Transcript The Winners' Choice: Sustainable Economic Strategies for

Poverty & Socioeconomic
Distress in the North Central
Region: Assessing Trends
Linda Lobao, Mark D. Partridge, and Michael
Betz, The Ohio State University
and
Richard Goe, Kansas State University
North Central Regional Center for Rural
Development
April 11, 2013
Overview
• Introduction
• What are the historical patterns of poverty across
the U.S?
• What are the national trends of poverty and
other distress in the 21st Century?
• The North Central Region in the Great
Recession decade: which places fared better,
which worse?
• Challenges for the North Central Region and
implications for policy
Introduction
• Indicators of Populations’ Well-being
• “Objective indicators” (measures collected from
government, census-type sources). Well-known,
extensive data over the long-term collected,
provides ability to track populations’ well-being.
Used by numerous government agencies and to
allocate funds (e.g. Appalachian Regional
Commission Distress Index)
Key indicators: poverty, unemployment,
household income
Introduction
• Indicators of Populations’ Well-being
• “Subjective indicators” extensive literature on
various types of measures, an example
--“perceived” socioeconomic wellbeing,
progress in standard of living over time
Introduction
•The importance of “objective” indicators for
public policy, scholarly research, and ability to
track trends make such indicators essential.
•We focus on three sets of measures with wellrecognized importance and a long-history of
use--poverty, unemployment, household
income
Introduction
Our focus today– a descriptive study of change:
• Document patterns and trends over time for
poverty, unemployment, household income.
• Mapping the nation– and the 12 North Central
states –using county-level data.
• Exploring “reasons” why some counties fared
better than others over the past decade.
• Based on analyses—challenges and potential
policy directions for the North Central Region.
Historical Patterns of Poverty
• The historical north-south divide-- poverty rates
historically higher and family income lower in the
south
• Change has occurred over time—but even given
post-1970s massive industrial restructuring, still
better conditions in the north.
• Spatial clustering measures (Moran’s I) reflect this-following are maps for poverty
Historical Patterns: Family Poverty in Four Censuses
1979
1969
1989
1999
Historical Patterns: Family Poverty Clustering (Local Moran’s I)
Lobao, Betz, Partridge, and Goe (2013)
Lobao, Betz, Partridge, and Goe (2013)
Data Source: 2000 Census of Population
The 21st Century: Poverty and Other
Distress: The United States
• Poverty, income, and unemployment
• Trends over the decade with a focus on the
Recession years
• A look first across the United States
Lobao, Betz, Partridge, and Goe (2013)
Data Source: 2000 Small Area Income and Poverty Estimates
Lobao, Betz, Partridge, and Goe (2013)
Data Source: 2007 Small Area Income and Poverty Estimates
Lobao, Betz, Partridge, and Goe (2013)
Data Source: 2010 Small Area Income and Poverty Estimates
Lobao, Betz, Partridge, and Goe (2013)
Data Source: 2000 and 2010 Small Area Income and Poverty Estimates
Lobao, Betz, Partridge, and Goe (2013)
Data Source: 2007 and 2010 Small Area Income and Poverty Estimates
Lobao, Betz, Partridge, and Goe (2013)
Data Source: 2000 and 2010 Small Area Income and Poverty Estimates
Lobao, Betz, Partridge, and Goe (2013)
Data Source: 2007 and 2010 Small Area Income and Poverty Estimates
Lobao, Betz, Partridge, and Goe (2013)
Lobao, Betz, Partridge, and Goe (2013)
Data Source: 2007 and 2010 Bureau of Labor Statistics Local Area Unemployment Statistics
Lobao, Betz, Partridge, and Goe (2013)
Data Source: 2007 and 2010 American Community Survey 3-year estimates
The 21st Century: Exploratory Analyses
Which places fared better, which worse?
Our analyses are informed by a large literature on
“poverty and place” that identifies key reasons
why some places are poorer than others:
• (1) economic structure or employment quality,
quantity, and growth
• (2) demographic attributes such as age,
education, ethnicity, gender, and family structure
(reflect residents’ vulnerability to poverty)
• (3) agglomeration-geographic factors such as
urban-rural location, distance from urban areas
Exploratory regression analyses– using mix of
independent variables with focus on:
(1) Economic Structure:
Share of employment by industry-- manufacturing,
mining, agriculture, services (professional versus
food services)
Employment growth
(2) Demographic Attributes (residents’
vulnerability): age, education, ethnic composition,
family structure
(3) Agglomeration Factors: distance from urban
areas, size of place.
Findings for levels of poverty in 2010
Economic Structure:
Employment growth related to lower future poverty—importance of
job growth for overall area well-being.
Manufacturing and professional services (“higher quality” jobs)-where higher in 2000, no significant relationship with poverty rates in
2010. (Differences from some past decades)
Mining—where higher in 2000, lower poverty in 2010.
