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To assess the strength of a cluster in a regional economy, the location ratios are calculated by comparing the cluster’s share of total local employment to the cluster’s national share. This quotient will yield a value generally between 0.00 and 2.00, where 1.00 demonstrates an equal share percentage between the local and national economies. Cluster location ratios greater than 2.00 indicate a strong cluster agglomeration, while those less than 0.50 indicate relatively weak clusters. The formulation is as follows: LQ = Local Industry Jobs Total Local Jobs National Industry Jobs Total National Jobs Data Collection CivEc compiled employment data from three fully compatible sources in order to assemble an accurate picture as possible of Cameron County’s economy. IMPLAN: Minnesota IMPLAN Group is the creator of IMPLAN software and databases and is a premier provider of economic and marketing analysis information. The primary input to the CivEc database is ES202 data, state and county level employment and wages at the 4-digit Standard Industrial Classification (SIC) code level. Government sources often suppress employment data, particularly at the local level, to avoid disclosing information about particular establishments. The suppressed elements in ES202 data have been adjusted through a procedure developed by MIG. For each community analysis, CivEc verifies the accuracy of this data by comparing ES202 with other data sources. CivEc uses IMPLAN because it is the most reliable source of data on American employment. ES202 data is drawn from mandatory submissions from all private sector enterprises, allowing for an accurate snapshot of employment. Data drawn directly from governmental sources fails to overcome the suppression problem. Private sector sources, such as Dun & Bradstreet, while purporting to collect more recent information, rely on non-mandatory surveys. This data is useful for identifying broad changes in the national economy, but is deemed by most economists too unreliable for any detailed analysis. BLS and State Labor Market Information: ES202 data excludes a few broad categories of workers in the American economy, most notably government employees. Fortunately, these workers are easily accounted for in other sources. The Bureau of Labor Statistics of the United States Department of Labor and state Labor Market Information sources provide readily available tabulations of public sector employment. The custom CivEc database facilitates an accurate blending of these employees into the ES202 data. viii.
APPENDIX D. SHIFT-SHARE ANALYSIS Shift-share analysis is one way to account for the competitiveness of a region’s industries and to analyze the potential contribution to its future economic base. This analysis is utilized to identify employment changes in various business sectors over a specific period of time. Shift-share indicates threats and opportunities based on regional, state, and industrial influences. Shift-share analysis breaks down employment growth (or decline) in a region over a given time period into three components: (1) a national growth effect, which assumes the growth (or loss) of employment in a region mirrors the national trend, (2) an industry mix effect, which is the amount of change in employment the region would have experienced had each of its industries grown at their national rates, less the national growth effect, and (3) a competitive effect, which is the difference between the actual change in employment and the employment change to be expected if each industrial sector grew at the national rate and thus determines the regional effect of industry employment. The sum of these three effects equals the actual change in total employment within a region over a prescribed time period. When these sums are plotted on a graph with XY coordinates, specific definitions that balance local trends against national trends can be applied to describe each industry’s current status, Figure D.1. Figure D.1. Definitions Used in Shift-Share Analysis CHALLENGE (-) National Trends CLUSTER is: - Lagging nationally - Leading locally CLUSTER is: - Lagging nationally - Lagging locally LIMITATION (+) Local Trends (-) ASSET CLUSTER is: - Leading nationally - Leading locally CLUSTER is: - Leading nationally - Lagging locally PROSPECT (+) ASSET – regional sector growth is faster than overall national employment growth; national sector growth is faster than overall national growth (fast regional growth in a quickly growing sector) PROSPECT – regional sector growth is slower than overall nationwide employment growth; regional sector growth is faster than overall regional growth (slow regional growth in a quickly growing sector) CHALLENGE – regional sector growth is faster than overall national employment; national sector growth is slower than overall national growth (fast regional growth in a regionally declining or lagging sector) LIMITATION – regional sector growth is slower than overall nationwide employment growth; national sector growth is slower than overall national growth (slow regional growth in a nationally declining or lagging sector) ix.
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CAMERON COUNTY/MATAMOROS AT THE CRO
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For George and Ronya Kozmetsky Dedi
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There is no choice in whether this
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University of Texas at Brownsville;
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SECTION 4. EDUCATION & TRAINING INT
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SECTION 6. CONCLUSIONS & RECOMMENDA
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Tables 3. 1. Respondents' Professio
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SECTION 6 Figures 6. 1. Border Secu
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Cross-Border Patient Needs: Develop
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UTB/TSC Student Profile Wage Compar
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UTB-CBIRD Report: “At the Crossro
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⇒ EDUCATION & TRAINING INTRODUCTI
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Percentage UTB-CBIRD Report: “At
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⇒ ECONOMIC DEVELOPMENT This secti
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