Charging Men More for Car Insurance vs. Women More for Health Insurance (Survey Results)

1. Overview

This is an informal survey-based study on people’s views of gender-based pricing in insurance. Two-hundred-and-one Americans, balanced for gender (men and women) and party affiliation (Republican and Democrat, although my interest isn’t party politics itself so much as the broader “Red Tribe” and “Blue Tribe” cultures in the United States that differ in politics, religion, gender roles, geography, urbanization, etc.), indicated their approval level (on a 1–7 scale) of one of the two following policy statements:

  1. Insurance companies should be allowed to charge women more for health insurance, if they find that women on average access health services more often.
  2. Insurance companies should be allowed to charge men more for car insurance, if they find that men on average get in car accidents more often.

This survey asks about car insurance for men and health insurance for women because those forms of gender-based pricing have received attention in the media (e.g., “Alberta man changes gender on government IDs for cheaper car insurance” from CBC and “Why Republicans Want to Make Women Pay More Than Men for Health Insurance” from NYMag), making these the most realistic or familiar scenarios.

Results indicate greater approval for charging men more for car insurance than for charging women more for health insurance. Respondent gender and party affiliation were relevant—women exhibited a larger difference than men in approval ratings, and the “Blue Tribe” (Democrats) had a larger difference than the “Red Tribe” (Republicans).

Some might question whether car insurance and health insurance are comparable. I think they are comparable, although there are obviously some differences. Health insurance is more essential, although car insurance is not far behind in the notoriously car-dependent United States (77% of Americans drive to work, not counting carpools). Health insurance is also more expensive to buy, but more likely to be provided by someone else (a majority of Americans have coverage through their employer, Medicare, or Medicaid). I don’t see these details giving an obvious justification for why gender pricing would be acceptable in one type of insurance and not the other, but that’s an open possibility.

2. Main findings

The overall average approval rating for gender-based pricing in insurance was 3.3 out of 7 (SD = 2.1). The average for charging men more for car insurance was 3.8, compared to 2.8 for charging women more for health insurance. This is a difference of 1 point or about half a standard deviation (Cohen’s d = 0.49), and is statistically significant (see section 3).

Figure 1

Both gender and party of respondent had a significant effect on the difference in ratings between scenarios. Men exhibited a smaller difference in their approval ratings than women did, and Republicans exhibited a smaller difference than Democrats. As a result of the effects of party and gender, Democrat women exhibit numerically the largest disparity (2.5 points) and Republican men the smallest (0.3 points in the other direction), with Democrat men (1.2) and Republican women (1.1) in the middle.

Figure 2

3. Additional details

The 201 participants were recruited from an online research platform and paid a small sum to complete the survey, which took under a minute (and included one other policy question). Respondents were assigned to the question about health insurance or car insurance based on identifying whether the last digit in their day of birth was an even number or an odd number, which divided them approximately in half.

Table 1: Question answered, by gender and party affiliation

Total respondentsAnswered question on men & car insuranceAnswered question on women & health insurance
Republican men502327
Republican women502822
Democrat men502525
Democrat women512823

Having participants answer one question, but not both, has the advantage that seeing one question doesn’t influence their answer to the second question, but the disadvantage of lower statistical power. Respondents also provided their ages, which I’ve summarized below. Republicans were a bit older than Democrats.

Table 2: Age of sample, by gender and party affiliation


Statistical analysis was done using a linear regression (lm in R). The response variable was the 1–7 rating of acceptability; the predictor variables were scenario (men on car insurance, women on health insurance), gender of the respondent (man, woman), and party affiliation of the respondent (Republican or Democrat).

The ANOVA table of the output is provided below. The most relevant results are the significant main effect of scenario (charging men more for car insurance was rated as more acceptable than charging women more for health insurance) and the significant scenario:gender and scenario:party interactions (both party and gender affect the disparity in ratings, as explained above). The non-significant scenario:gender:party interaction is also relevant; it means that the disparity exhibited by each party + gender combination is predicted by the separate effects of party and gender. In other words, the scenario ratings difference of Democrat women is largely predicted by the separate effects of “Democrat” and “woman” rather than something special about Democrat women (and similarly for Republican women, Republican men, and Democrat men).

Analysis of Variance Table

Response: insuranceresp
                       Df Sum Sq Mean Sq F value    Pr(>F)    
scenario                1  52.43  52.432 15.0413 0.0001442 ***
gender                  1  45.14  45.144 12.9504 0.0004065 ***
party                   1  48.27  48.273 13.8481 0.0002599 ***
scenario:gender         1  23.43  23.434  6.7226 0.0102488 *  
scenario:party          1  30.44  30.441  8.7325 0.0035152 ** 
gender:party            1  28.59  28.593  8.2026 0.0046460 ** 
scenario:gender:party   1   0.21   0.215  0.0617 0.8041652    
Residuals             193 672.78   3.486                      
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

A complete table of the results is provided below, with effect sizes (Cohen’s d, the effect size measured in standard deviations, calculated using the effsize package in R).

