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Census Bureau Poverty Rates
The U.S. Census Bureau is the most comprehensive source for poverty rates in the nation. Secondary data on poverty rates and welfare spending from the Census Bureau are used for this study. All ages and socio-economic conditions are sampled.
The North Dakota State Data Center supports the validity of Census Bureau data (Rathge & Olson). The reliability of the data is high but subject to non-sampling errors. This report accepts the data as reliable and valid.
The period of the study is from 1959 through 2009. Fifty one observations were analyzed. A second, smaller, time period of the last ten years of data was also analyzed. The study did not measure the influence of market conditions, unemployment rates, educational levels and unskilled wages of those living in poverty.
The study assumed that welfare spending is increased during times of economic decline and increased unemployment. The educational levels and unskilled wages of the impoverished were assumed to be relatively equal. Future studies need to control for these possible influences.
Linear regression and correlation analysis is used to answer the research question, “Does increased welfare spending reduce poverty rates?”
What is Poverty?
O’Boyle defines poverty as, “a lack of economic resources to meet physical need.” The Supplemental Poverty Measure (SPM) calculates expenditures for food, clothing, shelter, and utilities (FCSU), including the value of in-kind government benefits (Garner). ”Poverty is a moral obligation that is grounded in compassion. Most poor Americans have access to clean drinking water and electricity, unlike most of the global poor” (Stark).
Brady, Fullerton & Cross found that, “For each standard deviation increase in welfare generosity, the odds of poverty decline by a factor of 2.3.” Schram showed evidence that more spending results in less poverty.
Fording & Berry showed a decrease in the poverty rates with increased cash benefit. However, if the cash benefit rate is fixed, poverty rates increase. They attribute this to a “work disincentive effect.“
Brady, Fullerton & Cross acknowledged that, “The welfare state is not a panacea, as there is mixed evidence that generous welfare states might worsen the standing of young households.”
Schram noted that poverty rates have increased while welfare spending has, “remained at high levels.” He addressed the issue of welfare dependency and the “personal responsibility of the poor.” He found families who would rather take a job once they become self-sufficient. He states that the findings are, “not meant to suggest that welfare spending produces less poverty.”
These studies suggest that justification for increased welfare spending is at least questionable.
Welfare Spending Per Capita
Welfare spending per capita and poverty rates are displayed in Chart 1. The first ten years show a rise in welfare spending with a sharp decline in the poverty rate. The last ten years of the display show increased spending and an increase in the poverty rate. Since 1970, welfare spending increased and the poverty rate did not deviate by more than 3% from the mean.
Descriptive statistics are found in Table 1. The mean poverty rate is 14.11%. The mean number of dollars spent per person on welfare is $365.01. The standard error of the mean for welfare spending is 44.46 revealing little fluctuation.
Chart 1: Poverty Rates and Spending
US Welfare Spending and Poverty Rates
Poverty Rates Are Related to Welfare Spending
Linear regression and correlation analysis was conducted for the entire 51 year period. Results are shown in Table 2. Bivariate linear regression and correlation data did not reveal any outliers.
The standard error of the mean is 2.73, suggesting the sample represents the study. Welfare spending and the poverty rate are significantly correlated at 0.33 (p <.02). This means that 33% of the influence in welfare spending is explained by the poverty rate. Likewise 33% of the influence of the poverty rate is explained by welfare spending.
Correlation values reveal what influence two variables have on each other. The correlation analysis shows a negative coefficient suggesting that as welfare spending increases, poverty rates decrease. The influence or r square value between these variables is 0.11 meaning that 11% of the variance of poverty rates is influenced by welfare spending per capita.
The correlation between the relationship of welfare spending per capita and the poverty rate support the research question. However, this research is limited to one time period and only one independent variable. Other factors, such as unemployment rate, educational levels, unskilled wages and co-participation by charitable organizations should be investigated in future analysis.
Linear Regression of Poverty Rates
Weak Correlation: Increased Welfare Spending Decreases Poverty
The negative correlation of welfare spending per capita and the poverty rate using fifty-one observations support the research question that increased welfare spending decreases poverty rates. However, the coefficient is 0.33, a weak correlation. A value greater than 0.8 is generally described as strong, whereas a correlation less than 0.5 is described as weak (Roberts). It is difficult to know whether welfare spending was initiated as a reaction to the poverty rate or if the poverty rate was influenced by welfare spending.
Significant welfare spending did not begin until the late 1950s. Census Bureau data on spending is reported every ten years rather than annually.
Mixed Evidence that Welfare Spending Reduces Poverty
Bivariate linear regression of U.S. welfare spending per capita and poverty rates of the entire data set suggests that as welfare spending increases, poverty decreases.
