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estimated income elasticities in the range of 0.01 to 0.15, and Marquis et al. (2004) estimated

income elasticities of 0.03 to 0.04. In both studies, family income was measured relative to the

federal poverty level.

Differences (or changes) in income may have a greater effect on consumers’ in choosing

among different health plans, as opposed to their demand for insurance overall. Barringer and

Mitchell (1994) considered the effect of salary increases on choices between traditional FFS

plans and the prepaid plans offered by a large employer. They found that a 10 percent increase

in real salaries boosted demand for the traditional FFS plan by 1 to 2 percentage points, with

nearly commensurate disenrollment from the prepaid plans. Studying the military health system

(TRICARE, formerly known as CHAMPUS), Hosek et al. (1993) concluded that a 10 percent

increase in household income decreased the probability that a family would enroll in the HMO

option by 0.24 percentage points. (Ringel et al. (2002) translated this finding into an income

elasticity of demand for enrollment in HMOs of –0.27.) However, because both studies were

based on observational data, any number of unobserved factors correlated with both income and

insurance demand (such as health status) could have biased their estimates in either direction.


Among consumers who have access to free care, changes in income would not affect their

ability to obtain medical services. It follows that, among consumers with full insurance, the

income elasticity would be very small, if not zero (Ringel et al. 2002). Evidence from the very

few empirical studies of person-level data is consistent with this expectation. Based on results

from the HIE, Phelps (1992) calculated income elasticities of 0.2 or less.21 Reschovsky (1998)

21 In contrast, Hosek et al. (1993) found that an increase in income among military families reduced the probability of both outpatient visits and inpatient visits, as well as the number of outpatient visits in the military system. This result was likely due to switching among higher-income beneficiaries to nonmilitary health services,


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