Job Growth to Total Total Total Total Population Growth Employment Employment Population Population Ratio (1997) (2008) (1997) (2008) STW 0.16 132,468 134,454 275,319 262,587 NY 1.09 9,731,825 11,166,653 18,143,184 19,464,482 U.S. 0.69 154,541,200 179,644,900 267,783,607 304,059,724 Job Growth to Total Total Total Total Population Growth Employment Employment Population Population County Ratio (1997) (2008) (1997) (2008) Allegany County 1.03 19,807 21,382 50,823 49,301 Cattaraugus County 0.08 40,845 41,291 85,123 79,810 Chautauqua County 0.01 71,816 71,781 139,373 133,476 The data above show that while population has been steadily declining in each of the three counties in the region, total employment has been edging upward slightly in two of the three counties, with a slight decrease in total employment in Chautauqua County. In comparison to the state and the nation as a whole however, both the state and nation have experienced significant increases in both population and employment growth, with a positive job growth topopulation growth ratio, while that ratio is negative for the three county region.
C. Gross Domestic Product per Worker GDP serves as a measure of county level economic output, while increases in GDP per worker measures increases in worker productivity. This can be measured through two indices, GDP per worker and percentage change in GDP per worker. Gross Domestic Product (GDP) per Worker, 2008 STW $72,724 NY $99,321 U.S. $79,554 County Allegany County $60,691 Cattaraugus County $71,317 Chautauqua County $77,117 GDP per Worker GDP per Worker The above data indicate that the three county region lags both the state and nation as a whole in GDP per worker.
Percent Change in GDP per Worker, 1997 2008 Average Annual Change GDP per Worker, GDP per Worker, In GDP per Worker 1997 2008 STW 3.1% 51,932 72,724 NY 3.4% 67,968 99,321 U.S. 3.5% 53,917 79,554 Average Annual Change GDP per Worker, GDP per Worker, County In GDP per Worker 1997 2008 Allegany County 2.6% 45,490 60,691 Cattaraugus County 3.1% 50,793 71,317 Chautauqua County 3.2% 54,356 77,117 The data below also show that although GDP is growing annually in the three county region, it is not growing as fast as the state and nation as a whole.
D. Average Patents per 1,000 Workers New patented technologies provide an indicator of individuals and firms abilities to develop new technologies and remain competitive in the economy. Patents are presented as total number per 1,000 workers. Average Patents per 1,000 Workers, 1997 2008 STW 0.17 NY 0.87 U.S. 0.51 County Allegany County 0.29 Cattaraugus County 0.16 Chautauqua County 0.15 Average Patents per 1,000 Workers Average Patents per 1,000 Workers The above data indicate that although the state has a significantly higher level of patent development than does the nation as a whole, the three county region has a significantly lower level of patent development than both the state and nation.
5. Economic Well Being The other output index is Economic Well Being. Innovative economies improve economic well being for residents because they earn more and have in increasing standard of living. This index is comprised of five components, as follows: A. Average Poverty Rate B. Average Unemployment Rates C. Average Net Migration D. Average PCPI Growth E. Compensation The Economic Well Being Index shows that although the overall economic well being of the three county region is lower than both the state and nation as a whole, the region is fairly close to and competitive with the state and nation in terms of economic well being. Following is a description of the five components of this index.
A. Average Poverty Rate Innovative economies are thought to be less poverty stricken as a result of elevated employment opportunities and a more highly educated workforce with diverse skills that open the doors to an increased number of employers. As poverty rates decrease, presumably innovation has increased. Poverty Rate, 3 Year Average from 2006 2008 Average Number Number Number Poverty in Poverty in Poverty in Poverty Rate 2006 2007 2008 STW 16.1% 40,582 39,076 41,676 NY 13.9% 2,670,773 2,584,756 2,595,816 U.S. 13.2% 38,757,253 38,052,247 39,108,422 Average Number Number Number Poverty in Poverty in Poverty in Poverty County Rate 2006 2007 2008 Allegany County 17.2% 8,027 7,443 7,669 Cattaraugus County 15.2% 11,657 12,247 11,403 Chautauqua County 16.3% 20,898 19,386 22,604 The data above show that the three county region and each of the three counties have an average poverty rate exceeding that of both the state and nation as a whole, with the poverty rate in Allegany County being the highest poverty rate of the three counties. The research team thus would infer that innovation is not occurring at as high a rate as in the state and nation as a whole.
