The Role of Behavioral Frictions in Health Insurance Marketplace Enrollment and Risk: Evidence from a Field Experiment
icpsr_125801
Richard Domurat, Isaac Menashe, Wesley Yin (2021). American Economic Review
DOI: 10.1257/aer.20190823
| field | value |
|---|---|
| venue | American Economic Review |
| paper | 10.1257/aer.20190823 |
| replication data | openICPSR 125801 |
| data license | CC BY 4.0 — “This work is licensed under a Creative Commons Attribution 4.0 International (CC BY 4.0) License.” |
| regression datasets (in this corpus) | 3 |
| graduated / eligible / exported | 3 / 9 / 52 (policy claims_manual_regression_cap) |
| routed / gap / residue (at source) | 28 / 150 / 0 |
Claims & tasks
Every claim the paper makes in its main body about a parameter, joined to the benchmark task (dataset · coefficient) that captures it. The effect, s.e. and p are the captured regression's own reported values (the paper's Stata figures, carrying the paper's SE method); the row shows the paper's verbatim quote (page · exhibit), so you can confirm the regression matches what the paper says. The prominence column is the within-study inclusion signal (⭐ headline → primary → secondary). The sensitivity column is the privacy level of the most-sensitive variable in the regression (🔴 high / 🟠 medium / ⚪ low).
| # | prominence | sensitivity | claim | effect | s.e. | p | task | instance (dataset · coef) |
|---|---|---|---|---|---|---|---|---|
| C1 | ⭐ primary | 🔴 high | Among low-income consumers, letters making personalized subsidy and plan comparison information more salient raise enrollment slightly, indicating that some consumers are not fully aware of the magnitude of subsidy benefits. p. 1552 · Table 4, col 1 (Open enrollment (2)) |
+0.049 | 0.019 | 0.010 | Linear Regression | reg_13 · arm345n=32698 · d=78 |
| C2 | ⭐ primary | 🔴 high | “In the open enrollment sample, we observe a larger negative coefficient on the income × subsidy-reporting (Arm345) interaction, indicating that take-up falls more steeply when receiving subsidy information than the Basic Letter.” — p. 1564 “The difference in the coefficient estimates on Arm2 × FPL (× 100) and Arm345 × FPL (× 100) is only significant at the 0.169 level for the full sample, and 0.158 level for the open enrollment sample.” — p. 1564 Table 4, col 2 (OLS Open enrollment (2)) |
-0.004 | 0.010 | 0.686 | Linear Regression | reg_13 · arm2_subsidy_fplx100n=32698 · d=78 |
| C3 | ⭐ primary | 🔴 high | “In the open enrollment sample, we observe a larger negative coefficient on the income × subsidy-reporting (Arm345) interaction, indicating that take-up falls more steeply when receiving subsidy information than the Basic Letter.” — p. 1564 “As subsidies fall with income, the relative benefit of providing subsidy information also falls, further indicating that consumers misperceive their subsidies.” — p. 1552 “The difference in the coefficient estimates on Arm2 × FPL (× 100) and Arm345 × FPL (× 100) is only significant at the 0.169 level for the full sample, and 0.158 level for the open enrollment sample.” — p. 1564 Table 4, col 2 (OLS Open enrollment (2)) |
-0.015 | 0.008 | 0.053 | Linear Regression | reg_13 · arm345_subsidy_fplx100n=32698 · d=78 |
| C4 | primary | 🔴 high | Using either unadjusted or regression-adjusted models, we find no differences in overall take-up across the letter interventions, a result we revisit in subgroup analyses. p. 1561 · Table 3, col 2 (All (2)) |
+0.012 | 0.003 | 3.9e-05 | Linear Regression | reg_5 · arm2n=87394 · d=4 |
| C5 | primary | 🔴 high | Using either unadjusted or regression-adjusted models, we find no differences in overall take-up across the letter interventions, a result we revisit in subgroup analyses. p. 1561 · Table 3, col 2 (All (2)) |
+0.015 | 0.003 | 1.2e-06 | Linear Regression | reg_5 · arm3n=87394 · d=4 |
| C6 | primary | 🔴 high | Using either unadjusted or regression-adjusted models, we find no differences in overall take-up across the letter interventions, a result we revisit in subgroup analyses. p. 1561 · Table 3, col 2 (All (2)) |
