TABLE 2—
Evidence of Nonprice Effects on Take-Up, by Qualitative Feature
| Program | Study | Method of Identification | Statistical Significance and Effect Size | Notes |
| Program Benefit–Statistically Significant Effects | ||||
| Unemployment insurance | Anderson and Meyer26 (1997) | Longitudinal with exogenous variation | A 1.0–1.5 percentage point decrease in take-up from 10% decrease in after-tax benefits. | |
| Unemployment insurance | Blank and Card10 (1991) | Longitudinal (state-level) | A 1% increase in the state replacement rate causes a 1.6% increase in the take-up rate. | |
| Housing benefits in UK | Blundell et al.29 (1988) | Cross-sectional | A 0.52 percentage point increase per 1% increase in benefit size. | |
| Medicaid as supplemental insurance | Ettner32 (1997) | Cross-sectional | Elderly with chronic functional limitations 4 times likelier to take up Medicaid as supplemental insurance. | Effect could be interpreted as owing to better information about program because of greater contact with medical providers. |
| Child SSI | Garrett and Glied27 (2000) | Longitudinal with natural experiment | Change in eligibility rules results in a 0.427 percentage point increase in take-up per $100 increase in maximum SSI benefit. | Value of the benefit is identified by the extent that a higher SSI benefit increases the take-up effect of the eligibility expansion. |
| AFDC | Moffitt21 (1983) | Cross-sectional (structural) | Participation rose by 11 percentage points from an increase in benefits to a national minimum of 65% of the poverty line. | |
| Program Benefit–Insignificant, No Significance Test Provided, or Both | ||||
| Food stamps and AFDC | Blank and Ruggles9 (1996) | Cross-sectional | No statistical test. Length of eligibility or “need” an important determinant of take-up. | Longitudinal analysis used in study, but the effects of interest for us were identified cross-sectionally. |
| Earned income tax credit | Scholz7 (1994) | Cross-sectional | Insignificant (borderline). | Author states that magnitude is consistent with substantial effect but is not statistically significant. |
| Medicaid as Medigap (QMB) | Yelowitz28 (2000) | Longitudinal with natural experiment | Insignificant. Change in eligibility rules results in a 0.427 percentage point increase in take-up per $100 increase in maximum SSI benefit. | Value of benefit is identified by the extent that hospitalization increases the take-up effect of the eligibility expansion. |
| Program Benefit–Reverse Sign, Significant Results | ||||
| Subsidized health insurance | Diehr et al.30 (1996) | Cross-sectional | Sign the reverse of what was expected. | Those with poorer health status and greater prior health care usage less likely to take up insurance. |
| Inconvenience | ||||
| Income support (UK) | Duclos33 (1995) | Cross-sectional (structural) | Unobserved inconvenience costs could be as much as 20% of benefit level. | Indirect proxies for inconvenience could proxy for other factors. |
| Private pensions | Madrian and Shea25 (2000) | Longitudinal with natural experiment | Statistically significant 49 percentage point increase in 401(k) participation due to change to presumptive enrollment. | Dramatic effect, but it may be due more to psychological factors than literal convenience. |
| SSI | McGarry14 (1996) | Cross-sectional | Mixed statistical significance. Car owner: insignificant; same MSA: marginally significant; poor health: significant. | Car ownership, same MSA, and poor health all considered proxies for convenience. No marginal effects calculated. |
| Earned income tax credit | Scholz7 (1994) | Cross-sectional | Statistically significant. Having no state income tax system lowers take-up by 7.6 percentage points. | |
| Medicaid | Stuber et al.31 (2000) | Cross-sectional | Statistically significant. Perceiving forms as long and complicated implies 1.8 times less likely to take up Medicaid. Perceiving hours as inconvenient implies 1.7 times less likely to take up. | Nongeneralizable sample. |
| Stigma and Cultural Attitudes–Statistically Significant Effects | ||||
| Food stamps | Daponte et al.24 (1998) | Survey questioning those who are eligible but not receiving | 6.3% of eligibles not receiving cite stigma as a reason. | |
| SSI | McGarry14 (1996) | Cross-sectional | Mixed significance; other welfare programs highly statistically significant; South (cultural proxy), not significant. | No marginal effects calculated. |
| AFDC | Moffitt21 (1983) | Cross-sectional structural model estimation | Statistically significant; Stigma is a structurally identified and unitless function of race, education, and family size. | Interpretation as stigma is problematic. |
| Medicaid as long-term care insurance | Norton34 (1995) | Comparison of the distribution of time to spend down with the distribution of times to spend down predicted by a separate survey of assets and income | Longer times to spend down than are predicted by assets, implying that residents are receiving asset transfers to avoid Medicaid. | Interpretation as stigma is problematic. Effect could be due to fear of worse treatment because of lower provider payments for Medicaid residents. |
| Stigma and Cultural Attitudes–Insignificant and No test Results | ||||
| Medicaid | Stuber et al.31 (2000) | Cross-sectional | Nongeneralizable sample | |
| AFDC | Horan and Austin19 (1997) | Cross-sectional | Small sample size; poor proxies for stigma | |
| Informational Barriers–Statistically Significant Effects | ||||
| Unemployment insurance | Blank and Card10 (1991) | Longitudinal (state-level) | A 1% increase in the state unionization rate causes a 0.67% increase in the take-up rate. | Unionization is a poor proxy for informational barriers. |
| Food stamps | Daponte et al.24 (1998) | Randomized experiment | 36 percentage point increase in take-up due to information provided. | Preintervention distribution of information appears to be endogenous: those with greatest potential benefit unlikely to be uninformed. |
| Supplemental grant support (social fund) (UK) | Huby and Whyley35 (1996) | Cross-sectional | Those who have heard about program from friends or family are 7.4 times more likely to apply. | |
| Qualified Medicare Beneficiary program (QMB) | Neumann et al.36 (1995) | Cross-sectional | 20 percentage point increase in take-up due to awareness; 60% of those eligible and with knowledge of program take up; 40% of those eligible and unaware of program take up. | Medicare beneficiaries merged with Medicare and QMB and Medicare data. Beneficiaries asked about awareness of program. Substantial take-up by those unaware of program suggests importance of providers in take-up. |
| Medicaid | Stuber et al.31 (2000) | Cross-sectional | Confusion about Medicaid eligibility rules implies 1.8 times less likely to take up. | |
| Medicaid as Medigap (QMB) | Yelowitz28 (2000) | Cross-sectional | Greater effect of lagged eligibility than current eligibility indicates the possible effect of learning over time. | Relative contributions of lagged eligibility indicate role of learning over time. |
Note. SSI = supplemental security income; AFDC = Aid to Families With Dependent Children; QMB = Qualified Medicare Beneficiary program; MSA = metropolitan statistical area.