However, linear regression of the last ten years of data showed a positive correlation suggesting that poverty rates increased as welfare spending increased. This data shows that current poverty rates are at one of the highest levels since 1959 and that welfare spending per capita is at an all time high.
Data was analyzed for the entire United States. The findings are more applicable at the Federal level. Narrowing the national findings to a particular state or municipality is less applicable. The analysis does not account for the affluence or unemployment rate of one city compared to another city of a similar population. Nonetheless, lawmakers should consider these findings when developing welfare legislation.
This study only looked at one independent variable (year). Other variables such as the unemployment rate, educational levels and unskilled wages should be examined. Since the analysis included data that is over fifty years old, extrapolating the findings into the current time period becomes less applicable and less desirable.
Public Administrators will have to look at other root causes of poverty. Evidence suggests that addressing poverty through increased spending is only part of the solution. Other factors such as the educational and skill levels of the impoverished should be examined.
Studies have suggested that increasing educational levels of those with lower income can reduce poverty. It has also been suggested that increasing the skill levels of individuals contributes to reduced poverty. Future studies should include education levels and employment rates for poverty analysis. The influence of faith-based institutions participating in welfare aid should also be examined.
This report found “mixed evidence” about the relationship between welfare spending and the poverty rates. Increased welfare spending reduced poverty rates more significantly in the first half of the time period studied as compared to the last ten years of the analysis. Future analysis should analyze the time period from the year 2000 through 2029 to allow for generalizations and inferences that are more applicable to the time frame.
Brady, D., Fullerton, A., & Cross, J.(2009). Putting poverty in political context: a multi-level analysis of adult poverty across 18 affluent democracies. Social Forces. 88(1): 271-300. University of North Carolina Press.
Chantrill, C. (2011). U.S. welfare spending chart. Retrieved from: http://www.usgovernmentspending.com/
Fording, R.C., & Berry, W.D. (2007). The historical impact of welfare programs on poverty: Evidence from the American states. The Policies Study Journal. 35(1): 37-60.
Garner, T. I. (2011). Supplemental poverty measure thresholds: Laying the foundation. Bureau of Labor Statistics. 0-33. Retrieved from: http://www.census.gov/hhes/povmeas/methodology/supplemental/research/ASSAGarner%20Poverty%20Thresholds%20paper%2012-29-10.pdf
O'Boyle, E. J.(1990). Poverty: A concept that is both absolute and relative because human beings are at once individual and social. Review of Social Economy. 48(1): 2-17.
Rathge, R. & Olson, K. (2006). North Dakota case study: Perceived income and poverty contradiction. North Dakota State University Data Center. Retrieved from: http://www.ndsu.nodak.edu/sdc/toolbox/NDSDC_CaseStudyOne.pdf
Roberts, F. & Roberts, D. (2011). Statistics 2: How well does the regression equation truly represent the set of data? Retrieved from: http://mathbits.com/MathBits/TISection/Statistics2/correlation.htm
Schram, S. F. (1991). Welfare spending and poverty: Cutting back produces more poverty, not less. The American Journal for Economics and Sociology. 50(2): 129-141.
Stark, Barbara. (2009). Theories of poverty/the poverty of theory. Brigham Young University Law Review. No. 381-425, 2009; Hofstra Univ. Legal Studies Research Paper No. 10-20.
U.S. Census Bureau (2007). 2007 economic census: Reliability of data. Retrieved from: http://www.census.gov/econ/census07/www/methodology/reliability_of_data.html
U.S. Census Bureau. (2011). Small area income and poverty estimates: state and county interactive tables. Retrieved from: http://www.census.gov//did/www/saipe/county.html
United States Federal State and Local Government Spending (2011). Welfare. Retrieved from: http://www.usgovernmentspending.com/numbers
David Ortega (author) from Altoona, Iowa on October 21, 2014:
tsadjatko-I am sure your sentiments are shared. If you take a look at the last few years of the graph, it shows what appears to be an increase in welfare spending while at the same time an increase in poverty. More data is needed to study the relationship between the two variables. I could scientifically test the hypothesis that in the last ten years an increase in welfare spending has resulted in an increase in poverty.
The Logician from then to now on on October 17, 2014:
Why would anyone even think an increase in welfare spending would decrease poverty? To begin with the first thing that needs to be analyzed is exactly how welfare spending is spent. So much is lost to fraud & bureaucrats!
According to the U.S. Department of Labor statistics website, based on the 2012 IPIA three-Year average data report, fraud was prevalent in 2.67% of cases.
According to a report by the Department of Health and Human Services, bureaucracy has been steadily increasing as benefits have been declining. Almost 30% of welfare spending is eaten up by bureaucracy...http://i55.tinypic.com/2rwojno.jpg
My bet is there is much more wasteful spending on welfare than any government figures will reflect because people (like government bureaucrats and crooks) are doing very well from welfare spending but it's not the poor.