+0.010 | 0.003 | 5.7e-04 | Linear Regression | reg_5 · arm4n=87394 · d=4 |
| C7 | primary | 🔴 high | Using either unadjusted or regression-adjusted models, we find no differences in overall take-up across the letter interventions, a result we revisit in subgroup analyses. p. 1561 · Table 3, col 2 (All (2)) |
+0.013 | 0.003 | 2.3e-05 | Linear Regression | reg_5 · arm5n=87394 · d=4 |
| C8 | primary | 🔴 high | While the differences across the Basic Letter and subsidy-reporting arms are not statistically different, the patterns are consistent with a hypothesis that providing more information beyond the uniform reminder, about personalized premium subsidies and plan options, further reduces information frictions for a population with low baseline awareness. p. 1563 · Table 3, col 6 (County referral (6)) |
+0.004 | 0.003 | 0.191 | Linear Regression | reg_9 · arm2n=43146 · d=4 |
| C9 | primary | 🔴 high | “For the County referral sample, we find that providing additional subsidy and plan information (Arms 3–5) beyond the Basic Letter (Arm 2) leads to higher take-up (column 6, and in column 8, where the percent impact of a given treatment arm on county referrals is obtained by adding the coefficients on its uninteracted and county referral-interacted terms).” — p. 1563 “While the differences across the Basic Letter and subsidy-reporting arms are not statistically different, the patterns are consistent with a hypothesis that providing more information beyond the uniform reminder, about personalized premium subsidies and plan options, further reduces information frictions for a population with low baseline awareness.” — p. 1563 Table 3, col 6 (County referral (6)) |
+0.007 | 0.003 | 0.014 | Linear Regression | reg_9 · arm3n=43146 · d=4 |
| C10 | primary | 🔴 high | “For the County referral sample, we find that providing additional subsidy and plan information (Arms 3–5) beyond the Basic Letter (Arm 2) leads to higher take-up (column 6, and in column 8, where the percent impact of a given treatment arm on county referrals is obtained by adding the coefficients on its uninteracted and county referral-interacted terms).” — p. 1563 “While the differences across the Basic Letter and subsidy-reporting arms are not statistically different, the patterns are consistent with a hypothesis that providing more information beyond the uniform reminder, about personalized premium subsidies and plan options, further reduces information frictions for a population with low baseline awareness.” — p. 1563 Table 3, col 6 (County referral (6)) |
+0.006 | 0.003 | 0.032 | Linear Regression | reg_9 · arm4n=43146 · d=4 |
| C11 | primary | 🔴 high | “For the County referral sample, we find that providing additional subsidy and plan information (Arms 3–5) beyond the Basic Letter (Arm 2) leads to higher take-up (column 6, and in column 8, where the percent impact of a given treatment arm on county referrals is obtained by adding the coefficients on its uninteracted and county referral-interacted terms).” — p. 1563 “While the differences across the Basic Letter and subsidy-reporting arms are not statistically different, the patterns are consistent with a hypothesis that providing more information beyond the uniform reminder, about personalized premium subsidies and plan options, further reduces information frictions for a population with low baseline awareness.” — p. 1563 Table 3, col 6 (County referral (6)) |
+0.007 | 0.003 | 0.026 | Linear Regression | reg_9 · arm5n=43146 · d=4 |
Regression datasets
The 3 regression dataset(s) graduated into the benchmark corpus from this study's replication package — each backs one or more claims above. Expand each for its features, response, (sound, data-independent) public bounds, and reproduction grade.
icpsr_125801_reg_13 — any_takeup ~ arm2 + arm345 + subsidy_fplx100 + arm2_subsidy_fplx100 + arm345_subsidy_fplx…
Sensitivity proposal: 🔴 high maximum across columns (advisory; reviewed manually).
Reproduction grade: ✅ match (benchmark-eligible).
