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How to Stop Statistical Discrimination

employer discrimination and women's life choices reinforce each other

Forum: Reddit (/r/AskFeminists)
Date: 08/07/2012


How to convince my father that paying young women less is wrong?

Background: he's an executive in the financial field. He does some hiring and recommends people for promotion, but doesn't actively decide pay.

We had a two-hour conversation about how women statistically get paid 30% less. He rationalized this by saying that women are more likely to go off on maternity leave and never come back, therefore cutting the practicality of the company's investment in that employee. So as a result, they get paid less because they are more likely to leave.

I pointed out that's an unfair assumption to make, since many women come back to the office after they have a child, and that some men leave to become househusbands. Then he quoted statistics and stuff and just wouldn't budge on his previous suggestion. It's really irritating to me that he simply doesn't believe that men and women are worth the same amount.

This is known as statistical discrimination. Because employers cannot accurately and cheaply assess individual employees' future life choices, they base their assessment of the employee's value to the company on the aggregated average of other employees who share the same social backgrounds. Statistical discrimination does not require chauvinistic misogyny on the part of the employer: rather, it is motivated by rational profit-maximizing goals. You might be able to get your father to agree that it is wrong, but I don't know if it's possible to change your father's company's policies and practices when it is profitable to discriminate.

Statistical discrimination is different from the more traditional forms of discrimination in that it is rewarded by the market. Employers that do not hire people of particular race or gender because they hate them lose opportunity to hire most talented or qualified job applicants and are eventually punished by the market forces (as in, of course, "in the long run, we are all dead" as Kaynes wrote). On the other hand, companies that practice statistical discrimination can be more profitable than egalitarian employers, assuming that the statistical information they base their decisions on is correct, and it is they--not the companies that provide equal opportunities--that lose out the competition.

Further, widespread statistical discrimination leads members of the discriminated group to adapt to the employers' discriminatory practices by not investing in their productivity. In other words: if your employer is not going to give you promotion because you are women anyway, you wouldn't waste your energy learning new skills or postponing childbearing in order to get that promotion. But when many women choose to rationally maximize their own utility this way, employers will have even more statistical evidences to discriminate against women as a class. Unlike more traditional, "taste-based" discrimination, statistical discrimination is self-perpetuating: rational discrimination on the employer's part reinforces rational adaptation among the discriminated group, which further reinforces the statistical basis on which employers discriminate.

This is a vicious spiral that can only be resolved with external intervention, rather than individual awareness-raising. Anti-discrimination laws exist to punish such rational discrimination just the same as irrational, "taste-based" discrimination for this reason. Other societal solutions include social insurances for women leaving workforce to give birth and raise children, financial incentives for employers to hire members of the discriminated group, subsidies that reward employees investing in their own productivity, etc. Affirmative action should be carefully designed to stop and reverse the negative spiral of incentives that perpetuate rational discrimination.


Unlike more traditional, "taste-based" discrimination, statistical discrimination is self-perpetuating: rational discrimination on the employer's part reinforces rational adaptation among the discriminated group, which further reinforces the statistical basis on which employers discriminate.

Only by someone who considers themselves a victim first and not an agent. The latter would do what they could to prove the employer wrong. Doing this enough would change the statistical basis.

This is a vicious spiral that can only be resolved with external intervention, rather than individual awareness-raising.

Actually the latter could accomplish the same as well.

Wow, such lack of logical comprehension.

Statistical discrimination cannot be corrected by individual employers becoming more enlightened or individual women working hard to "prove the discriminatory employers wrong," because market punishes these employers and women who go against the tide of statistical discrimination. Individually, it is more profitable to discriminate and to adapt to that discrimination at the margin, even though going against that would be ultimately beneficial to women as a group.

Statistical discrimination creates perverse incentives. We need to move to a social, legal, and economic structure in which 1. discrimination does not pay, and 2. working hard pays. There are two methods for doing that: legal mandates (anti-discrimination laws) or market forces (incentivization).

Government cannot tell individual women how to live, but it can tell businesses not to discriminate. If the threat of anti-discrimination lawsuits and civil penalties were significant enough, companies would realize that discrimination does not pay.

