Moving From
Data to Decisions
Sharon Gulick, Pat Curry, ExCEED, University of Missouri Extension
Maurice Harris, MERIC, MO Dept. Economic Development
MEDC Conference, October 22, 2015
MERIC, ExCEED, BRIDG Partnership
•
•
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Provide easier access to data and special
research
MERIC will continue to focus on the large
projects, in-depth research, etc.
ExCEED & BRIDG will provide county/regional
data, county/region profiles, special projects,
training and planning
Rural Missouri Asset
Mapping
MISSOURI ECONOMIC
RESEARCH AND
INFORMATION CENTER
Introduction
Traditional economic development approaches alone
won’t change rural area trends.
• The report highlights rural county assets to consider
when planning economic development strategies.
• The assets that were selected were:
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•
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Population
Infrastructure
Entrepreneurial
Economic Catalyst
Large Urban/Rural Trends
Urban areas grow faster in population, not income.
¤
Rural income trends may be tied to farm income increases over this time period.
Area
Metropolitan US
Population
Personal Income*
Non-Metro US
Population
Personal Income*
Metro Missouri
Population
Personal Income*
Non-Metro Missouri
Population
Personal Income*
2000
2013
Change
% Chg.
241,035,121
$10,715,659
274,427,460
$12,906,262
33,392,339
$2,190,602
14%
20%
45,201,471
$1,423,692
46,609,359
$1,727,780
1,407,888
$304,087
3%
21%
4,127,071
$173,685
4,487,584
$196,834
360,513
$23,149
9%
13%
1,480,214
$43,337
1,556,587
$52,870
76,373
$9,533
5%
22%
*in Millions $2014
Headwaters Economics (US Forest Service): http://headwaterseconomics.org/tools/economic-profile-system
Large Urban/Rural Job by Type
Urban area employment grows at faster pace
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¤
Payroll Jobs declining in Rural Areas
Proprietors growing more slowly in Rural Areas
Area
Metropolitan US
Wage and Salary Jobs
Number of Proprietors
Non-Metro US
Wage and Salary Jobs
Number of Proprietors
Metro Missouri
Wage and Salary Jobs
Number of Proprietors
Non-Metro Missouri
Wage and Salary Jobs
Number of Proprietors
2000
2013
Change
% Chg.
121,466,930
22,660,177
126,590,791
34,294,278
5,123,861
11,634,101
4%
51%
17,945,007
5,520,284
17,523,464
6,445,152
-421,543
924,868
-2%
17%
2,294,668
397,849
2,266,808
532,407
-27,860
134,558
-1%
34%
560,056
221,005
549,831
230,827
-10,225
9,822
-2%
4%
Headwaters Economics (US Forest Service): http://headwaterseconomics.org/tools/economic-profile-system
Population Assets
Small cities are economic
hubs for rural areas:
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¤
Employment and
infrastructure centers
Draw commuting population
from surrounding counties
17 cities in rural counties
have population of 10,000
+.
Counties surrounding small
cities had at most 55% of
population working out of
county.
Infrastructure Assets - Transportation
4-Lane Highway Access
is Important
¤
Population in 15-Minute* Drive:
■ 91% All Population
■ 78% Non-Metro Population
*12 Miles used to estimate drive time.
Missouri has 6th Largest
Highway System in the
U.S.
Infrastructure Assets – Internet
Broadband Access is
Important:
¤
¤
48% of rural population
has access to two or more
ISP’s.
Download speeds > 25
mbps are big divider:
■
■
MO Rural: 40% (U.S. 55%)
MO Urban: 95% (U.S. 94%)
Source: FCC Broadbandmap.gov. Census 2010 Urban/Rural designation
Counties with postsecondary education
institutions have a larger
percentage.
Entrepreneurial Assets
Breadth and Depth are concepts that measures the concentration and
impact of entrepreneurial activities in a county.
Breadth assesses the quantity of activity, which reflects the size and
variety of small businesses.
¤
¤
Breadth is highest in small, isolated counties.
This is due to the need to spawn a large number of small firms to provide
goods and services.
Depth measures the quality of activity in a region. It assesses the
value small businesses generate for themselves and the local
economy.
¤
¤
Depth is higher in more densely populated metro and micropolitian
counties.
Self-employed workers usually earn higher incomes in larger metro
counties.
Source: Kansas City Federal Reserve Report: Gauging a Region’s Entrepreneurial Potential
https://www.kansascityfed.org/publicat/econrev/pdf/3q05low.pdf
Entrepreneurial Asset Maps
Economic Catalysts
Export-oriented (income
importing) sectors.
Map highlights top sectors
of employment.