Features
| name | description | type | sensitivity | bound lo | bound hi | estimate | s.e. |
|---|---|---|---|---|---|---|---|
_cons |
intercept | continuous | — | 1 | 1 | +0.1776 | 0.0345 |
arm2 |
Basic Letter treatment arm indicator | continuous | ⚪ low | 0.0 | 1.0 | +0.02451 | 0.0235 |
arm345 |
subsidy-reporting arms (3-5) combined indicator | continuous | ⚪ low | 0.0 | 1.0 | +0.04947 | 0.0192 |
subsidy_fplx100 |
household income as percent of poverty line | continuous | 🔴 high | — | — | -0.03622 | 0.00683 |
arm2_subsidy_fplx100 |
interaction of arm2 and income-to-FPL ratio | continuous | ⚪ low | — | — | -0.003948 | 0.00978 |
arm345_subsidy_fplx100 |
interaction of arm345 and income-to-FPL ratio | continuous | ⚪ low | — | — | -0.01539 | 0.00795 |
age_mean10 |
mean age scaled by dividing by 10 | continuous | 🟠 medium | 0.0 | 12.0 | +0.01512 | 0.00353 |
funnel_round |
enrollment funnel stage or round | categorical | ⚪ low | — | — | — | — |
latino |
Latino/Hispanic ethnicity indicator | continuous | 🔴 high | 0.0 | 1.0 | -0.0291 | 0.0118 |
asian |
Asian race/ethnicity indicator | continuous | 🔴 high | 0.0 | 1.0 | -0.003175 | 0.0162 |
black |
Black race/ethnicity indicator | continuous | 🔴 high | 0.0 | 1.0 | -0.04988 | 0.0218 |
otherrace |
other/unclassified race indicator | continuous | 🔴 high | 0.0 | 1.0 | -0.03621 | 0.0131 |
subsidy_hh_size |
household size used for subsidy calculation | continuous | 🟠 medium | — | — | -0.01848 | 0.00499 |
hh_members |
total number of household members | continuous | 🟠 medium | — | — | +0.03714 | 0.00862 |
hh_kids |
number of children in household | continuous | 🟠 medium | — | — | -0.005296 | 0.014 |
married_infer |
inferred marital status of household head | continuous | 🟠 medium | 0.0 | 1.0 | -0.01539 | 0.0135 |
hoh_email_ok |
indicator household head email deliverable | continuous | ⚪ low | 0.0 | 1.0 | +0.02734 | 0.00976 |
x7 |
unnamed covariate, meaning unclear | continuous | ⚪ low | — | — | -0.09798 | 0.00922 |
region |
geographic region of household residence | categorical | 🟠 medium | — | — | — | — |
arm2_age_mean10 |
interaction of arm2 and scaled age | continuous | ⚪ low | — | — | -0.004254 | 0.00504 |
arm2_funnel_round1 |
interaction of arm2 and funnel round dummy | continuous | ⚪ low | — | — | -0.01312 | 0.0287 |
arm2_latino |
interaction of arm2 and Latino dummy | continuous | ⚪ low | — | — | +0.01632 | 0.0169 |
arm2_asian |
interaction of arm2 and Asian dummy | continuous | ⚪ low | — | — | -0.01252 | 0.0231 |
arm2_black |
interaction of arm2 and Black dummy | continuous | ⚪ low | — | — | +0.01175 | 0.0319 |
arm2_otherrace |
interaction of arm2 and other-race dummy | continuous | ⚪ low | — | — | +0.04406 | 0.0193 |
arm2_subsidy_hh_size |
interaction of arm2 and subsidy household size | continuous | ⚪ low | — | — | -0.0003609 | 0.00754 |
arm2_hh_members |
interaction of arm2 and household size | continuous | ⚪ low | — | — | +0.0193 | 0.0126 |
arm2_hh_kids |
interaction of arm2 and count of kids | continuous | ⚪ low | — | — | -0.0207 | 0.0196 |
arm2_married_infer |
interaction of arm2 and inferred marriage | continuous | ⚪ low | — | — | -0.001573 | 0.0195 |
arm2_hoh_email_ok |
interaction of arm2 and email-valid flag | continuous | ⚪ low | — | — | +0.02222 | 0.014 |
arm2_x7 |
interaction of arm2 and covariate x7 | continuous | ⚪ low | — | — | +0.001242 | 0.0137 |
arm2_region1 |
interaction of arm2 and region 1 dummy | continuous | ⚪ low | — | — | -0.01619 | 0.0402 |
arm2_region2 |
interaction of arm2 and region 2 dummy | continuous | ⚪ low | — | — | +0.02035 | 0.0423 |
arm2_region3 |
interaction of arm2 and region 3 dummy | continuous | ⚪ low | — | — | +0.08286 | 0.0355 |
arm2_region4 |
interaction of arm2 and region 4 dummy | continuous | ⚪ low | — | — | +0.03644 | 0.0506 |
arm2_region5 |