B. Average Unemployment Rates Innovative economies have greater employment opportunities and lower unemployment rates. Unemployment Rate, 3 Year Average 2007 2009 Unemp. Rate 3 year Labor Labor Labor Average Unemp. Unemp. Unemp. Force Force Force 2007 2009 2007 2008 2009 2007 2008 2009 STW 6.4% 6,483 7,936 11,222 132,002 132,934 132,651 NY 6.1% 434,303 517,772 804,438 9,532,054 9,631,691 9,640,618 U.S. 6.6% 7,078,000 8,924,000 14,265,000 153,124,000 154,287,008 154,142,000 Unemp. Rate 3 year Labor Labor Labor Average Unemp. Unemp. Unemp. Force Force Force County 2007 2009 2007 2008 2009 2007 2008 2009 Allegany County 6.9% 1,299 1,561 2,094 23,503 23,947 24,021 Cattaraugus County 6.7% 2,141 2,596 3,610 41,442 41,671 42,027 Chautauqua County 6.1% 3,043 3,779 5,518 67,057 67,316 66,603 Interestingly, although the thee county region s overall unemployment rate exceeded the state unemployment rate over this three year period, it was less than the unemployment rate of the nation as a whole. This is due primarily to the strength of the Chautauqua County economy, as both Allegany and Cattaraugus had unemployment rates exceeding both the state and national unemployment rates over this three year period. However, all three counties experienced an increase in the total number of unemployed over this period, which was masked by the growth in the labor force in Allegany and Cattaraugus and a contraction of the labor force in Chautauqua County. This contraction of the labor force in Chautauqua County has made it possible for the unemployment rate to be the lowest of the three counties, despite the significant increase in total unemployment in the county over the three year period.
C. Average Net Migration Total migration of all persons into a region serves as an indicator of whether a region is attractive to job seekers and families. Average Net Internal Migration Rate, 2000 2009 STW 49.1 NY 87.5 U.S. County Average Net Internal Migration Rate per 10,000 Residents N/A Allegany County 25.7 Cattaraugus County 65.8 Chautauqua County 47.7 Average Net Internal Migration Rate per 10,000 Residents The above data show that both New York State and the region are experiencing a negative net internal migration rate, indicating that the state and region not attractive to job seekers and families, but also that the three county region s migration rate is not as negative as the state s.
D. Average Growth in Per Capita Personal Income Per capita personal Income is the broadest measure of a person's income because it includes rental income, dividends and interest payments, in addition to salary, wages and benefits. As a result, it probably is the best measure of well being. Percent Change in Per Capita Personal Income, 1997 2008 Average Annual Growth in Per Capita Personal Income (PCPI) PCPI, 1997 PCPI, 2008 STW 4.3% $18,613 $29,799 NY 4.5% $30,012 $49,408 U.S. 4.3% $25,654 $40,947 Average Annual Growth in County Per Capita Personal Income (PCPI) PCPI, 1997 PCPI, 2008 Allegany County 4.1% $16,994 $26,658 Cattaraugus County 4.8% $18,647 $31,459 Chautauqua County 4.1% $19,168 $29,950 The above data show that the state s rate of growth of PCPI (4.5%) is higher than the national rate and the regional rate, which are equal at 4.3%. The rate of growth of PCPI is highest in Cattaraugus County, while the other two counties lag both the state and nation as a whole in PCPI growth rate.
E. Compensation Improvements in earnings per worker, or compensation, signify a positive trend in economic growth being passed on to workers. The following provides compensation data for two specific categories of workers: wage and salary employees and nonfarm proprietors. Percent Change in Average Wage and Salary Earnings, 1997 2008 Average Annual Wage and Wage and Change in Wage and Salary Salary Wage and Salary Wage and Salary Salary Earnings per Employment Employment Disbursements Disbursements Worker 1997 2008 1997 (000s) 2008 (000s) STW 3.0% 106,788 105,327 $ 2,518,946 $ 3,471,478 NY 4.1% 8,301,560 9,003,322 $ 315,016,781 $ 534,956,650 U.S. 3.8% 128,681,000 143,009,000 $3,872,441,000 $6,546,600,000 Average Annual Wage and Wage and Change in Wage and Salary Salary Wage and Salary Wage and Salary Salary Earnings per Employment Employment Disbursements Disbursements County Worker 1997 2008 1997 (000s) 2008 (000s) Allegany County 3.0% 14,850 15,020 $ 358,481 $ 506,787 Cattaraugus County 3.3% 33,267 32,702 $ 783,613 $1,104,810 Chautauqua County 2.9% 58,671 57,605 $1,376,852 $1,859,881 The data show that although the annual growth rate of wages and salary earnings in New York State exceeded the national growth rate, the three county region s growth rate was less than either the state or national rates, with the growth being the smallest in Chautauqua County.
