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Poverty & Socioeconomic Distress in the North Central Region: Assessing Trends

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. Introduction

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Poverty & Socioeconomic Distress in the North Central Region: Assessing Trends

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  1. 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

  2. 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 Overview

  3. 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

  4. 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

  5. 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 well-recognized importance and a long-history of use--poverty, unemployment, household income Introduction

  6. 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. Introduction

  7. 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

  8. Historical Patterns: Family Poverty in Four Censuses 1979 1969 1989 1999

  9. Historical Patterns: Family Poverty Clustering (Local Moran’s I)

  10. Lobao, Betz, Partridge, and Goe (2013) Data Source: 1990 Census of Population

  11. Lobao, Betz, Partridge, and Goe (2013) Data Source: 2000 Census of Population

  12. Poverty, income, and unemployment • Trends over the decade with a focus on the Recession years • A look first across the United States The 21st Century: Poverty and Other Distress: The United States

  13. Lobao, Betz, Partridge, and Goe (2013) Data Source: 2000 Small Area Income and Poverty Estimates

  14. Lobao, Betz, Partridge, and Goe (2013) Data Source: 2007 Small Area Income and Poverty Estimates

  15. Lobao, Betz, Partridge, and Goe (2013) Data Source: 2010 Small Area Income and Poverty Estimates

  16. Lobao, Betz, Partridge, and Goe (2013) Data Source: 2000 and 2010 Small Area Income and Poverty Estimates

  17. Lobao, Betz, Partridge, and Goe (2013) Data Source: 2007 and 2010 Small Area Income and Poverty Estimates

  18. Lobao, Betz, Partridge, and Goe (2013) Data Source: 2000 and 2010 Small Area Income and Poverty Estimates

  19. Lobao, Betz, Partridge, and Goe (2013) Data Source: 2007 and 2010 Small Area Income and Poverty Estimates

  20. Lobao, Betz, Partridge, and Goe (2013) Data Source: 2000 and 2010 Bureau of Labor Statistics Local Area Unemployment Statistics

  21. Lobao, Betz, Partridge, and Goe (2013) Data Source: 2007 and 2010 Bureau of Labor Statistics Local Area Unemployment Statistics

  22. Lobao, Betz, Partridge, and Goe (2013) Data Source: 2007 and 2010 American Community Survey 3-year estimates

  23. 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 The 21st Century: Exploratory Analyses

  24. (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. Exploratory regression analyses– using mix of independent variables with focus on:

  25. 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, past-penalty of rurality) Findings for levels of poverty in 2010

  26. 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. Findings for changes inpoverty: where the recession hit hardest over years 2007-2010

  27. Poverty, income, and unemployment • Trends over the decade with a focus on the Recession years • Which places fared better, which worse? The 21st Century: Poverty and other Distress Across The North Central Region

  28. Lobao, Betz, Partridge, and Goe (2013) Data Source: 2000 Small Area Income and Poverty Estimates

  29. Lobao, Betz, Partridge, and Goe (2013) Data Source: 2007 Small Area Income and Poverty Estimates

  30. Lobao, Betz, Partridge, and Goe (2013) Data Source: 2010 Small Area Income and Poverty Estimates

  31. Lobao, Betz, Partridge, and Goe (2013) Data Source: 2000 and 2010 Small Area Income and Poverty Estimates

  32. Lobao, Betz, Partridge, and Goe (2013) Data Source: 2007 and 2010 Small Area Income and Poverty Estimates

  33. 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. The 21st Century The North Central Region

  34. Lobao, Betz, Partridge, and Goe (2013) Data Source: 2000 and 2010 Small Area Income and Poverty Estimates

  35. Lobao, Betz, Partridge, and Goe (2013) Data Source: 2007 and 2010 Small Area Income and Poverty Estimates

  36. Lobao, Betz, Partridge, and Goe (2013) Data Source: 2000 and 2010 Bureau of Labor Statistics Local Area Unemployment Statistics

  37. Lobao, Betz, Partridge, and Goe (2013) Data Source: 2007 and 2010 Bureau of Labor Statistics Local Area Unemployment Statistics

  38. 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.

  39. The North Central Region: Challenges and Policy Implications Region continues to face longstanding, well-known challenges (lack of natural amenities; an “old industrial region” economy/ever consolidating farm-sector; boom-bust commodity cycle)

  40. 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”

  41. Lobao, Betz, Partridge, and Goe (2013)

  42. 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.

  43. Thank-you!.

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