Demographic Determinants: similar to past:
Education (higher % college educated in 2000 related to lower poverty
in 2010)
Family structure (lower % single-parent households related to lower
poverty)
Agglomeration Factors: Counties more distant from metro areas tend
to have lower poverty rates (Differences from the traditional, pastpenalty of rurality)
Findings for changes in poverty: where the
recession hit hardest over years 2007-2010
Economic Structure:
Employment growth: where strongest early in decade (2000-2007) greater
growth in poverty.
Manufacturing employment and food service employment: where greater —
poverty growth.
No significant relationship--professional services and poverty.
Demographic:
Education—little effect; highly educated places generally did not fare better.
Single parent male households--poverty growth.
Age: younger--greater poverty; over age 65--less poverty growth.
Agglomeration Factors: larger metro counties experience greater growth in
poverty
*Other common determinants of poverty show little association with ability
to weather the recession.
The 21st Century: Poverty and other
Distress Across The North Central
Region
• Poverty, income, and unemployment
• Trends over the decade with a focus on
the Recession years
• Which places fared better, which worse?
Means and Standard Deviations of Selected Variables for NCS and the Rest of the US
2000
2010
Variable
NCS
RUS
NCS
RUS
Poverty rate
10.43
14.79***
14.17
18.16***
(4.04)
(5.67)
(4.91)
(6.35)
37,899
35,537***
44,280
42,438***
(7,608)
(9,483)
(8,083)
(11,710)
3.73
4.64***
8.22
9.69***
(1.25)
(1.75)
(3.24)
(2.95)
3.74
3.38***
(2.37)
(2.86)
17.65
19.53***
(10.46)
(8.69)
4.49
5.05***
(2.67)
(2.42)
0.41
0.44
(0.03)
(0.04)
1067
2069
Median household income
Unemployment rate
Change in poverty rate 2000-2010
Percent change in median household
income 2000-2010
Change in unemployment rate
2000-2010
Gini coefficient 2010 (ACS 3-year avg)
N
*** statistically significant difference at the 1% level
1067
2069
Lobao, Betz, Partridge, and Goe (2013)
Data Source: 2000 Small Area Income and Poverty Estimates
Lobao, Betz, Partridge, and Goe (2013)
Data Source: 2007 Small Area Income and Poverty Estimates
Lobao, Betz, Partridge, and Goe (2013)
Data Source: 2010 Small Area Income and Poverty Estimates
Lobao, Betz, Partridge, and Goe (2013)
Data Source: 2000 and 2010 Small Area Income and Poverty Estimates
Lobao, Betz, Partridge, and Goe (2013)
Data Source: 2007 and 2010 Small Area Income and Poverty Estimates
The 21st Century The North Central
Region
What we find for changes in poverty rates over 2007-2010
Places:
with greater employment growth had a relative decrease in the poverty rate
with greater dependence on manufacturing and professional services had
higher growth in the poverty rate.
closer in distance to metro areas had relative growth in their poverty rates.
with a higher proportion of those with an associate degree had a relative
decrease in the poverty rate
Little relationship with other common determinants of poverty used in
studies and changes in the poverty rate from 2007-2010.
Lobao, Betz, Partridge, and Goe (2013)
Data Source: 2000 and 2010 Small Area Income and Poverty Estimates
Lobao, Betz, Partridge, and Goe (2013)
Data Source: 2007 and 2010 Small Area Income and Poverty Estimates
Lobao, Betz, Partridge, and Goe (2013)
Data Source: 2000 and 2010 Bureau of Labor Statistics Local Area Unemployment Statistics
Lobao, Betz, Partridge, and Goe (2013)
Data Source: 2007 and 2010 Bureau of Labor Statistics Local Area Unemployment Statistics
The 21st Century: Poverty and other
Distress Across The North Central
Region
In summary, during the recession:
The western states within the North Central Region
tended to fare better.
Likely booms in commodity-based industries are visible
in our data—points of prosperity for the present.
Counties where manufacturing employment was higher
and counties closer to the larger cities fared worse.
The North Central Region:
Challenges and Policy
Implications
• Region continues to face longstanding, wellknown challenges (lack of natural amenities;
an “old industrial region” economy/ever
consolidating farm-sector; boom-bust
commodity cycle)
The North Central Region:
Challenges and Policy Implications
• Region as a whole may need place-based policy and
human-capital investment in education– yet local
government has declined across the U.S. (as
indicated by employment).
• There are no short-term fixes.
• Less migration, so local “shocks” have more impact.
• Policy likely more effective on the positive side in
remote locations.
• Small business development
• Tax incentive schemes tend to be “lose-lose”
Lobao, Betz, Partridge, and Goe (2013)
The North Central Region:
Challenges and Policy
Implications
• Trends over the recession decade improved
the western part of the region, reducing the
poverty gap.
• Banking on manufacturing and commodity
industries needs to be given greater scrutiny
as a development strategy in terms of
building long-term sustainable communities.
Thank-you!
.