Date of Award


Document Type


Degree Name

Doctor of Philosophy (PhD)



First Advisor

David Yerger, Ph.D.

Second Advisor

Daniel Alex Heckert, Ph.D.

Third Advisor

John A. Anderson, Ph.D.


Many poverty authors point out that the various ways poverty is conceptualized and measured are very crucial because different poverty measures tend to capture different people as poor. The main focus of this research is to compare and examine how different poverty measures estimate poverty outcomes in the United States. The data for the study are from the 2004 of National Longitudinal Study of Youth, 1979 (US Department of Labor, 2006). Using frequency curves and cross tabulations, the distribution of the sample in poverty was computed. Logit models were used to estimate the likelihood of the effects of demographic characteristics on individuals to fall below the thresholds of three poverty measures that include the monetary, social exclusion, and capability poverty measures. All the three poverty measures have been found to estimate varied levels of poverty outcomes. Both the monetary and social exclusion poverty measures are found to exhibit consistent patterns in the distribution of sample in poverty. On the contrary, poverty incident is found to be highly sensitive to the capability poverty lines. In addition, the research findings also indicate that the poverty measures do overlap to capture a percent of the sample as poor. The result indicates a moderate agreement between the monetary and social exclusion poverty measures. However, the consistency between the capability and monetary or social exclusion poverty shows a weak agreement. The findings that the capability poverty measure exhibits inconsistent patterns of poverty distribution as well as a weak agreement with the other two poverty measures suggests that the capability poverty measure is not a good poverty measure. The logit analyses have also shown that gender (being female), race (other than White), place of residence (rural or inner city dwellers), and marital status (never married, separated, divorced, widowed) had statistically significant positive effects on the likelihood of individuals falling into poverty. Of these, marital status is the strongest predictor in determining the likelihood of persons falling into poverty.