SOCIO-ECONOMIC DATA FOR WNDD Presentation by: Tom Harris and Buddy Borden
Understanding WNDD Regional Strengths and Weaknesses Understanding Strengths and Weaknesses was a crucial piece of a successful region as defined in Module 2 in March in Carson City. (SET Facilitators Guidebook Page 2.29).
QUESTIONS TO BE DISCUSSED TODAY What are the current socio-economic conditions in WNDD? What components of the WNDD demographics and economy are growing or declining? What options exist for improving demographics and economic conditions in WNDD, and what options should we pursue first?
Silicon Valley Index Measures for Success Successful region can measures its success by: 1. Population Change 2. Educational Attainment 3. Employment 4. Occupational Skills (Source for 1 to 3: Index of Silicon Valley, Silicon Valley Community Foundation/Joint Venture Silicon Valley Network: San Jose, CA, 2011: P. 14. Accessed July 5, 2012 at: http://www.siliconvalleycf.org/docs/jointventure/2011-jv-index.pdf)
Why Are There Changes in Proportional Share in Goods-Producing and Service-Producing Industries? Increased Efficiencies Increased Personal Income and Changes in Demand Changes in World Economy
Proportionate Shares of Sources of Income for the U.S., State of Nevada, and WNDD from 1969 to 2010
County Population, Rank of Population and Change in Population Rank, WNDD and State of Nevada, 2000 to 2010 County 2000 2010 Change in Rank Population Rank Population Rank Clark 1,375,765 1 1,951,269 1 0 Washoe 339,486 2 421,407 2 0 Carson City 52,457 3 55,274 3 0 Elko 45,291 4 48,818 5-1 Douglas 41,259 5 46,997 6-1 Lyon 34,501 6 51,980 4 +2 Nye 32,485 7 43,946 7 0 Churchill 23,982 8 24,877 8 0 Humboldt 16,106 9 16,528 9 0 White Pine 9,181 10 10,030 10 0 Pershing 6,693 11 6,753 11 0 Lander 5,794 12 5,775 12 0 Mineral 5,071 13 4,772 14-1 Lincoln 4,165 14 5,345 13 +1 Storey 3,399 15 4,010 15 0 Eureka 1,651 16 1,987 16 0 Esmeralda 971 17 783 17 0 WNDD 183,468 211,191 WNDD Plus Washoe 522,954 632,598 TOTAL 1,998,257 2,700,551
Population by Age and Proportionate Share of Population by Age, Western Nevada Development District, 2000 and 2010. Age Group Number 2000 2010 Proportionate share Number Proportionate share Under 5 11,735 6.40% 12,624 5.98% 5 to 9 13,069 7.12% 12,937 6.13% 10 to 14 14,091 7.68% 13,596 6.44% 15 to 19 12,432 6.78% 13,592 6.44% 20 to 24 8,706 4.75% 10,935 5.18% 25 to 34 21,887 11.93% 23,329 11.05% 35 to 44 29,939 16.32% 25,557 12.10% 45 to 54 27,156 14.80% 32,792 15.53% 55 to 64 19,567 10.67% 30,840 14.60% 65 to 74 14,294 7.79% 20,826 9.86% 75 to 84 8,480 4.62% 10,550 5.00% 85 and above 2,112 1.15% 3,613 1.71% 65 and above 13.56% 16.57% TOTAL 183,468 100.00% 211,191 100.00%
Trends in Population by Race, Western Nevada Development District, 2000 and 2010 2000 2010 Race Number Proportionat e Share Number Proportionate Share Percentage Change 2000 to 2010 White 158,929 86.65% 177,244 83.93% +11.52% Black or African- American 2,375 1.29% 2,643 1.25% +11.28% American Indian or Alaska native 5,645 3.08% 6,332 3.00% +12.17% Asian & Pacific Islander 2,733 1.49% 4,017 1.90% +46.98% Other Race 13,728 7.48% 20,955 9.92% +52.64% Total 183,410 100.00% 211,191 100.00% +15.15% Hispanic or Latino (of any race) 21,319 11.62% 33,773 15.99% +58.42%
