2006
DOI: 10.1526/003601106781262025
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Are the Effects of the Macroeconomy and Social Policies on Poverty Different in Nonmetro Areas in the United States?*

Abstract: The macroeconomy and social policies can have substantial influences on poverty in the United States. In this paper, I investigate whether these influences differ across metro and nonmetro areas. To do so, using a 16‐year panel of state‐level data, I estimate state and year fixed effects models separately for metro and nonmetro areas to see if the effects of the macroeconomy and social policies differ between these two areas. These models are estimated using two measures—the poverty rate and the squared povert… Show more

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Cited by 21 publications
(19 citation statements)
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“…For example, certain industrial structures such as high proportions of employment in financial services (Singelmann 1978;Parisi et al 2003;Rupasingha and Goetz 2007) and manufacturing (Brady and Wallace 2001;Cotter 2002;Rupasingha and Goetz 2007) tend to reduce aggregate poverty. There is also widespread consensus that the proportion of the working-age population that is employed is associated with lower poverty in counties (Cotter 2002;Slack and Jensen 2002;Gundersen 2006;Rupasingha and Goetz 2007). Other factors that tend to increase the poverty rate of counties are the percent of families headed by females without a spouse present (Albrecht et al 2000;Goe and Rhea 2000;Lichter et al 2003;Lichter and McLaughlin 1995); a high proportion of the population aged 15 years of age and under (Cotter 2002;Rupasingha and Goetz 2007;Adelman and Jaret 1999); and the nonmetropolitan status of the county (Jensen et al 2003;Jensen and Tienda 1989;O'Hare 1988;Parisi et al 2003;Rank and Hirschl 1988;Rural Sociological Society Task Force on Persistent Rural Poverty 1993;Saenz and Thomas 1991).…”
Section: Prior Studiesmentioning
confidence: 99%
“…For example, certain industrial structures such as high proportions of employment in financial services (Singelmann 1978;Parisi et al 2003;Rupasingha and Goetz 2007) and manufacturing (Brady and Wallace 2001;Cotter 2002;Rupasingha and Goetz 2007) tend to reduce aggregate poverty. There is also widespread consensus that the proportion of the working-age population that is employed is associated with lower poverty in counties (Cotter 2002;Slack and Jensen 2002;Gundersen 2006;Rupasingha and Goetz 2007). Other factors that tend to increase the poverty rate of counties are the percent of families headed by females without a spouse present (Albrecht et al 2000;Goe and Rhea 2000;Lichter et al 2003;Lichter and McLaughlin 1995); a high proportion of the population aged 15 years of age and under (Cotter 2002;Rupasingha and Goetz 2007;Adelman and Jaret 1999); and the nonmetropolitan status of the county (Jensen et al 2003;Jensen and Tienda 1989;O'Hare 1988;Parisi et al 2003;Rank and Hirschl 1988;Rural Sociological Society Task Force on Persistent Rural Poverty 1993;Saenz and Thomas 1991).…”
Section: Prior Studiesmentioning
confidence: 99%
“…This is due in part to the fact that agriculture tends to predominate in rural areas with less diversified economies, and is also characterized by particularly high rates of underemployment compared to other industries (Slack and Jensen 2004). Research has also found the percentage of the working age population that is employed (versus unemployed or not in the labor force) is negatively associated with poverty (Cotter 2002;Gunderson 2006). This stands to reason since employment tends to be the strategy by which most non-wealthy Americans earn a living.…”
Section: Employment Structurementioning
confidence: 99%
“…Previous research has also shown a negative association between the percent of the working-age population employed and poverty Gundersen, 2006;Rupasingha & Goetz, 2007; see also Chapter 19 in this volume). Previous research has also shown a negative association between the percent of the working-age population employed and poverty Gundersen, 2006;Rupasingha & Goetz, 2007; see also Chapter 19 in this volume).…”
Section: Dimensions Of Poverty Correlatesmentioning
confidence: 76%