Percent Change in Average Proprietors Income, 1997 2008 Average Annual Change Proprietors' Proprietors' Proprietors' Proprietors in Proprietors' Employment Employment Income Income Income per Proprietor 1997 2008 1997 (000s) 2008 (000s) STW 0.4% 21,728 25,748 $ 354,732 $ 438,695 NY 1.3% 1,391,589 2,130,655 $ 62,677,318 $ 83,467,737 U.S. 1.6% 23,648,200 34,732,900 $595,645,000 $1,046,135,000 Average Annual Change Proprietors' Proprietors' Proprietors' Proprietors in Proprietors' Employment Employment Income Income County Income per Proprietor 1997 2008 1997 (000s) 2008 (000s) Allegany County 1.6% 4,076 5,561 $ 58,894 $ 67,469 Cattaraugus County 3.1% 6,403 7,548 $113,041 $186,620 Chautauqua County 1.0% 11,249 12,639 $182,797 $184,606 Interestingly, proprietors incomes seem to be increasing at the national level, and to a lesser degree, at the three county regional level, but actually are decreasing at the state level. Within the region, lower proprietors incomes in Allegany County and Chautauqua County are more than counterbalanced by a relatively large rate of increase in Cattaraugus County.
Summary Findings: The following are the summary results of this Innovation Index analysis for the three Southern Tier West counties, in comparison to the state and nation as a whole: 1. The Southern Tier West region has a lower cumulative Innovation Index than the state and nation as a whole. This implies that the region is less prepared and capable to generate innovationbased economic development, which the theory asserts is essential for a long term healthy economy. Accordingly, as regional innovation capacity is identified as being a shortcoming of the region, this discussion has been located along with the discussion of other structural weakness and development constraints. 2. The Southern Tier West region has a lower cumulative Innovation Index is a function of its relative inadequacies in both human capital (labor force) and economic assets (including venture capital and broadband density and penetration), both of which the analytic model considers are inputs to innovation. A. The first input sub index, Human Capital (labor force) is comprised of four elements, with the analytic results as follows: A high concentration of residents with college associate's or bachelor s degrees has a significant positive effect on the growth of GDP per worker. The data indicate that although the region is competitive with the State and country as a whole in terms of residents having some college or an associate s degree, the region is less competitive in terms of residents having bachelor s degrees or higher. High population growth rates for younger working age persons (ages 25 to 44) suggest new residents are attracted to an area, growing the workforce, adding to the innovative base, and launching new businesses. This has a significant positive effect on the growth of GDP per worker. Unfortunately, the data indicate that the region is experiencing a higher decline in its young adult population than either the State or country as a whole. Firms requiring a highly skilled and specialized workforce contribute to innovation in a region by providing a resource for workers, other firms and other industries. However, the three county region has a much lower percentage representation of high tech employees in the employment base, indicating that the pool of tech skilled workers available to support innovation and tech based business development is smaller in the region as compared to the state and nation as a whole, on a relative size basis. Certain tech base occupation clusters are often thought to be closely associated with the production of innovations. However, although the state has a larger tech based knowledge occupation cluster employment share than does the nation as a whole, the region lags both the state and nation significantly in this regard, indicating that the region s labor pool is inadequate to support tech based and knowledge based business development and innovation. B. The second input sub index, Economic Assets, also is comprised of four elements, with the analytic results as follows: Venture capital provides a source of funds to launch new ideas or expand innovative companies. The data indicate that venture capital is essentially not available or else not being utilized in the three county region.
