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Field
Trial Start Date
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Before
June 09, 2026
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After
June 15, 2026
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Field
Trial End Date
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Before
October 15, 2026
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After
July 01, 2027
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Last Published
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Before
June 15, 2026 09:52 AM
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After
June 23, 2026 01:37 PM
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Field
Intervention Start Date
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Before
June 09, 2026
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After
June 15, 2026
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Intervention End Date
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Before
October 15, 2026
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After
July 01, 2027
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Field
Primary Outcomes (Explanation)
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Before
The Medicare plan recommendation is measured as whether the intermediary recommends Medicare Advantage or Original Medicare plus Medicare Supplement (Medigap). We also measure the intermediary's belief about how much different Medicare beneficiaries would be willing to pay (in $ monthly premium) to have Original Medicare plus Medigap instead of a $0-premium Medicare Advantage plan. This allows us to put the value of the plan recommendation in monetary terms.
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After
The Medicare plan recommendation is measured as a binary indicator of whether the intermediary (agent/broker) recommends Medicare Advantage or Original Medicare plus Medicare Supplement (Medigap). We also elicit the intermediary's belief about how much different Medicare beneficiaries (presented as hypothetical profiles) would be willing to pay (in dollars per month) to have Original Medicare plus Medigap instead of a $0-premium Medicare Advantage plan. This allows us to put the value of the plan recommendation in monetary terms.
We use two methods to elicit WTP for Original Medicare + Medigap for a beneficiary profile constructed to be a strong fit for Medigap: (1) a single aggregate plan-level WTP, and (2) an attribute-level elicitation where the beneficiary's perceived WTP is elicited for each MA and Medigap plan attribute and summed. Our primary welfare measure uses the attribute-level build-up (2) since studies have shown that aggregate reports risk omitting plan components the intermediary does not recall when valuing the option. We use the aggregate WTP measure primarily to test how our main randomized statement influences the perceived WTP of the beneficiary. We interpret the attribute-level WTP as the more accurate "true" welfare measure and the aggregate WTP as perceived client demand, however, we will report both measures.
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Field
Experimental Design (Public)
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Before
Licensed Medicare insurance intermediaries (agents and brokers) are recruited through a B2B commercial respondent panel. We may also recruit participants from other online survey platforms or distribute the survey through online forums commonly used by Medicare intermediaries. After screening and consent, respondents answer background questions about their business practices and evaluate a series of hypothetical client profiles. We also elicit beliefs about consumers' valuations of different Medicare plan features.
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After
Licensed Medicare insurance intermediaries (agents and brokers) are recruited through a B2B commercial respondent panel, online survey platforms, online forums commonly used by Medicare intermediaries, publicly available intermediary websites and email addresses, and other online distribution channels. After screening and consent, respondents answer background questions about their business practices and evaluate a series of hypothetical client profiles. We also elicit beliefs about consumers' valuations of different Medicare plan features and common business practices in the Medicare market.
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Field
Planned Number of Observations
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Before
300-500 individual responses.
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After
We plan to collect between 150 and 400 observations, depending on recruiting success. We plan to screen for bots, duplicate flags, low-quality or low-effort responses (e.g., always reporting the same answer, always selecting the same right or left-hand side for multiple-choice questions), responses with logical contradictions, and unusually low completion times. These responses will be excluded from the analysis. We also include an attention check question in the second half of the survey. Since this question is late in the survey, we intend to use this as an internal measure of response effort. We believe these responses will still offer valuable information and plan to keep responses that fail the later attention check, but we will report results with and without the failed responses. After screening, we expect the final number of responses to be between 100-300, but will ultimately depend on the response quality and recruitment success. Conditional on funding and recruitment success, we may collect additional responses to make sure we are powered for heterogeneity analysis by baseline characteristics (call center status, tenure) and exploratory analysis by recommendation and knowledge-check performance.
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Field
Sample size (or number of clusters) by treatment arms
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Before
300-500 individual responses.
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After
We plan to collect between 150 and 400 observations. After screening (see above), we expect the final number of responses to be between 100 and 300. Treatment and control conditions are assigned evenly (50/50) at the respondent level. We may also conduct some versions of the survey that do not include the randomized experiment so we can add additional questions.
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Field
Power calculation: Minimum Detectable Effect Size for Main Outcomes
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Before
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After
We pre-specify a willingness to pay difference of $100-120/month as our minimum economically meaningful effect. We choose this range because $100 is the smallest plausible Medigap-vs-MA premium difference (but is less than the average minimum Medigap-vs-MA premium difference we observe for our sample); $120 is roughly the average minimum price difference we observe. Given our within-subject design we expect to be powered to detect differences of $100 with a sample size of 100.
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Field
Intervention (Hidden)
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Before
This project surveys licensed Medicare insurance intermediaries (agents/brokers) to better study how intermediaries interact with clients and how they form Medicare plan recommendations. We embed a randomized experiment in the survey where we randomly vary whether a profile includes a statement that the client intends to speak with multiple intermediaries and gather multiple Medicare plan quotes before enrolling in a plan. We then compare recommendations across the profiles with the randomized statement and across respondents. Intermediaries are not told that any element of the profiles is randomized. We also ask intermediaries about their own business practices and about common insurance carrier practices in the Medicare market.
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After
This project surveys licensed Medicare insurance intermediaries (agents/brokers) to better study how intermediaries interact with clients and how they form Medicare plan recommendations. We embed a randomized experiment in the survey where we randomly vary whether a profile includes a statement that the client intends to speak with multiple intermediaries and gather multiple Medicare plan quotes before enrolling in a plan. We then compare the willingness-to-pay across the profiles with the randomized statement using a within-subject design for our primary outcome. We also compare responses across participants as a robustness check. Intermediaries are not told that any element of the profiles is randomized. We also ask intermediaries about their own business practices and about common insurance carrier practices in the Medicare market.
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Field
Secondary Outcomes (Explanation)
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Before
We ask each intermediary to evaluate Medicare plan fit on a 0-100 scale, to explain their recommendation, and to report how confident they are in their recommendation on a 0-100 scale.
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After
We ask each intermediary to evaluate Medicare plan fit on a 0-100 scale, if they are missing any information needed to make a recommendation, and to report how confident they are in their recommendation on a 0-100 scale.
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