Poverty Line

This paper takes an extensive look at poverty in the modern, industrialized world. Specifically, the essay looks at the ways in which societies measure and gauge poverty.

Keywords Absolute Measure; Hardship Measure; Poverty Measure; Relative Measure; Social Capital

Sociology > Stratification & Class in the U.S. > The Poverty Line

Overview

According to Confucius, who is considered by many to be one of history’s greatest philosophers, attention to the poor is essential to a system's overall success. "In a country well-governed, poverty is something to be ashamed of," he said. "In a country badly governed, wealth is something to be ashamed of" ("Confucius" 2007).

Indeed, in every society, there are three general strata of economic class. In the upper class are the wealthy citizens, whose financial incomes make life comparatively easy. For middle-class citizens, however, money and access to the best programs and services are not as easily obtained — they do, on the other hand, experience a modicum of stability.

In the third class, income is minimal, access is limited, and social mobility is rare. For those who live below the poverty line, life is wrought with anxiety and uncertainty. This paper takes an extensive look at poverty in the modern, industrialized world. Specifically, the essay looks at the ways in which societies measure and gauge poverty.

Understanding Poverty

In order to gauge poverty in the postindustrial era, one must be able to define it. According the United Nations High Commissioner for Human Rights (UNHCR), poverty is "a human condition characterized by the sustained or chronic deprivation of the resources, capabilities, choices, security, and power necessary for the enjoyment of an adequate standard of living and other civil, cultural, economic, political, and social rights" (UNHCR, 2002).

The causes of poverty stem from two main arenas.

• First, the individual himself or herself, by his or her own action or inaction, does not seek access to or take advantage of the resources and services he or she needs to bolster personal income and move a state of poverty.
• Second, the government or relevant political institutions (or in the cases of war-torn nations, a lack thereof) fails to provide to impoverished individuals the access or means by which they may gain access to the aforementioned programs, resources, and services that would enable them to pull themselves out of poverty.

Social Capital

Absent for the impoverished citizen is social capital. Social capital refers to the institutions, networks, and resources that are integral to the development and maintenance of a society's interactions. Social capital, according to the World Bank, is manifest in five key dimensions. The first of these areas is that of groups and networks, in which individuals collectively form and maintain interpersonal relations. Second is solidarity, which fosters cohesion and stronger collective action. The third arena is collective action and cooperation, in which groups of people work together to resolve issues within their community. Fourth is social cohesion and inclusion, which helps mitigate conflict, promotes equitable distribution of benefits and encourages participation of marginalized groups. Finally, information and communication enables social groups to gain access to the data and resources they need to collectively advance (World Bank Group, 2008).

The structural framework of social capital described above indicates that poverty is not simply a matter of a lack of financial resources. It is a lack of community cohesion, information, networking opportunities, and other resources that will enable upward mobility. Social capital is not a concept that is localized to one particular social stratum, however. Ideally, it exists in some form on every social level. However, certain types of social capital may be more conducive to strengthening a given class. One study, for example, identifies two manifestations.

• The first of these examples is horizontal social capital, which are incarnations of the framework above that operate solely within a socioeconomic or cultural stratum.
• The second is vertical social capital — for this version, the above-mentioned framework is applicable and uniform from the highest to the lowest socioeconomic strata (Lewandowski, 2008). Poverty is evident within this latter context, as it entails the absence of the very same forms of social capital that exists in higher strata.

Relying on Statistics

Orshansky's Poverty Measure

In the early 1960s, the United States Social Security Administration (SSA) began publishing poverty statistics based on a model derived by economist Mollie Orshansky. Orshansky assessed the average diet for a family and multiplied it by three in order to create an effective buffer (thereby allowing for additional expenses). Comparing it to the before-tax income necessary to afford such expenses, the SSA turned the resulting figure to the US Census Bureau, which would compile the information of households that fit this profile. The poverty measure, as the model is known, has been used consistently over time by government agencies and leaders to craft policy responses to rises in poverty rates in a given population. Such responses include the availability of federal, state, and local assistance programs, tax reductions, and other public services.