Alternatively, the government could subsidize companies that hire women, or tax companies that hire men: this is not to create a general preference toward hiring women, but to balance out the statistical discrimination so that men and women with comparable skills and experiences can be treated fairly.

The government could also subsidize career development for women. Why? Let's say men invest in their own career development because they expect the return of 2 units over lifetime when they invest 1, but women don't invest in their careers because they know that discrimination would prevent them from receiving the same return on their investment. If the government subsidized career development, thereby reducing the cost of investment, more women would feel that investing in their career would be worthwhile because expected return on investment would improve.

So forcing employers to absorb the additional costs of having employees that make choices far more often that reduce productivity? That would just discourage businesses from hiring as many women.

Which is why I argued that we cannot rely on education or awareness-raising as a way for companies to voluntarily stop discriminating: they must be forced or incentivized to stop discriminating.

what you're suggesting is that women making decisions that impact their productivity shouldn't be judged on their merit.

What I'm suggesting is that they shouldn't be judged on other women's decisions.


Ah, no it doesn't. Women being more productive isn't punishing employers, and women are not discriminated against more for being more productive.

You seem to have real difficulty following an argument. Statistical discrimination is the kind of discrimination in which employers use statistical knowledge about a group of people (women, for example) when they assess an individual job applicant or worker (an individual woman).

The employer cannot tell if the particular woman is going to leave workforce, but they know that women tend to leave workforce mid-life more frequently than men do. The employer has two choices: they can use this information to discriminate against female applicants or workers, or disregard it because each individual woman deserves to be treated as individuals first and not be judged by what other women do.

Assuming that the statistical knowledge (women tend to leave workforce mid-life more than men do) is correct, it is in the employer's economic interest to practice statistical discrimination. There is a perverse incentive to discriminate against women simply because they belong to a group that has known statistical tendencies, regardless of each particular woman's life plans. Market punishes companies that disregard statistical information and treat each person fairly as an individual.

For example, when the employer invests in skills and leadership development for their male and female employees equally, and if more women leave the company than men do, the employer end up wasting some of the resources they'd put into the employee development. On the other hand, if the employer gives preferential treatment to male employees when they invest in skills and leadership development for its employees, and more of these individuals would remain with the company than if they had invested in both males and females, the employer can receive more return on investment than if they had not discriminated. That is how the market rewards companies that discriminate, and punishes companies that do not.

Now, if female workers know that companies discriminate against them, depriving them of opportunities for growth and promotion simply because it's profitable to do, the women would also lose incentive to invest in their own career development. If the employers do not consider them viable candidates for promotion anyway, it is simply a waste of their scarce resources to work on improving their productivity. When the market fails to reward female employees who invest in improving their own productivity, the cost of that investment (time, energy, change of life plan) is a loss that they will not recoup; it would have been more rational and utility-maximizing to focus their time and energy on other areas of their lives. Thus, statistical discrimination disincentivizes women from seeking opportunities to improve their productivity, which in turn makes it more likely that employers will discriminate.

What part of this logic do you not understand?

If they really wanted to pay men more than women in cases women are just as productive, then competitors can get equally productive employees at a lower price.

That is an example of taste-based discrimination. Do you not understand how different (in fact, opposite) incentives operate in statistical discrimination vs. taste-based discrimination?

Statistical discrimination would not exist in a perfect market where perfect information is readily available (and therefore companies can assess each individual's future productivity accurately). But companies do not have any way of knowing what decisions job applicants or employees make in the future, but they know what percentage of women versus men leave workforce. When they use the aggregated average of female employees' productivity as an estimate for a particular female employee's, she is no longer treated as an individual: she is discriminated, however rational it might be for the employer's bottom line.

It would seem it is you who lacks a proper understanding of economics in favor of "fair outcomes".

Why are you so sure that you are smarter about labor market and incentives than two Nobel Prize winning economists Kenneth Arrow and Edmund Phelps, who came up with the model of statistical discrimination?

And yet, we're also not allowed to punish women who do make those decisions. So where is the accountability for women's choices? You seem to think it should be on no women at all.

Whether or what sort of consequences women who make a decision to leave workforce should bear is a different discussion topic. Here, we are talking about young women being discriminated not because of choices they made themselves, but because of what companies know about choices other women have made.


