Abstract
Efforts to evaluate the impact of programs designed to safeguard the well-being of older adults in the US are stymied by the absence of adequate tools to answer a key question: how much income is “enough” in later life? The purpose of this paper is to report on a new indicator of income adequacy designed to correct this measurement gap. The Elder Economic Security Standard Index (Elder Index) is a geographically specific measure of the cost of living independently for older adults aged 65 and over. This paper provides an overview of the development of the Elder Index, demonstrates the variability in Elder Index values both geographically and across different residential settings, and provides an illustration of how the Elder Index may be used in establishing differences in economic hardship across subgroups of older adults. The paper concludes with a discussion of the potential research and policy uses of this new measure.
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Notes
See, for example, a report of the Special Committee on Aging, US Senate (2010) focusing on Social Security modernization, referencing retirement income security, and the adequacy of retirement income, as goals and interests of the committee.
The Elder Index calculations assume that senior singles and couples live on their own, not with other family members such as grandchildren. As a result, expenses associated with minor children in the household, including childcare expenses, are not included in the Elder Index. For an example of how grandparent caregiving may modify a senior’s budget, see Padilla-Frausto and Wallace (2013).
We present expenditures for individuals living alone so that age of the householder is not confounded with size of the household in this comparison. Households headed by younger adults are larger, on average, than are households that are headed by older adults.
For low-income seniors, need-based supports and subsidies, such as SSI, SNAP, Medicaid, housing assistance programs and low-income Part D subsidies, may help to close the gap between resources and necessary expenses (see Russell 2009 for a description of these programs in Massachusetts). These subsidies are often highly variable by locality. A full evaluation of these important programs is beyond the scope of the current paper. However, to the extent that supports and subsidies are geographically variable in availability and eligibility rules, they may contribute in important ways to the variability across communities in the extent to which seniors experience economic hardship.
In 2011, 28 % of seniors aged 65 + lived alone, with another 38 % living independently with a spouse or partner only. The remaining 34 % lived in households that included other people (adults and/or children), or in group quarters, including institutions (calculated by the authors from the 2011 American Community Survey). In 2011, more than 900,000 seniors were primarily responsible for grandchildren living in the same home, amounting to roughly 1.5 % of adults aged 60 + . Estimating the Elder Index values for households in which grandchildren or other economically dependent family members may also reside is beyond the scope of the current study (but see Padilla-Frausto and Wallace 2013 for a discussion of grandparent families in California). As well, many seniors provide childcare and direct financial support to family members living in separate households, including adult children as well as grandchildren or other relatives. Expenses associated with support for non-household members are not included in the calculation of the Elder Index. .
In 2011, 52 % of US householders aged 65 + owned a home with no mortgage; 27 % owned a mortgaged home and 21 % rented (calculated by the authors from the 2011 American Community Survey using IPUMS data retrieved from Ruggles et al. 2010).
Many seniors rent an apartment with more than 1 bedroom. Nationally, the FMR value for a two-bedroom unit is 19 % higher than the one-bedroom value; seniors who choose a larger apartment size would face higher rents. In estimating owner costs, number of bedrooms is not taken into consideration. Owner calculations are based on senior homeowners regardless of size of the home, the majority of which include more than 1 bedroom. Elder Index values therefore estimate the cost for seniors to remain in their current owned home (owner estimates), or to rent a market-rate one-bedroom apartment (renter costs).
Although literature suggests that food prices vary across different communities in the US, insufficient data on geographic variability in food prices are available to support a county-level adjustment. To the extent that food costs are considerably higher in some areas of the US than in others, geographic difference in the Elder Index associated with food are minimized in this calculation.
Seniors living in areas with reliable, low-cost public transportation may be able to meet their transportation needs through a combination of public transportation, taxi service, ride sharing, and other public and private transportation options. Although these seniors would avoid the expense of maintaining and operating a private automobile, their transportation expenses could either be considerably lower than the Elder Index estimate (if they walk or obtain free transportation from neighbors, for example) or considerably higher (if they rely primarily on taxi service). For non-drivers, the transportation figure represents a reasonable average estimated expense. According to the 2011 American Community Survey, nationwide 86 % of householders aged 65 and older have at least one vehicle available to members of the household.