The poverty measure has proven to be the gauge of choice for policymakers to monitor instances of poverty within their constituency. Researchers and even the media have also looked at this measuring stick as a vital resource in combating poverty. Then again, as populations grow more diverse to include different racial and ethnic groups, geographic variations (such as rural areas versus urban neighborhoods) and even age group differentials, it becomes more vital that the tools employed to monitor poverty are fully reliable (Citro & Murphy, 1995).

Dangers of Incomplete Data

There is an issue at hand in measuring poverty based on statistical analysis and census data; by relying on voluntary individual responses to surveys, the agency is at risk of receiving significantly incomplete data. Failure to adequately count the number of impoverished individuals in a given population could lead to woefully inadequate government antipoverty funding and programming. A pivotal 1995 report by the National Academy of Sciences offered twelve alternatives to the official poverty measure, taking into account varying definitions of family income and poverty thresholds as opposed to the more rigid Orshansky formula.

Additional Factors to Consider

The alternatives did not seek to replace the present poverty measure but to offer some additional factors worthy of consideration in expanding the definition of poverty in the United States. Among the suggestions was using actual costs for food, clothing, and shelter rather than basing expenditures on an estimated budget for such costs. Also, the study recommended adjusting the poverty level to account for family size and for geographic differences in housing costs. Furthermore, the panel suggested including government food and housing benefits that do not come in the form of a cash payment, as well as tax credits such as the Earned Income Tax Credit (EITC) in calculations of individual and household income. On the expense side, the National Academy of Science (NAS) report recommended that mandatory costs such as taxes, work expenses, child care costs, child support, and out-of-pocket medical costs be included in the calculation process (Porter, 1999).

In the aggregate, the proposed adjustments to the poverty measure provide greater clarity to the true state of poverty. In fact, it appears that such proposals would add greater accuracy. According to one study, if employed within the poverty measure, all twelve measures would have produced a higher poverty level (in some cases, 2 percent more) than the existing formula ("The troubling…," 2007).

The Determination of More Accurate Poverty Levels

Such an underestimation can have significant impacts both on economies and nations. While in the United States, for example, the official federal poverty rate in 2013 was 14.5 percent, meaning there were 45.3 million Americans living poverty (DeNavas-Walt & Proctor, 2014, p. 12), many reports estimate the figure to be higher. Such undercalculation has already had an impact on federal education funding on programs such as Medicaid (the federally funded health care program), Temporary Assistance for Needy Families (TANF), and the EITC (US General Accounting Office, 2007).

Since 1995, the NAS report has been embraced but never implemented on a federal level. There are, after all, political forces at work in any given governmental system, and for one such entity to adjust its formula to reflect that there are actually more poor people living under its charge than previously reported, anxiety about backlash is not without merit.

In the absence of a federal (or, for that matter, state-level) policy response to the NAS report, the same problems in accurately measuring poverty in the United States continued. However, a number of major metropolitan centers, all of which were on the front lines in a "war on poverty," took steps to incorporate the twelve proposals into their own methodologies for determining the number of impoverished residents within city limits.

In July 2008, for example, the city of New York began taking into account the cost of living in the city as a major factor in quantifying its poor residents. As a result, the number of poor in that city rose markedly, from 19 percent of the population to 23 percent. The poverty line increased by about $6,000, also a major increase. With the poverty rate increased, the number of extreme poor residents dropped, but the population of working poor increased. The most shocking result was revealed in one key demographic — whereas the federally determined rate of elderly poor in New York City was officially marked at 18 percent, under the new formula, the city's estimate was 32 percent ("The Big Apple," 2008). By 2012, the city’s calculation for the poverty rate and the official federally determined rate were much closer: 21.4 percent versus 20 percent ("The CEO Poverty Measure," 2014, p. 11).

In light of the New York example, other cities have looked to make similar modifications to their poverty measurement formulae. The stakes are significant — urban areas are suffering drains in services, and without a fully relevant set of figures on which to rely for targeting limited municipal funds, the cities are concerned with inadvertently wasting money.

Supplemental Poverty Measure

In 2010, the Census Bureau adopted the supplemental poverty measure (SPM) to enhance its reporting on poverty in the United States. The SPM was derived from the NAS report as well as research findings from the years since its publication (US Census Bureau, 2014). Although the SPM offers more robust data, using actual expenditures for necessities like housing as well as information on direct transfers and noncash government benefits, it only supplements but does not replace the Orshansky formula as the official method of determining poverty, and thus it does not affect eligibility to receive governmental assistance (Short, 2014; US Census Bureau, 2014). The SPM poverty rate for 2013 was 15.5 percent, or 48.7 million people (Short, 2014).