Table 3: Full results

Charge men more
Charge women moreDifferenceCohen’s d
Full sample (n = 201)3.842.811.030.49
Men (n = 100)3.983.600.380.18
Women (n = 101)3.711.911.801.02
Republicans (n = 100)3.943.710.230.10
Democrats (n = 101)3.741.901.841.12
Republican men (n = 50)4.484.81-0.330.17
Republican women (n = 50)3.502.361.240.54
Democrat men (n = 50)2.522.281.140.68
Democrat women (n = 51)3.931.482.451.85

Be Careful Equating Unwanted Sexual Advances with Harassment

October 2017 saw a series of allegations of sexual harassment, abuse, and assault in Hollywood spark a conversation about sexual misconduct in society. I don’t object to that conversation happening, but I do object to one concerning trend: people and outlets conflating unwanted sexual advances with sexual harassment.

(Length: 800 words.)

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The Women-Are-Wonderful Effect (We Don’t Live in a “Culture of Misogyny”)

Attitudes towards women are hostile and contemptuous, according to the standard model of prejudice (as described by Glick & Fiske, 2001). This view is prevalent:

A “culture of misogyny” is “deeply-rooted in our society” (Kathleen Wynne, former Premier of Ontario). “We live in a culture of casual misogyny” (Megan Leslie, former deputy leader, New Democratic Party in Canada). We live in a “patriarchal misogynistic society” (Tina Garnett, Equity Committee Coordinator, York University). “Misogyny runs so deep in this society […] all the women-hating, woman-blaming, woman-fearing instincts” (Polly Toynbee, columnist for The Guardian). “[W]e should look in the mirror for woman-hating culture” (Stephen Hume, columnist for the Vancouver Sun). “This Is How Much America Hates Women” (Anne Helen Petersen, PhD, writer for BuzzFeed News). “America really, really hates women […] there is actually nothing women can do that is right” (Megan Murphy, Feminist Current).

But the actual psychological research on gender attitudes and stereotypes paints a very different picture, one where women are viewed more positively than men. Glick and Fiske describe this phenomenon (the women-are-wonderful effect) as an “extremely robust” finding (although it is found more strongly among women than among men).

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Sexual Double Standards for Men? Player, Virgin, Creep, Objectifier (also: Male Nudity and Male Homosexuality)

We treat male and female sexuality differently. The most well-known example of that is the slut double standard for women (casual sex is seen as degrading and disgraceful for them to an extent that it isn’t for men), but we also have some important sexual double standards for men. The first and second (player and virgin) involve having or not having sex, while the third and fourth (creep and objectifier) are about expressing sexual desire. The fifth (“male nudity is funny, not sexy”) is a difference in how we tend to see men’s and women’s bodies. The sixth is “male homosexuality is uniquely offensive”.

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Men’s Lives Matter Less? “Among the Dead Were Women and Children”

News organizations and human rights groups reporting on tragic events commonly single out the victimization of certain groups (based on gender, nationality, religion, age, etc.) as especially noteworthy. Sometimes this is based on the circumstances of the incident, like if a group is disproportionately targeted or affected (“Gunmen shot dead 11 people, mostly Christians, in central Syria on Saturday”). Other times it is based on properties of the group, such as if they’re more relatable to the audience (“At least 2 Americans among the dead in Nice, France attack” in an American outlet).

Singling out “women and children” is especially common in this reporting. Sometimes it happens when they’re disproportionately affected (“Dozens killed in Aleppo; mostly women and children among the dead”), but even when men are disproportionately affected—which is very often—it’s still generally “women and children” whose victimization is singled out. I consider this an example of male disposability and finding the suffering/death of men less distressing than that of women (and children).

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“Yes, Dear”: Henpecked Husbands and One-Sided Relationship Dynamics

“Yes, dear” is the characteristic phrase of a one-sided relationship dynamic where the woman functions as the “boss” of the relationship and the man is said to be “henpecked” or “whipped”. This is a common portrayal of marriage on TV or in jokes, but it also underlies a lot of real relationship advice for men. It’s a problem because taking it to heart can leave men unable to stand up for themselves in relationships.

Stories and jokes aren’t obligated to portray healthy relationships, but in light of these portrayals and especially the serious advice, men (particularly young men) need to learn that this is not ideal, and certainly not inevitable, in a relationship. It’s likely that we’re not as concerned about teaching men to stand up for themselves in relationships due to the history of men being head of household, but that’s largely a thing of the past.

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Spotlight on: Men’s Suicide Rates

This page is a resource on suicide as a gender issue for men. It includes first some statistics demonstrating the concerning fact that men are a lot more likely to kill themselves, and second some possible explanations for why that’s the case, including in the context of the “gender paradox of suicide” where men kill themselves much more but women consider and attempt it somewhat more.

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Defining, Demonstrating, and Understanding Male Disposability

Male disposability is our society’s tendency to have less concern for the safety and well-being of men than of women. The concept is central to many men’s advocates’ critiques of society similarly to how women’s traditional lack of access to power (and their current lower levels of direct participation in it) is central to most feminist critiques of society.

(Cet article est également disponible en français.)

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