Getting “Rural” Right: Poverty Disparities Across Two Dimensions of Rurality

Jose Pacas, University of Minnesota
Jonathan Schroeder , University of Minnesota
David Van Riper, Minnesota Population Center
Erin Meyer, University of Minnesota

To study rural poverty in the U.S., researchers commonly use metropolitan/non-metropolitan (i.e., metro/nonmetro) classifications rather than the Census Bureau’s urban/rural classifications, often mixing the “metro/nonmetro” and “urban/rural” terminology interchangeably. This practice is flawed and misleading. Under the metro/nonmetro classification, nonmetro areas have higher poverty rates than metro areas. However, under the urban-rural classification, the relationship is completely reversed; rural areas have the lowest poverty rates overall. In order to overcome this limitation, we compute a continuous measure of urban/rural status—population-weighted density—which can be used as a complement to the metro/nonmetro classification in the analysis of public-use census microdata, thereby capturing two dimensions of rurality. In general, we provide a theoretical basis and methodology for distinguishing rural areas in microdata beyond the metro/nonmetro classification and then use this framework to analyze urban/rural disparities in poverty.

See paper

 Presented in Session 98. The Changing Demography of Rural Areas