interaction of arm2 and region 5 dummy | continuous | ⚪ low | — | — | +0.03371 | 0.0469 |
arm2_region6 |
interaction of arm2 and region 6 dummy | continuous | ⚪ low | — | — | -0.04446 | 0.0419 |
arm2_region7 |
interaction of arm2 and region 7 dummy | continuous | ⚪ low | — | — | +0.02395 | 0.0397 |
arm2_region8 |
interaction of arm2 and region 8 dummy | continuous | ⚪ low | — | — | +0.08631 | 0.0521 |
arm2_region9 |
interaction of arm2 and region 9 dummy | continuous | ⚪ low | — | — | -0.06338 | 0.0516 |
arm2_region10 |
interaction of arm2 and region 10 dummy | continuous | ⚪ low | — | — | +0.005626 | 0.0349 |
arm2_region11 |
interaction of arm2 and region 11 dummy | continuous | ⚪ low | — | — | -8.93e-05 | 0.0425 |
arm2_region12 |
interaction of arm2 and region 12 dummy | continuous | ⚪ low | — | — | +0.009812 | 0.04 |
arm2_region13 |
interaction of arm2 and region 13 dummy | continuous | ⚪ low | — | — | +0.01272 | 0.0623 |
arm2_region14 |
interaction of arm2 and region 14 dummy | continuous | ⚪ low | — | — | +0.01379 | 0.0409 |
arm2_region15 |
interaction of arm2 and region 15 dummy | continuous | ⚪ low | — | — | -0.02281 | 0.0307 |
arm2_region16 |
interaction of arm2 and region 16 dummy | continuous | ⚪ low | — | — | +0.01417 | 0.0287 |
arm2_region17 |
interaction of arm2 and region 17 dummy | continuous | ⚪ low | — | — | +0.00412 | 0.0285 |
arm2_region18 |
interaction of arm2 and region 18 dummy | continuous | ⚪ low | — | — | +0.06222 | 0.0304 |
arm345_age_mean10 |
interaction of arm345 and scaled age | continuous | ⚪ low | — | — | -0.004828 | 0.00411 |
arm345_funnel_round1 |
interaction of arm345 and funnel round dummy | continuous | ⚪ low | — | — | +0.006033 | 0.0236 |
arm345_latino |
interaction of arm345 and Latino dummy | continuous | ⚪ low | — | — | +0.01512 | 0.0136 |
arm345_asian |
interaction of arm345 and Asian dummy | continuous | ⚪ low | — | — | -0.009458 | 0.0188 |
arm345_black |
interaction of arm345 and Black dummy | continuous | ⚪ low | — | — | +0.0144 | 0.0256 |
arm345_otherrace |
interaction of arm345 and other-race dummy | continuous | ⚪ low | — | — | +0.0196 | 0.0153 |
arm345_subsidy_hh_size |
interaction of arm345 and subsidy household size | continuous | ⚪ low | — | — | +0.0001751 | 0.00582 |
arm345_hh_members |
interaction of arm345 and household size | continuous | ⚪ low | — | — | +0.01928 | 0.0101 |
arm345_hh_kids |
interaction of arm345 and count of kids | continuous | ⚪ low | — | — | -0.02565 | 0.0161 |
arm345_married_infer |
interaction of arm345 and inferred marriage | continuous | ⚪ low | — | — | -0.008004 | 0.0156 |
arm345_hoh_email_ok |
interaction of arm345 and email-valid flag | continuous | ⚪ low | — | — | +0.008148 | 0.0114 |
arm345_x7 |
interaction of arm345 and covariate x7 | continuous | ⚪ low | — | — | -0.0009506 | 0.0108 |
arm345_region1 |
interaction of arm345 and region 1 dummy | continuous | ⚪ low | — | — | +0.03477 | 0.0335 |
arm345_region2 |
interaction of arm345 and region 2 dummy | continuous | ⚪ low | — | — | +0.05366 | 0.0337 |
arm345_region3 |
interaction of arm345 and region 3 dummy | continuous | ⚪ low | — | — | +0.05729 | 0.0277 |
arm345_region4 |
interaction of arm345 and region 4 dummy | continuous | ⚪ low | — | — | +0.02097 | 0.0404 |
arm345_region5 |
interaction of arm345 and region 5 dummy | continuous | ⚪ low | — | — | +0.05891 | 0.0387 |
arm345_region6 |
interaction of arm345 and region 6 dummy | continuous | ⚪ low | — | — | +0.01602 | 0.0345 |
arm345_region7 |
interaction of arm345 and region 7 dummy | continuous | ⚪ low | — | — | +0.07378 | 0.0315 |
arm345_region8 |
interaction of arm345 and region 8 dummy | continuous | ⚪ low | — | — | +0.0476 | 0.0405 |
arm345_region9 |
interaction of arm345 and region 9 dummy | continuous | ⚪ low | — | — | -0.02604 | 0.0423 |
arm345_region10 |