The Many Faces of Poverty

As suggested above, there is far more to the composition of a system's impoverished population than simple income. However, much of policymakers' approach to addressing poverty has been hinged on income and expenses. The failure of many policy responses to adequately address poverty provides an indication of the shortcomings of this approach.

The shortcomings of income-based poverty measurement suggest that other considerations about the profile of poverty (and the venues in which it occurs) must be given light.

The argument can be made that there are two general approaches to measuring poverty. Earlier in this essay, the reliance on a standard poverty measure in the United States provides policymakers and advocates with a simple formula to assess the state of poverty. This "absolutist" approach sets rigid standards by which the reviewer may interpret direct data. However, as shown here, there are deficiencies to the absolutist approach, in that other, the exclusion of non-income factors leads to underreporting the true breadth of an impoverished population.

Relative Poverty Measures

Costs of Living

On the other hand, "relative" poverty measures reveal the more abstract side of poverty's manifestations. Whereas the United States' absolutist poverty measure takes into account income and an estimate of how much food might be consumed by a subject family, a relativist view determines how much that food might cost in the given system. From country to country, the varying costs of living clearly indicate that one standard may not be entirely reliable. The price of beef in Japan, for example, is considerably higher than it is in the United States due to the fact that it must be imported to Japan. Similarly, war-torn and environmentally ravaged nations will likely see greater costs for wheat and other staples.

Currency

In fact, the strengths and weaknesses of a given currency are also factors that may directly countermand an absolute poverty measure. The World Bank (2015), for example, uses a poverty standard of $1.25 per day as its determinant for extreme poverty status. However, if there is no flexibility in the standard and the value of the dollar changes, there may be a great many more people who should, under the aforementioned standard, be classified below the poverty line.

Geography

The region where people live adds to variances that must be accounted for in the measurement of poverty. As suggested earlier, geography plays an important role in the types of services for which a family must pay. In fact, geography is a major factor in not just the services a family may receive but in the basic necessities it must obtain. Relevant to this arena are so-called "hardship measures." Among hardship measures are the costs of health care, drinking water, housing, food, and heating or cooling, which vary based on the region. People may have to travel much greater distances than others to obtain these resources, and doing so is usually a greater expense (Iceland, 2005).

Additional Factors

As differences in geographic regions create variables for which absolute poverty measures do not account, another factor further adds to the issue. Many regions have their own internal elements that foster or maintain poverty. Some, for example, are racial or ethnic in nature. Entering a new country means learning languages and cultural norms. One example is not dissimilar from the issue of currency exchange — an individual who is trained or educated in his or her country of origin may find those skills woefully inadequate in his or her new home — without the money to obtain a new education, the individual may find minimal employability. Racism, sexism, ageism, ableism, and other forms of discrimination have also been shown to have a significant effect on pushing minority groups toward poverty.

Investigating Poverty within Social Groups

One study of Canadian poverty provides a new form of poverty measurement. Noticing that the poverty within Canada's population is locatable within certain demographic communities and geographic neighborhoods, the authors investigated poverty levels of 2,400 such enclaves rather than studying individuals, case samples, or aggregate figures. Their focus on First Nations and immigrant communities revealed invaluable information about the inner workings of these groups, underscoring the factors that contributed to their poverty, such as economic conditions, income, and a wide range of other socioeconomic factors endemic to impoverished social groups. In tracking these individual communities instead of entire populations or small segments thereof, the authors were able to gauge how effective antipoverty policies would be when applied — the study's community-based measure revealed that income rates are affected by economic conditions in the short term, but that over time, demographic factors (such as ethnicity, race, age, and education) become much more significant contributors to poverty (and its mitigation) over the longer term (Chokie & Partridge, 2008).

Based on the examples provided in this section, there are a wide range of sociological, geographic, and demographic factors that contribute to poverty rates in addition to income levels and expenses. Tracking such elements may present a clearer picture of poverty around the globe.