Nevada County Educational Attainment, Residents 25 and Older, 2010 County High School or Better Bachelor s or Better Graduate or Professional Churchill 87.7% 18.2% 6.6% Clark 83.5% 21.7% 7.2% Douglas 91.2% 25.9% 9.9% Elko 84.5% 15.8% 5.1% Esmeralda 84.1% 21.1% 6.1% Eureka 88.2% 17.8% 3.0% Humboldt 80.9% 13.4% 3.1% Lander 75.0% 12.9% 2.5% Lincoln 83.0% 15.8% 6.2% Lyon 85.8% 12.7% 4.2% Mineral 86.3% 8.2% 1.7% Nye 81.7% 10.5% 2.7% Pershing 79.4% 12.4% 3.6% Storey 91.8% 13.9% 5.5% Washoe 86.4% 26.7% 9.7% White Pine 83.8% 13.4% 3.8% Carson City 88.0% 21.6% 9.0% WNDD 87.1% 18.0% 6.9% WNDD Plus Washoe 54.3% 21.8% 7.4% NEVADA 85.0% 27.9% 10.3%
WNDD 85.8% 89.0% WNDD Plus Washoe 82.6% 85.8% NEVADA 86.8% 87.5% Nevada County Educational Attainment, High School or Better, Selected Age Groups, 2010 County High School or Better 25 to 34 Years Old High School or Better 45 to 64 Year Olds Churchill 91.9% 89.8% Clark 82.2% 85.0% Douglas 89.3% 92.7% Elko 84.7% 85.0% Esmeralda 100.0% 86.0% Eureka 78.4% 91.8% Humboldt 82.8% 80.8% Lander 77.1% 77.3% Lincoln 74.2% 85.6% Lyon 82.7% 87.8% Mineral 96.1% 89.9% Nye 79.4% 83.1% Pershing 69.7% 80.1% Storey 100.0% 88.9% Washoe 83.4% 87.6% White Pine 85.2% 86.9% Carson City 85.4% 90.0%
Group Exercise 1. What are the WNDD Region s Strengths from a Demographic Perspective 2. What are the WNDD Region s Weaknesses from a Demographic Perspective
Two Economic Development Procedures Export Enhancement Import Substitution
Export Enhancement Export Enhancement seeks to find economic sectors which WNDD has had relative success in attracting and nurturing during the past
Import Substitution Import Substitution seeks to reduce money outflows from WNDD by creating economic development opportunities to fill the demands for goods and services by WNDD businesses and institutions
Types of Import Substitution GAPS are demands for goods and services by WNDD industries and institutions purchased outside the WNDD Area because they are not produced locally. These are called Non- Competitive Imports. DISCONTECTS are demands for goods and services by WNDD industries and institutions purchased outside the WNDD Area but are produced locally. These are called Competitive Imports.
CRITERIA FOR SELECTING EXPORT ENHANCEMENT SECTORS IN WNDD Criteria used for selection follows 2006-2011 data supplied by the Southern Rural Development Center: 1. Location Quotients for 2011 2. Jobs in 2006 3. Hobs in 2011 4. Percentage Change in Jobs from 2006 to 2011 5. Average Earnings for 2011
CALCULATION OF LOCATION QUOTIENT LQ i = LEI i / TLE NEI i / TNE Where: LEI j = Local Employment Industry i TLE = Total Local Employment NEI j = National Employment Industry i TNE = Total National Employment
EXAMPLE LQ CALCULATION
BUBBLE CHART AREAS
BUBBLE CHART ANALYSIS WITH SRDC DATA
CLUSTER RATING CLUSTER Business & Financial AER Energy Biomedical Transportation &Logistics Agricultural Business Defense Advanced Materials Mining IT Telecommunications Printing Fabricated Metal Chemicals Education Forest Computer Transportation Equipment Primary Metal Apparel Machinery Glass Electrical Category STAR MATURE STAR STAR STAR MATURE STAR TRANSFORMING EMERGING TRANSFORMING TRANSFORMING TRANSFORMING TRANSFORMING EMERGING TRANSFORMING TRANSFORMING TRANSFORMING TRANSFORMING TRANSFORMING EMERGING TRANSFORMING TRANSFORMING
RANKING OF WNDD CLUSTERS-SRDC Business & Financial Energy Transportation & Logistics AER Biomedical Advanced Materials Mining Defense Primary Metal IT Telecomm Machinery Chemicals Agricultural Business Computer Fabricated Metal Education Glass Transportation Equipment Printing Electrical Forest Apparel CLUSTER
DETAILED SECTOR BY SRDC CLUSTER
Group Exercise Which clusters should WNDD pursue and why? Which clusters should WNDD not pursue and why?
SIERRA PACIFIC MEGAPOLITAN