But the point is that women are not penalized for being more productive.

If a female employee invests her scarce resources (time, energy, etc.) in order to improve her productivity but still does not receive the promotion that a comparable male employee would, because the employer thinks that she is more likely to leave the company than her male colleague is, her investment is wasted. There is an opportunity cost for her loss, and that is a penalty--which is why statistical discrimination disincentivizes women from investing in improving their own productivity.

If we were permitted to punish people who left a job early, then the higher potential liability women in this case employers face need not rely on statistical discrimination

I see, so you are finally acknowledging that statistical discrimination exists, and it is self-perpetuating, given the employers' inability to punish women who leave jobs early.

Enabling companies to punish individual women who leave jobs early is indeed one of the ways statistical discrimination can be eradicated. It is highly impractical and has disproportionate negative impact on women, but at least it gets rid of statistical discrimination. There are other, more realistic and fair policy options--many of which I've already listed, including a creation of social insurance for companies that offer equal opportunities to their employees (that would reimburse them for damage when their female employees leave their jobs early).

I think how you're describing it is incomplete or misunderstood.

I don't think so, but if you actually know what you are talking about, feel free to point out how I misrepresent the theory of statistical discrimination.

Either we can disencentivize unproductive behavior by employees by punishing those who make such decisions or prophylactically treating people most likely to make those decisions as a greater liability. Just like treating felons with a different level of assent for various levels of trust, or people with bad credit ratings, or charging men more for car insurance. They're all forms of discrimination, but the market must have some way to incentivize productive and disencentivize less productive/destructive behaviors.

It is a paragraph like this that makes me question that you understand statistical discrimination. Charging men more for car insurance based on statistics might be unfair and discriminatory, but it does not disincentivize men from driving carefully. Not offering positions and promotions to women because the company thinks they are likely to quit disincentivize them from investing in improving their productivity.

Unless you think strangling the market's ability to regulate incentives for productivity is a good thing, one or the other must exist.

Actually, statistical discrimination is a distortion of the market caused by imperfect information, and it diminishes the market's ability to allocate resources (including labor) efficiently. For example, there are probably many women who would make great leaders and have no plan or desire to leave their professional careers early, but are not given opportunities to develop their leadership because employers fear that they might leave the workforce soon. Because of this information asymmetry, market is unable to maximize productivity and efficiency without some sort of intervention.

You are correct to suggest that one possible (albeit impractical and problematic) solution to that problem is to enable companies to punish women (and any others) who leave their jobs early. But that is far from the only option, and you seem to object to just about any other solutions that are equally sound (or better), economically speaking. Perhaps you like the solution you suggested, because it's so impractical that it would never happen, thereby guaranteeing that statistical discrimination will continue unabated. Your misogyny is showing.


That penalty isn't due to more productivity though.

Well first off, you claimed that women are penalized more for being more productive.

My point here is that statistical discrimination disincentivizes women from investing in improving their productivity. Your response does not indicate that you can follow an argument or logics, since you continue to cling to a distorted interpretation of my argument after it was explained three or four times. Go back and read again--and tell me if I ever stated that women are penalized for being more productive (never).

What? We can't judge people on employment history?

You are defending companies' right to discriminate against women regardless of their own individual employment history or aspirations, solely because of other women's aggregated employment histories, not her own. How am I premature to conclude you a misogynist?


Because you've misinterpreted me several times, but at the same time acknowledging that punishing women for their unproductive decisions would also be an approach. So the concept I've espoused several times isn't alien to you nor did you not realize what I was talking about then, but you then later misinterpret/mischaracterize my position.

I consider your position misogynist because 1. the particular solution you propose has disproportionate negative impact on women; 2. you reject all other solutions that do not have similarly disproportionate impact on women or on men; 3. you argue that it is perfectly acceptable to discriminate against all women because of the actions of some women unless and until your proposal is adapted.

You also seem to be confusing what is good for individual employers with what is good for the society. Disincentivizing women from leaving jobs early might be in the interest of the employers, but it may not necessarily be in the society's interest. After all, women who leave workforce do not just disappear into void: they perform different, but valuable tasks in the society.