Income

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Almost 7 out of every 10 of individuals living to age 65 will require some long-term care (LTC) assistance.  Of these, over one-third will spend some time in a nursing home.  In general, however, the elderly strongly prefer home based LTC if possible.   “Mattimore and colleagues (1997) found that 30% of elderly survey respondents would rather die than enter a nursing home and an additional 26% indicated they were very unwilling to move to an institutional setting.”

A recent paper Goda, Golberstein and Grabowski (GGG hereafter) examines how permanent income shocks affect LTC utilization.

The estimation equation used is the following:

  • Uhi = βIh + δXh + ε

where U refers to a LTC utilization measure (e.g., nursing home, paid home health care, unpaid care), I is annual household Social Security Income, and X is a set of exogenous controls.

Identifying income and LTC choices independently is difficult.  Individuals with a high probability of needing LTC may more years or longer hours per year to accumulate additional assets to fund LTC expenses.  Ideally, identification requires an income shock that is exogenous to the individual’s labor market choices.  For that purpose, GGG rely on natural experiment known as the “Social Security Benefits Notch” to serve as an instrument for the income variable.  The authors define the Notch as follows:

“Prior to 1972, neither lifetime earnings nor post-retirement payments were indexed for inflation, but rather periodically adjusted by the Congress. In 1972, Congress amended the Social Security Act to provide automatic indexation of credited earnings for those workers who had not yet retired, which created an unanticipated windfall for workers from certain birth cohorts because of an error that led the prior earnings of these workers to be doubly indexed for inflation. The high rate of inflation over the following years led to a large increase in benefits for the affected cohorts. In 1977, Congress passed another law to eliminate the double indexation for future cohorts of retirees.  This law change created a large reduction in Social Security payments for those cohorts born in 1917 or later relative to the preceding cohorts. Importantly however, cohorts born prior to 1917 (near retirement in 1977) retained doubly indexed benefits under a grandfather provision. Taken together, these law changes and the high rate of inflation over the mid 1970s created a large and permanent difference in Social Security payments across birth cohorts, which came to be called the Social Security Benefits Notch.”

Econometrically, GGG use a dummy variable for being born in the notch years (i.e., 1915-1917).  To apply their model, the authors use data from the 1993 and 1995 waves of the Assets and Health Dynamics Among the Oldest Old (AHEAD).  The authors find that this instrument is weak for richer households who have at least a high school education, but much stronger for households whose heads have at least a high school diploma.  Due to this result, GGG limit the sample only households without a high school education.  Using this specification,  the authors find the following results:

…positive income shocks had a negative effect on nursing home entry, but a positive effect on the use of paid home care. Specifically, a $1,000 (or 10.2 percent) increase in annual Social Security income for those in this low-education group would decrease the likelihood of any nursing home use by 22%-30% (relative to mean) and increase the likelihood of receiving any paid home care use by 24%-34%. Social Security income was not systematically related to the receipt of any informal (unpaid) care across the different specifications.

At first glance, one might perceive that increased income leads to less nursing home care due to substitution for home health care.  Alternatively, higher income could improve health directly and thus lessen the need for institutionalized care.

One obvious mechanism by which increased income would decrease nursing home use is through disqualification of Medicaid eligibility.  The authors claim that assets rather than income are the key driver of Medicaid eligibility for nursing home care, but do not investigate how asset accumulation and the Social Security notch are related.

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Many economists have lamented that income inequality has grown over recent decades.  Although it is true that wage inequality has increased, compensation inequality may not have.  When I mention “compensation inequality,” I refer to the total package of compensation that a worker receives.  This includes wages, health insurance, 401(k) benefits, and other non-wage forms of compensation.  In previous posts, I have mentioned that once health insurance is taken into account, inequality may in fact be shrinking.

A recent NBER working paper by Burkhauser and Simon (2010) also shows that inquality is in fact decreasing once one taking into account health insurance costs.  This chart provides information on changes in income and total income between 1995 and 2008.  Income includes only raw wages, but “total income” also takes into account workers compensation in the form of health insurance.  The authors use this evidence to claim that “…ignoring the value of health insurance coverage will substantially understate the level of economic well being of Americans and its upward trend and overstate the level of inequality and its upward trend.”

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The WSJ Real Time Economics blog reviews a paper by Michael Lechner which finds that “sports-playing adults saw a boost in income of about 1,200 euros per year over 16 years when compared to their less active peers. That translates into a 5-10% rate of return on sports activities, roughly equal to the benefit of an extra year’s worth of education.” How can playing sports increase income?

The simplest mechanism is that playing sports increases one’s health level. Healthier people are less likely to get sick and more likely to be able to work to earn income. This health difference, however, only explains a portion of the income differential. Dr. Lechner claims that playing sports builds a social network which helps to increase pay (e.g., your friends are the ones who recommend you for jobs). In fact, Lechner finds that sports-playing men display a higher level of “social functioning” than did the less active men.

One worry of this study is that of reverse causation. If someone is very sick, they are not able to play sports. Further, if you are sick, you are probably less likely to engage in social activities. Thus, health–and not sports playing–may be a hidden, unobserved feature which may be driving these results.

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