Intermediaries in the Medicare Market

2024-09-20

2026-03-31

The key outcome of interest is the insurance plan recommendation from an insurance producer (or insurance agent). We are interested in mean differences in recommendation quality across consumer and agent characteristics. We measure recommendation quality by looking at the mean number of Medicare Advantage recommendations, plan prices, and the number of incorrect/misleading statements. We will measure recommendation quality against an expert benchmark, consumer choice, and other agent recommendations. We also consider a random choice benchmark. We are interested in the heterogeneity in recommendations and response rates by insurance agent characteristics based on publicly available data and randomly assigned consumer characteristics. We will also use text analysis from recordings to study variations in the language used by caller/consumer and insurance producer characteristics.

We will look at heterogeneity in recommendation quality and response rates by insurance agent characteristics based on publicly available data (e.g. firm affiliated with, number of states licensed in, number of appointments, tenure, advertising presence, etc.) We will also look at differences in the regulatory and market environment.

This study seeks to understand the role of intermediaries in the Medicare market. We investigate how insurance plan recommendations are correlated with consumer and agent characteristics. The key outcome of interest is the quality of an insurance plan recommendation from an insurance producer (or insurance agent). We are also interested in the heterogeneity in recommendations by insurance agent characteristics based on publicly available data.

Not available

Consumers will be randomly assigned to insurance producers by a computer.

Consumers will be randomly assigned to insurance agents (and therefore insurance agent characteristics) by a computer. Variation in consumer characteristics will also be randomly assigned.

No

We will collect approximately 400-800 observations. There is a chance we will have fewer than 400 observations if more observations than expected do not meet our screening criteria. We will exclude incomplete observations, off-topic observations, and responses from individuals who are not licensed insurance producers. (Complete responses from individuals who are not licensed can be reported separately.) The maximum number of observations will also depend on take-up, screening, and whether we are able to obtain funding to look at multiple sources of heterogeneity.

We will collect approximately 400-800 observations. There is a chance we will have fewer than 400 observations if more observations than expected do not meet our screening criteria. We will exclude incomplete observations, off-topic observations, and responses from individuals who are not licensed (complete responses from individuals who are not licensed can be reported separately). The maximum number of observations will also depend on take-up, screening, and whether we are able to obtain funding to look at multiple sources of heterogeneity.

We will aim to have a 50/50 balance of the main agent characteristics of interest, but we do not expect the sample to be perfectly balanced due to the expected differences in response rates among agents. The randomization does not ensure exact balance by insurance agent characteristics such as number of states licensed in, number of appointments, etc. We will also aim to have a balanced sample of consumer characteristics such as gender.