Methodology


Defining Poverty

Poverty is a complex social concept that can be understood and defined in a variety of different ways.  Most understandings of poverty conceptualize it as a level of socially unacceptable hardship due to material conditions, economic circumstances, or social position, but different social ideas of what exactly poverty means have resulted in a variety of different methods for measuring poverty (1).
 The table below shows some of these diverse methods for measuring poverty along with some of the strengths and limitations of each method.
Measures of Poverty
This report uses the U.S. Census Bureau’s Official Poverty Measure because it is the poverty measure for which the most complete information is available at the local level.

Selecting Which Issues to Study

To better understand which factors may contribute to poverty in Forsyth County, Forsyth Futures reviewed academic literature, local analyses from partner agencies, and conducted interviews with residents and local organizations. These analyses provided a broad range of risk factors which may play a contributing role to poverty in Forsyth County.

Selecting the Factors Studied 

The risk factors for poverty explored in each section of this study were sourced from analyses conducted by various local agencies, a review of academic literature, and a qualitative analysis of interviews with community members and organizational stakeholders.  The topics identified from these sources are listed in the sections below.  Issues for which there was sufficient publicly available data to assess the risk factor itself and its connection to poverty were included in this report. 

 Academic Literature Review 

Several broad theories attempt to address the question: What causes poverty? These theories differ significantly in how they identify pathways to poverty. While the analyses in this report are informed by a review of these theories, Forsyth Futures focused more heavily on risk factors of poverty that have been objectively measured and statistically associated with poverty.

 Local Analyses Review 

Forsyth Futures reached out through community partners to identify local analyses that are relevant to poverty, identifying several studies that had been carried out in Forsyth County that investigated poverty and issues related to poverty. Of these studies, only one, “Neighborhood Data Presentation”(8) published by United Way of Forsyth County as a part of its Place Matters initiative, met the following criteria:
  • the study was based on data collected through primary methods (they collected data themselves)
  • the study asked residents to identify causes of financial instability (which Forsyth Futures considered to be a sufficient proxy to poverty)
“Place Matters” suggests that a lack of financial literacy is a risk factor of poverty. Although this study met the criteria for local analyses, Forsyth Futures was unable to measure financial literacy as a risk factor in order to include it in this report.

 Qualitative Analyses

Forsyth Futures undertook qualitative data collection to better understand the community’s perception of what is causing poverty in Forsyth County. Forsyth Futures conducted interviews with the following:
  • representatives of organizations that address poverty or work with clients in poverty
  • residents who were living in high-poverty neighborhoods or experiencing poverty  
Forsyth Futures researchers analyzed these interviews for major themes, and issues repetitively referred to as causes of poverty or barriers to escaping poverty by different interviewees were identified as potential risk factors for the study. 

Factors Used

Concentrated Poverty
Education
Employment
Family Type
Health
Housing
Immigration
Income Insufficiency
Income
Industry

Factors Unused

Some risk factors are not included due to insufficient data or due to an insufficient quality of data available at the local level to support scientifically valid analyses – these factors have not been included in the report. For example; racism is very complicated to measure and could not have been directly measured with the resources available for this study. In the cases of other risk factors, such as transportation, a moderate amount of local data is available; however, there is insufficient quantitative data to support a rigorous, statistics-based analysis of transportation’s relationship to poverty. When there was insufficient local data on risk factors, Forsyth Futures could not investigate their relationship to poverty in Forsyth County or compare their potential impact to that of other risk factors.
Behavioral Health
Community Support
Criminal History
Financial Literacy and Budgeting
Food Access and Food Deserts
Generational Poverty
Large-scale Economy and Policy
Motvation, Work Ethic, and Culture
Networking
Parenting and Upbringing
Racism
Resource Access, Awareness, and Coordination
Security, Stability, and Crisis
Transportation

Relating Risk Factors to Poverty

Forsyth Futures assessed each identified risk factor as a measurable, potential contributor to poverty in Forsyth County. Each risk factor and its relationship to poverty was examined, both currently and over time, to establish a clear picture of how each risk factor has changed in the recent past. Forsyth Futures also assessed risk factors and their relationships to poverty in Forsyth County in the context of demographically similar comparison communities (see Comparison Communities below).
In most cases, Forsyth Futures observed disparities in exposure to risk factors and disparities in poverty among people exposed to risk factors when considering geography, age, gender, and race/ethnicity. To better understand which factors may contribute to these disparities, these analyses provide an extended assessment of each factor through these demographic lenses whenever possible (see Demographic Lenses below).

Comparison Communities

Contrasting Forsyth County with comparison communities allows Forsyth County’s statistics to be understood in the context of what is happening in similar communities. Comparing to similar communities means that differences identified are less likely to be due to basic demographic differences. This context shows that Forsyth County has higher poverty rates than all of its comparison communities. Throughout this study, Forsyth County is rigorously assessed against comparison communities across the identified risk factors for poverty; Forsyth Futures anticipates that the discrepancies discovered in these areas will illuminate key differences that could help explain why Forsyth County has a higher poverty rate than its comparison communities.
To identify these comparison communities, Forsyth Futures matched each county in the US with more than 65,000 residents to the largest city in that county with more than 65,000 residents (if one existed). An algorithm was then used to select the city/county pairs that were the most demographically similar to Winston-Salem and Forsyth County in terms of population size, population growth, age, race, gender, and rural/urban character.