Innovation and knowledge are linked to widespread Internet usage for individuals and businesses. The data indicate that broadband penetration rates in the three county region are lower than they are at the state and national levels. However, the options for broadband availability, as measured by the number of providers available, are increasing within the region. Southern Tier West s efforts in serving dark areas of the region with wireless broadband service have had some impact in this regard. Innovative and efficient companies replace outdated establishments, or those firms unable to modernize techniques and processes. Establishment churn is a measure of total business births and deaths, and expansions and contractions, relative to the total number of businesses in a region, over a specified range of years. Churn rates are lower in the Southern Tier West region than in the state and nation as a whole. However, without additional data, the reasons for this are not entirely clear: the results may indicate healthier businesses, or a less efficient marketplace that results in the creation of fewer new businesses when old ones terminate operations. The sizes of establishments provide an indication of a regional economy's structural composition. Small establishments with fewer than 20 employees are flexible and not overburdened by a bureaucratic organizational structure enabling rapid changes to implement new ideas and evolve with technology. On the other end of the spectrum, large establishments with more than 500 employees have both the capital and labor resources to fund research and other innovative activities. Research shows that the average share of small establishments has a significant effect on the growth of GDP per worker. The data above indicate that the three county region is represented by a healthy percentage of small establishments, as compared to the nation as a whole, but lags behind the state in this regard. On the other hand, there is a higher incidence of large establishments in the region than at the state and local level. The analytical model indicates that the impact of this latter data is lower innovation levels in the Southern Tier West region. Also, the regional economy becomes more sensitive to dislocations by individual companies as a consequence of this higher incidence of larger employers. 3. As a whole, New York State is not as competitive with other states with respect to the resources available to entrepreneurs and businesses (as measured by the number of science and engineering graduates and R&D intensity). 4. Innovation is not only about inputs, however. A region s economy must translate these inputs into productive outcomes: employment in high technology firms, greater output per worker, the creation of patents, etc. By examining these output indicators, a region can explore how well its economy converts innovation inputs into performance. A. The first output productivity indicator, the Productivity and Employment Index, indicates that although the state exceeds the nation as a whole with respect to this output index, the three county Southern Tier West region lags both the state and nation in terms of innovation outputs. In fact, the region lags the state and nation in all four of the index s components: changes in high tech employment, job growth, GDP per worker, and average patents per worker. B. The second output productivity indicator, the Economic Well Being Index, indicates that although the overall economic well being of the three county Southern Tier West region is lower than both the state and nation as a whole, the region is fairly close to and competitive with the state and nation in terms of economic well being. This is borne out by mixed results for the five individual components of this index: The region s average poverty rate is higher than the state and national rates.
However, the region s average unemployment rate is higher than the state rate but lower than the national rate. Net in migration rates into the region are lower than state rates. The region s average PCPI growth rate is comparable to the national rate, and only slightly lower than the state rate. And the region s compensation growth rates are lower than state and national rates. 5. The data driven regional innovation analysis indicates that several factors appear to be especially important for increasing economic growth in the Southern Tier West region: educational attainment young adult population growth high tech employment growth venture capital availability and use business development finance availability broadband density and penetration the number of small establishments. The highlighted bullet list immediately above should be used to develop strategic economic development initiatives for the region.
Bibliography of Relevant Source Materials: 1. Unlocking Rural Competitiveness: The Role of al Clusters, Purdue University, Indiana University, et al, January 2007. http://www.statsamerica.org/innovation/reports/unlocking_rural_competitiveness_full_report.p df This study report provides an introduction to: o Industry clusters a tool for identifying the most significant sectors of the regional economy and developing strategies based upon that information 2. Crossing the Next al Frontier: Information and Analytics Linking al Competitiveness to Investment in a Knowledge Based Economy, Purdue University, Indiana University, et al, October 2009. http://www.statsamerica.org/innovation/reports/crossing_regional_frontier_full_report.pdf This study report provides an introduction to: o o o Occupation clusters a tool for assessing the regional workforce and human capital asset Innovation index a tool for assessing the region s capacity to innovate al strategy and investment framework a tool that provides guidance for developing a regional strategy from the information developed from the analytical tools 3. A Practitioner s Guide To Economic Development Tools for al Competitiveness in a Knowledge Based Economy, Purdue University, Indiana University, et al http://www.statsamerica.org/innovation/guide/practitioners_guide.pdf This guide provides a hands on guide for utilizing the various analytical tools described in the above two documents. 4. www.statsamerica.org/innovation A web site hosted by Indiana University, developed using EDA funding, which provides all the data, tools, practitioner s guide and roadmap for regional strategy building