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Hammond Econ Presentation Fisher


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OSU Econ 539 presentation of Fisher: "Why is U.S. Poverty Higher in Nonmetropolitan than in Metropolitan Areas?” in In Growth and Change, …

OSU Econ 539 presentation of Fisher: "Why is U.S. Poverty Higher in Nonmetropolitan than in Metropolitan Areas?” in In Growth and Change,
(March 2007)
Vol. 38 No. 1 pp. 56-76

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  • 1. “ Why is U.S. Poverty Higher in Nonmetropolitan than in Metropolitan Areas?” by Monica Fisher, OSU AREC In Growth and Change, (March 2007) Vol. 38 No. 1 pp. 56-76 Presented by D’Anne Hammond
  • 2. Rural/Urban Poverty, Fisher
    • Examines whether the difference in poverty levels reflects personal choice in addition to structural explanations of limited economic and social opportunities.
    • i.e. structural condition and sorting hypothesis?
  • 3. The question:
    • “ ...asking if the disproportionate poverty in non-metro places partly reflects attitudes of people with personal attributes related to poverty: they may be attracted to non-metro places or otherwise reluctant (or unable) to leave them.”
  • 4. Observable differences in poverty rates
    • Other research shows the odds of being poor are 1.2 to 2.3 times higher in rural areas
    • 1/20 metro counties poverty rate 20% or higher
    • 1/5 non-metro counties poverty rate 20% or higher
  • 5. Theoretical model
    • y = f (age; female/not; white/not; education; unemployed/not; in labor force/not; retired; disabled; married; household size; young child present/not; non-metro/not)
    • where y = adj. income-needs ratio
  • 6. Method
    • Series of multivariate regression models using OLS to model poverty across place
    • All models are variations of
    • y 1 = a 0 + a 1 x i + a 2 n i + a 3 s i + e i
    • Where y = pretax income-to-need; need is census-based poverty threshold
    • x = individual factors: race, age, gender, presence of children, etc.
    • n = binary variable indicating non-metro
    • s = fixed-effects controlling for state-level expenditures, tax structure, etc.
    • e = error term, assumed to be i.i.d.
  • 7. Variable y
    • Dependent variable y (income-to-need) is adjusted for housing cost differences using fair market rent values (FMR)
      • Persistent differences in housing costs between metro and non-metro
  • 8. Data source
    • Panel Study of Income Dynamics (PSID)
      • Nationally representative sample
      • Longitudinal data
      • Survey following apx. 5,000 families since 1968
      • This research uses the nine panels between 1985 and 1993 that include non-metro variable
  • 9. Data subsample
    • Household min. 2 yrs. observations in study
    • Restricted to lower income distribution
    • Records must have complete data for all variables
    • Head of household is a proxy for entire household
    • Result is sample of 2,007 household heads in poverty in 1993 and at least one other year between 1985 and 1993
    • Average number of years in sample =7
  • 10. Final data set characteristics
    • Differences (statistically significant) between whole sample and selected sub-sample
      • Female
      • With young child
      • Non-metro area
      • More likely non-white and unemployed
      • Lower education levels
  • 11. Results
    • F-stat indicates joint significance of explanatory variables (95% ci)
    • Indirect evidence supporting both structural condition hypothesis and self-sorting to non-metro
    • Metro to non-metro movers have increased income-needs ratio of 25%
    • Non-metro households economically worse off (ceteris parabus)
  • 12. Policy Implications
    • Further empirical studies on place-level and individual-level variables over time
    • “ ...can improve the design of anti-poverty policy, providing insights on what combinations of human-capital and community-strengthening policies are most likely to reduce non-metro poverty and its unfavorable consequences.” (p. 73)