Conclusion

William Sydney Porter, better known by his pen name, O. Henry, was well known for popularizing the short story form. "Love and business and family and religion and art and patriotism are nothing but shadows of words when a man's starving," he once wrote (O. Henry, 1904).

Every society in the modern world is home to people who simply cannot afford to live within that system without some form of outside assistance.

It is for this reason that societies have sought the most effective measures by which to gauge the rate of poverty within their given systems. During the Lyndon Johnson administration in the 1960s, the United States crafted one such mechanism in the poverty measure. Similar measures have been introduced in other countries. The primary foci of the poverty measures have been income and certain household expenses. Such delineations have proven somewhat effective in at least illustrating the approximate size of the impoverished members of a given society.

However, poverty is not limited to income. Many impoverished people are in their current situations because of where they happen to live, the level of education to which they have access, their employability, and other factors. As this paper has demonstrated, understanding and measuring poverty is not as simple as analyzing one set of data. Poverty and its causes are multidimensional, and measurement of it must also occur on a number of fronts.

Poverty on the local, state, national, and international levels clearly necessitates further study. While some systems continue to use to income and other inadequate socioeconomic data in order to implement effective policy responses, there is an increasing school of thought that is dedicated to studying poverty outside of those limited parameters. In doing so, those who adhere to this approach are providing the rest of the world with invaluable information about poverty and how to eliminate it.

Terms & Concepts

Absolute Measure: System of analysis in which data parameters are fixed and static.

Hardship Measure: Mode of study that analyzes issues such as access to basic human needs.

Poverty Measure: Formulaic standard for measuring poverty created by sociologist Mollie Orshansky.

Relative Measure: Standard of poverty measurement that includes sociological factors, demographics, and geography as part of the supporting data.

Social Capital: The institutions, networks, and resources that are integral to the development and maintenance of a society's internal interactions.

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Suggested Reading

Betti, G., & Verma, V. (2008). Fuzzy methods of the incidence of relative poverty and deprivation: A multidimensional perspective. Statistical Methods & Applications, 17, 225–250. Retrieved August 4, 2008, from EBSCO Online Database Business Source Premier. http://search.ebscohost.com/login.aspx?direct=true&db=bth&AN=31695156&site=ehost-live

Chen, S., & Ravallion, M. (2007). Absolute poverty measures for the developing world, 1981-2004. Proceedings of the National Academy of Sciences of the United States of America, 104, 16757–16762. Retrieved August 4, 2008, from EBSCO Online Database Academic Search Premier. http://search.ebscohost.com/login.aspx?direct=true&db=aph&AN=27430122&site=ehost-live

Jo, Y. N. (2013). Psycho-social dimension of poverty: when poverty becomes shameful. Critical Social Policy, 33, 514–531. Retrieved November 5, 2013 from EBSCO online database SocINDEX with Full Text. http://search.ebscohost.com/login.aspx?direct=true&db=sih&AN=89409941

Poverty's real measure. (2008, July 22). The New York Times, 18. Retrieved August 4, 2008, from EBSCO Online Database Academic Search Premier. http://search.ebscohost.com/login.aspx?direct=true&db=aph&AN=33246532&site=ehost-live

Primus, W.E. (2006). Reductions in poverty significantly greater in the 1990s than official estimates suggest. Review of Policy Research, 23, 781–797. Retrieved August 4, 2008, from EBSCO Online Database Academic Search Premier. http://search.ebscohost.com/login.aspx?direct=true&db=aph&AN=20858094&site=ehost-live

Rossi, M. M., & Curtis, K. A. (2013). Aiming at half of the target: An argument to replace poverty thresholds with self-sufficiency, or “living wage” standards. Journal of Poverty, 17, 110–130. Retrieved January 12, 2015 from EBSCO online database SocINDEX with Full Text. http://search.ebscohost.com/login.aspx?direct=true&db=sih&AN=84918175&site=ehost-live&scope=site

Tzavidis, N., et al. (2008). M-quantile models with application to poverty mapping. Statistical Methods and Applications, 17, 393–411. Retrieved August 4, 2008, from EBSCO Online Database Business Source Premier. http://search.ebscohost.com/login.aspx?direct=true&db=bth&AN=33005460&site=ehost-live