interaction of arm345 and region 10 dummy | continuous | ⚪ low | — | — | +0.01042 | 0.0278 |
arm345_region11 |
interaction of arm345 and region 11 dummy | continuous | ⚪ low | — | — | -0.01166 | 0.0344 |
arm345_region12 |
interaction of arm345 and region 12 dummy | continuous | ⚪ low | — | — | +0.03206 | 0.0323 |
arm345_region13 |
interaction of arm345 and region 13 dummy | continuous | ⚪ low | — | — | +0.05625 | 0.0538 |
arm345_region14 |
interaction of arm345 and region 14 dummy | continuous | ⚪ low | — | — | +0.06772 | 0.0332 |
arm345_region15 |
interaction of arm345 and region 15 dummy | continuous | ⚪ low | — | — | +0.01612 | 0.025 |
arm345_region16 |
interaction of arm345 and region 16 dummy | continuous | ⚪ low | — | — | +0.02537 | 0.0231 |
arm345_region17 |
interaction of arm345 and region 17 dummy | continuous | ⚪ low | — | — | +0.02573 | 0.023 |
arm345_region18 |
interaction of arm345 and region 18 dummy | continuous | ⚪ low | — | — | +0.04953 | 0.024 |
Response
| name | description | type | sensitivity | bound lo | bound hi | estimate | s.e. |
|---|---|---|---|---|---|---|---|
any_takeup |
indicator household enrolled in health insurance | continuous | 🔴 high | 0.0 | 1.0 | — | — |
Public bounds (data-independent) sourced from: age_mean/10, age range 0-120; binary indicator; binary indicator; health-insurance enrollment outcome; binary indicator; marital status; binary indicator; race/ethnicity.
n = 32,698 samples.
icpsr_125801_reg_5 — any_takeup ~ arm2 + arm3 + arm4 + arm5
Sensitivity proposal: 🔴 high maximum across columns (advisory; reviewed manually).
Reproduction grade: ✅ match (benchmark-eligible).
Features
| name | description | type | sensitivity | bound lo | bound hi | estimate | s.e. |
|---|---|---|---|---|---|---|---|
_cons |
intercept | continuous | — | 1 | 1 | +0.08102 | 0.00207 |
arm2 |
Basic Letter treatment arm indicator | continuous | ⚪ low | 0.0 | 1.0 | +0.01243 | 0.00302 |
arm3 |
subsidy/plan-information letter arm indicator | continuous | ⚪ low | 0.0 | 1.0 | +0.01475 | 0.00304 |
arm4 |
subsidy/plan-information letter arm indicator | continuous | ⚪ low | 0.0 | 1.0 | +0.01036 | 0.003 |
arm5 |
subsidy/plan-information letter arm indicator | continuous | ⚪ low | 0.0 | 1.0 | +0.0128 | 0.00302 |
Response
| name | description | type | sensitivity | bound lo | bound hi | estimate | s.e. |
|---|---|---|---|---|---|---|---|
any_takeup |
indicator household enrolled in health insurance | continuous | 🔴 high | 0.0 | 1.0 | — | — |
Public bounds (data-independent) sourced from: binary indicator; binary indicator; health-insurance enrollment outcome.
n = 87,394 samples.
icpsr_125801_reg_9 — any_takeup ~ arm2 + arm3 + arm4 + arm5
Sensitivity proposal: 🔴 high maximum across columns (advisory; reviewed manually).
Reproduction grade: ✅ match (benchmark-eligible).
Features
| name | description | type | sensitivity | bound lo | bound hi | estimate | s.e. |
|---|---|---|---|---|---|---|---|
_cons |
intercept | continuous | — | 1 | 1 | +0.03575 | 0.00199 |
arm2 |
Basic Letter treatment arm indicator | continuous | ⚪ low | 0.0 | 1.0 | +0.003782 | 0.00289 |
arm3 |
subsidy/plan-information letter arm indicator | continuous | ⚪ low | 0.0 | 1.0 | +0.007246 | 0.00295 |
arm4 |
subsidy/plan-information letter arm indicator | continuous | ⚪ low | 0.0 | 1.0 | +0.006296 | 0.00294 |
arm5 |
subsidy/plan-information letter arm indicator | continuous | ⚪ low | 0.0 | 1.0 | +0.006569 | 0.00294 |
Response
| name | description | type | sensitivity | bound lo | bound hi | estimate | s.e. |
|---|---|---|---|---|---|---|---|
any_takeup |
indicator household enrolled in health insurance | continuous | 🔴 high | 0.0 | 1.0 | — | — |
Public bounds (data-independent) sourced from: binary indicator; binary indicator; health-insurance enrollment outcome.
n = 43,146 samples.