Top-employing, exportoriented industries in rural
counties
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¤
¤
Manufacturing
Tourism
Agriculture
Source: U.S. Census American Community Survey, 2008-2012 5-Year Estimates. Definitions available at https://www.missourieconomy.org/
pdfs/rural_mo_asset_mapping.pdf
Summary
Urban Areas outpacing Rural
Areas in population and job
growth
Missouri has number of connected,
smaller cities that serve as
economic engines
Broadband access lower in rural
areas than U.S. average
Rural areas have entrepreneurial
breadth.
Top export-oriented industries in
rural counties
¤
¤
¤
Manufacturing
Tourism
Agriculture
https://www.missourieconomy.org/pdfs/rural_mo_asset_mapping.pdf
Data for Decision Makers
MEDC
October 22, 2015
“Getting information off the Internet is like taking a drink from a
firehose.” – Mitchell Kapor
“Every day, three times per second, we produce the equivalent
of the amount of data that the Library of Congress has in its
entire print collection, right? But most of it is like cat videos on
YouTube or 13-year-olds exchanging text messages about the
next Twilight movie.” – Nate Silver
“There are lies, damned lies, and statistics.” – Mark Twain
“Numbers have an important story to tell. They rely on you to
give them a voice.” –Stephen Few
Source: http://journal.c2er.org/2013/06/do-economic-developers-know-what-they-are-doing-the-curmudgeon-in-wonderland/
The Data Dilemma
Knowing your economy should be a ‘guiding principle’ for all economic
development professionals
Thousands of statistical sources on the Internet
Despite the ease of access provided at many sites the good stuff still
requires data base skills. Have you mastered Excel and Access?
Complicated definitions, limitations and suppression
Proliferation of indexes that manipulate and combine variables to distill
a one number solution
Developing meaningful benchmarks is difficult but necessary
How can you use data in planning without overloading the process
Data are metrics for job performance. Who picks the metrics in your
organization?
Dig deep – The important stuff isn’t on the surface
Population
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¤
Total
Components of change
Migration (inflow, outflow,
characteristics)
Race
Age
Labor Force
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¤
Total
Labor force participation
Educational attainment
Unemployment rate
Occupational characteristics
Commuting
Composition (sex, age, race)
School system indicators
Government Finance
Social Capital
• Economy
• Composition by sector
• Economic base
• Classification based on dominant industries
• Diversity
• Entrepreneurship, new business formation
• Small business sector
• Regional dynamics (worker and income flows)
• Wage rates (per job, by industry)
• Retail sales
• Income
• Personal income by source (BEA)
• Money income (per capita, household distribution)
• Poverty
• Gini coefficient
• Households/Housing
•
•
•
•
Total
Household type
Housing units by tenure
Affordability
So, where did you get those numbers?
Traditional sources: Census, BEA, BLS, FBI, NCES,
USDA …
Administrative record data: Missouri Dept. of
Revenue, IRS Statistics of Income, National Center for
Charitable Statistics
Proprietary sources: Economic Modeling Systems Inc.,
ESRI Business Analyst, Synergos Technologies Inc.,
Pcensus
Value added public access: StatsAmerica, Missouri
Census Data Center, On the Map, NetMigration,
Your Economy, Economic Profile System, Kids Count
What is it?
Population Change 2000 to 2010
90% of population
growth occurred in 6
counties
2002 Employment Density
Source: U.S. Census Bureau, Center for Economic Studies
2013 Employment Density
Source: U.S. Census Bureau, Center for Economic Studies
2013 Manufacturing Locations with 100+ Employees
Source: U.S. Census Bureau, Center for Economic Studies
2013 Employers with High Densities of College Educated Workers
Source: U.S. Census Bureau, Center for Economic Studies
Population Density by Census Block
Office of Management and Budget County Classification
Source: http://www.census.gov/population/metro/
Percent of Missouri Population by OMB Category
70%
67%
65%
65%
64%
64%
65%
15%
15%
15%
15%
14%
11%
1%
64%
60%
53%
55%
55%
24%
24%
49%
46%
41%
35%
33%
29%
27%
21%
17%
18%
0%
12%
12%
12%
11%
11%
11%
11%
10%
11%
11%
11%
14%
11%
2%
2%
2%
1%
1%
1%
1%
1%
1%
1%
1%
1%
1900
1930Outlying
1940
Metro 1910
Central 1920 Metro
Source: Census Bureau
1950
1980Outlying
1990
Micro 1960
Central1970 Micro
2000
2010 or 2014
Not Metro
Micro
Unemployment Rates by OMB Classification
0.1072
11.0%
0.0952 0.0928 0.096
0.0922
0.0817 0.0792
8.3%
5.5%
0.0593 0.0612 0.0612
0.0578 0.0569
0.0536 0.0521 0.0547
0.053 0.0515 0.0556
0.0476 0.0496
0.0436
0.0419
0.0753
0.0668 0.0643 0.0682
0.0588
0.0651
0.0605
0.0336
2.8%
0.0%
2000
2001
2002
2003
2004
2005
2006
Metropolitan
Missouri
2007
2008
Micropolitan
2009
2010
Rural
2011
2012
2013
2014
Historical Minimum and Maximum Unemployment Rates
30
Wayne
22.8
22.5
21.5
Iron
17.8
16.8
16.7
15.3
15
14.2
14
13.3
12.6
12
11.3
8.5
7.5
7.4
8.4
9.1
10.2
9.1 8.7
8
2.3
3
2
1.5 1.5 1.5 1.5 1.2
2.3
3
Taney
10.7
10.2
8.7
Boone
6
2.8 3
14.1
4.2
3.5 3.5 3.8 3.6 3.3 3.7
6.5
9.6
5.7
4.2 4.1 3.9
Worth
Boone
0
1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014
Minimum
Source: Bureau of Labor Statistics
Maximum
Real and Nominal Average Wage Growth 2001-2015
50%
38%
25%
13%
0%
-13%
2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015
Source: Economic Modeling Systems Inc.