Forsyth County and Comparison Communities

Forsyth County, NC
Guilford County, NC
Jackson County, MO
Forsyth County, NC
Guilford County, NC
Jackson County, MO
Pulaski County, AR
Roanoke city, LA
Lafayette Parish, LA
Pulaski County, AR
Roanoke (munc.), VA
Lafayette Parish, LA

Demographic Lenses

Geography

Poverty and the factors associated with it are not evenly spread across Forsyth County, and the local variation of each of these factors can be relevant to understanding and reacting to poverty.  This report uses census tracts to investigate local patterns within Forsyth County.  Census tracts are areas with 1,200 to 8,000 residents which may contain parts of multiple distinct socially-defined neighborhoods.  Local patterns may be more easily identified using other kinds of local areas (such as neighborhoods), but census tracts are the only local areas smaller than cities and counties with the census data that is central to this report.  And, other methods of identifying local areas would not provide adequate data for this report.

Age

Life circumstances change with age, and differing life stages can expose people to different risk factors for poverty, for example: having a larger family or less work experience. Child poverty is often of particular concern because children growing up in poverty are more likely to be in poverty as adults; child poverty can be an indicator of future poverty rates (9, 10). Understanding differences in poverty rates and risk factors between age groups could reveal differences in the underlying causes of poverty in each group.

Gender

The relationship between gender and poverty is complex, and there are a number of factors involved such as inequality in education, job opportunities, wage differences, social policies, and a lack of equal roles in political, social, and business sector decision making (11-13). Forsyth Futures examined the associations between both gender and poverty to assess if gender disparities exist in Forsyth County and to identify what may be contributing to these disparities in poverty. 

 Race/Ethnicity

Racial disparities exist in poverty, as poverty rates for members of the African American and Hispanic/Latino communities in the United States are generally substantially higher than those of the White, non-Hispanic community (14-16). The effects of racial disparities span multiple aspects of life including income, education, employment, neighborhood poverty, etc. Over time, the effects of these disparities increase the risk of these populations being in poverty (14, 17, 18).
Due to the composition of Forsyth County's population, Forsyth Futures included three racial groups in this study (White, non-Hispanic; Hispanic/Latino; and African American). Other groups present in Forsyth County were too small to produce accurate data from the census for most risk factors and were excluded.

References

  1. Poverty. (n.d.). Retrieved from https://www.merriam-webster.com/dictionary/poverty
  2. The World Bank. (2015). Brief FAQs: Global poverty line update. Retrieved from http://www.worldbank.org/en/topic/poverty/brief/global-poverty-line-faq
  3. Eurostat. (2014). Glossary: At-risk-of-poverty rate. Retrieved from http://ec.europa.eu/eurostat/statistics-explained/index.php/Glossary:At-risk-of-poverty_rate
  4. Short, K. (2015). The supplemental poverty measure: 2014. (US Department of Commerce Report).  Retrieved from https://www.census.gov/content/dam/Census/library/publications/2015/demo/p60-254.pdf
  5. Meyer, B. D., & Sullivan, J. X. (2010).  Five decades of consumption and income poverty (Working Paper 09.07). Retrieved from http://harris.uchicago.edu/sites/default/files/working-papers/wp_09_07.pdf
  6. Haveman, R., & Mullikin, M. (1999) Poverty: Improving the definition after thirty years. Retrieved from http://www.irp.wisc.edu/research/method/havemanall.pdf
  7. U.S. Department of Commerce. (n.d.). Supplemental poverty measure overview. Retrieved from http://www.census.gov/hhes/povmeas/methodology/supplemental/overview.html
  8. United Way of Forsyth County. Neighborhood data presentation. Retrieved from http://www.forsythunitedway.org/place-matters/
  9. Child Trends. (2015). Children in poverty. Retrieved from http://www.childtrends.org/?indicators=children-in-poverty 
  10. Danziger, S.H., & Haveman, R.H. (2001). Understanding poverty. Cambridge, MA: Harvard UP
  11. US Agency for International Development. (n.d.) Gender and extreme poverty. Retrieved from https://www.usaid.gov/ending-extreme-poverty/gender
  12. Negash, A. (2006). Economic empowerment of women. Retrieved from https://www.scu.edu/ethics/focus-areas/more/resources/economic-empowerment-of-women/
  13. Lin, A., & Harris. D. (2009). The colors of poverty: Why racial & ethnic disparities persist (Issue brief). Retrieved from http://www.npc.umich.edu/publications/policy_briefs/brief16/
  14. Kimmel, P. L., Fwu, C., Abbott, K. C., Ratner, J., & Eggers, P. W. (2016). Racial disparities in poverty account for mortality differences in US medicare beneficiaries. Population Health,  2, 123-129. doi:10.1016/j.ssmph.2016.02.003
  15. American Pscyhological Association. (n.d.). Ethnic and racial minorities and socioeconomic status. Retrieved from http://www.apa.org/pi/ses/resources/publications/factsheet-erm.pdf
  16. Schulz, A. J., Williams, D. R., Israel, B. A., & Lempert, L. B. (2002). Racial and spatial relations as fundamental determinants of health in Detroit. Milbank Quarterly, 80(4), 677-707. doi:10.1111/1468-0009.00028
  17. Sharkey, P. (2009). Neighborhoods and the black-white mobility gap. Retrieved from http://www.pewtrusts.org/en/research-and-analysis/reports/0001/01/01/neighborhoods-and-the-blackwhite-mobility-gap