This calculation includes estimates for fuel, maintenance, insurance, depreciation, and associated taxes. It does not include the cost of acquiring or financing a new vehicle (http://www.irs.gov/pub/irs-drop/n-12-72.pdf). Gasoline is a volatile expense and may result in fluctuations in cost of living throughout a calendar year. However, given the comparatively low number of miles driven in a year by most seniors, within-year volatility in gasoline costs has a small impact on total expenses. In 2011, the IRS made an unusual mid-year adjustment to the cost-per-mile value based on high gasoline prices, raising the rate to 55.5 cents per mile starting in July 2011. If we substitute the higher IRS per-mile rate in our calculations, and assume transportation costs of 55.5 cents per mile driven for the entire year, the national average Elder Index value for single renters would rise by 1.2 %.
For single seniors, assuming “excellent” health results in a decline in the Elder Index of 3.6 % (using the national Elder Index calculations), and assuming a senior in “poor” health results in an increase in the Elder Index value of 6.8 %.
This amount is equivalent to roughly 17 % of total estimated expenses being in the miscellaneous category, a percentage equivalent to that reported in an exhaustive examination of elder consumer expenditures conducted by the Social Security Administration (Social Security Administration 2007).
Note that formal long-term care—paid caregiving provided at home or in a nursing facility—is a sizable potential expense; see the report to the Congress submitted by the Commission on Long-Term Care, issued September 30, 2013 (www.ltccommission.senate.gov/index.cfm). These potential expenses are not included in our calculation of the elder budget because they are not a routine expense for community-dwelling seniors. Previous research indicates that even a low level of in-home caregiving provided by paid helpers can increase total annual expenses by a considerable amount (Russell, Bruce, Conahan, & Wider Opportunities for Women 2006). The majority of long-term care is provided informally by family members, neighbors and friends.
The average Social Security Benefit is calculated for older retirees. Data were retrieved from the US Social Security Administration website at http://www.ssa.gov/policy/docs/statcomps/oasdi_sc/2011/.
In Sumter County, Florida, the ratio of the average Social Security benefit for workers to the Elder Index for single renters is 83.8 %.
Total personal income includes all cash income, including means-tested benefits such as Supplemental Security Income. Personal income does not include in-kind transfers, such as the value of rental assistance or SNAP. The Medicare Part B premium is included in the calculation of the Elder Index ($115.40/month or $1384.80/year in 2011) because in the calculation of expenses we assume that all seniors purchase this coverage. However, because this premium is deducted from the Social Security check that beneficiaries receive, it is likely that this amount is not included in the income reported by respondents to the American Community Survey. 95 % of Part A beneficiaries in Medicare enroll in Part B (Kaiser Family Foundation 2010). To adjust for the fact that we include the premium expense in calculating the Elder Index value, but it is most likely not included in the income reports, we add $1,384.80 to individuals’ annual incomes before calculating the percentages reported in Table 4.
Within each county listed in Table 4, differences between younger and older age groups are statistically significant at α ≤ 0.05 level, except for Bexar County (TX) where age groups are not significantly different. In all counties shown, comparisons by gender, education, and work status are significantly different.
Whites are significantly different from Blacks at α ≤ 0.05 level in all counties shown. Significant differences between other race groups are identified in the footnotes of Table 4.
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Acknowledgments
The authors acknowledge colleagues at Wider Opportunities for Women, Laura Henze Russell, and the research assistance of Ngai Kwan, Lauren Martin, Henry Montas, and Michele Tolson. The financial support of Atlantic Philanthropies, The Boston Foundation, and the Retirement Research Foundation is gratefully acknowledged.
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Mutchler, J.E., Shih, YC., Lyu, J. et al. The Elder Economic Security Standard Index™: A New Indicator for Evaluating Economic Security in Later Life. Soc Indic Res 120, 97–116 (2015). https://doi.org/10.1007/s11205-014-0577-y
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DOI: https://doi.org/10.1007/s11205-014-0577-y