US Nominal
US Real
MO Nominal
MO Real
Self Employed Workers 2001 to 2015
18%
14%
9%
5%
US
0%
2001
2002
2003
2004
Source: Economic Modeling Systems Inc.
2005
2006
2007
Missouri
2008
2009
2010
2011
2012
2013
2014
2015
Covered Employment 2001 to 2015
8.0%
6.0%
4.0%
2.0%
0.0%
-2.0%
US
-4.0%
2001
2002
2003
2004
Source: Economic Modeling Systems Inc.
2005
2006
2007
Missouri
2008
2009
2010
2011
2012
2013
2014
2015
Recovery – 2014 unemployment compared to 2006
Source: Bureau of Labor Statistics
Belle
• New business development organization
needs assistance with strategy
development
• Stagnant economy
• Geographically isolated
• Lagging retail sales but active retail
community
• Osage Arts Community
• Large commuting population
• Declining home ownership
• Age selective migration – Brain Drain
• How to take advantage of Rock Island
Trail State Park
USDA Stronger Economies Together
Green Hills Region
• Facilitating the planning process
• Delivering regional data profiles to
support regional development plan
• Purdue Center for Regional Development
• Research support as the project evolves
• Opportunities
• Build out of the East Locust Creek Reservoir
• Tourism
• Agribusiness
Stone County
Very unique growth drivers
¤ Table Rock Lake
¤ Branson
¤ Springfield MSA
Lake Recreation Retirement County
High income in-migration
Young low income out-migration
Economy dominated by small
businesses (63% compared to 26%
in the region)
Sustainable Ozarks Partnership
Leonard Wood Institute
SOP is the public outreach agent for
the Leonard Wood Institute at Ft.
Leonard Wood concerned with quality
of life
Veteran farmer training
Expanding markets for locally
produced foods
Grant writing
Building data bases describing
agricultural production, food demand,
veteran population, and market
characteristics
Developing a trail system
Civilian'
Population
Veterans
%'Veterans
Laclede
26,571
3,495
13.2%
Phelps
35,001
26,352
4,246
7,416
12.1%
28.1%
19,873
2,947
107,797
4,542,868
234,029,580
18,104
494,876
21,853,912
14.8%
16.8%
Pulaski
Texas
SOP?Region
Missouri
US
10.9%
9.3%
Data Services
• Detailed analysis of demographic,
housing and economic conditions,
trends and projections
• Drive time analysis and market profiles
• Economic impact assessment
• Detailed occupational profiles and
wage rates
• Tools for attraction
Smart, innovative workers like to be
around other smart, innovative
workers.
Manufacturing of the labor intensive
variety, no matter the tax
subsidies, will never return to the
United States
Trade is a two-way street
There are “Three
Americas” (innovative, well educated
cities, dying manufacturing hubs, and
cities that could go either way)
Small businesses is dependent on
large businesses.
“In the past, good jobs and high
incomes were tied to large-scale
production of manufactured goods.
Factories were the places where
economic value was created. But
today little value remains in the
production of goods that anybody
can make.”
ExCEED and BRIDG Services
Workshops
•
•
Fundamentals of Economic Development (New version coming in
2016)
•
Data For Decision Makers (coming early 2016)
Planning
Data
•
•
•
•
•
•
•
Custom analysis
Economic Impact Analysis
County/Regional Profiles
Mapping
Resilient Communities
Resilient Communities
▪
▪
Engagement with county/region to explore
opportunities and build an actionable plan to move the
county/region forward
Includes:
▪
▪
▪
▪
▪
Assessment and Readiness Analysis
Asset Mapping
Community Profile and Economic Impact Analysis
Development of Strategic Plan
Ongoing Support and Assistance
We Need Your Help
What data is important to you?
What format? Excel spreadsheet? Prepared tables
and charts? Other formats?
How do we benchmark?
¤ Who
do you consider your “peers”? Adjacent counties?
Counties of similar size? Similar economy?
Watch for a survey later this year.