Japanese Americans and Muslim Americans

Instapundit had some thoughts on the internment of Japanese-Americans during World War II and the patriotism of Muslim Americans now. I have strong disagreements with most of his post except for the following about a Pakistani American saving a synagogue from arson by a Bosnian:

And those who favor extensive profiling should note the photos of Ali — the hero — and Jakup — the alleged terrorist — and think about which one of the two would be more likely to come in for close attention under most profiling proposals.

So I was thinking was writing a post about it when I saw Jim Henley’s excellent post on the topic.

No, the wrongfulness in the World War Two internments was that they were based on the principle of collective guilt, and applied to US citizens, and the internees were dispossessed of all their property without compensation. I’m not sure what Glenn thinks would be “significant numbers” but it would still not be okay to rob the innocent Japanese-Americans of the bulk of their belongings, as the Roosevelt Administration allowed to happen as part of the internments.

[…]The wording [“there are American Muslims who are quite loyal”] implies that these wondrous creatures are prodigies, like saying “There are Snowy Owls as far down the Appalachians as Eastern Kentucky.” Gosh, but the surefire sign of disloyalty to the United States would seem to be committing terrorist acts against it and a bare handful of American muslims, almost none of them citizens, have tried to do that. As Gene Healy has pointed out, it would be a trivial matter for “significant numbers” of American Muslims to raise all kinds of caine around here. Doesn’t seem to be happening.

Go read his whole post.

NOTE: Thanks Jim for the link.

Racial Profiling

CalPundit points out about racial profiling by police in Los Angeles:

Among people who were pulled over:

  • 3.5% of whites were frisked and 5% were searched.
  • 12% of Latinos were frisked and 18.5% were searched.
  • 14.7% of blacks were frisked and 18.7% were searched

Then responding to criticism, he looked up the raw report and deduced from it that:

  • Police searched blacks at about four times the rate of whites, but also found contraband at about four times the rate, which makes the search rate seem defensible on non-racial grounds. On the other hand, they found contraband on Hispanics at only twice the rate of whites, which makes the 4x search rate look pretty dubious.
  • The arrest rates seem even more troubling, since this is a good indication of whether anything serious was going on. For both blacks and Hispanics the search rate is 4x the white search rate, but the arrest rate is only about double. This seems to indicate that the LAPD’s “suspiciousness radar” was tuned rather higher for blacks and Hispanics than for whites.

It’s true that data like this needs careful study, certainly something more careful than an amateur like me can give it. On the other hand, it does seem to indicate that the LAPD treats blacks and Hispanics with rather more suspicion than is justified, and race seems to be a part of it.

POSTSCRIPT I: One last comment: my snarky remark about affirmative action in yesterday’s post had a serious side to it: conservatives typically claim that, yes, there is probably still some racism in our society, but the best way for the government to respond is to just set a good example and be absolutely color blind. Eventually society will follow.

But if that’s true, then why isn’t it equally true for racial profiling? The liberal response might be, sure, maybe blacks commit more crimes than whites, but the best way to respond to this is to ignore it and have police act in a completely color blind manner. Eventually the problem will solve itself.

Is racism still alive? I would say pretty much so though it has definitely decreased from historical levels. Is racial profiling a good thing? I concede that in some cases it might provide police with some help but it also impedes them in a number of ways. For example, a profile of Middle Eastern men would never have caught Richard Reid or Jose Padilla. Also, racial profiling of African Americans smacks too much of Jim Crow. Another very important way in which racial profiling creates problems for the police is by fraying the relationship between law enforncement and the minority in question. And that is something most conservatives, especially those belonging to the white majority, don’t understand at all. Randall Kennedy in an article in the New Republic argued for banning racial profiling due to the same reasons.

Death Penalty Racism

According to the New York Times,

Blacks who kill whites are significantly more likely to face the death penalty in Maryland than are blacks who kill blacks or white killers, according to a state-sponsored study released yesterday. By itself, the study found, the race of the defendant was essentially irrelevant.

[…]The report found that two counties with the highest death sentencing rates, Baltimore and Harford, were also the two counties with the highest rates of capital homicides involving white victims and black killers.

The report also found that choices made by prosecutors about whom to charge with a capital crime accounted for almost all of the racial disparity. Later decisions by prosecutors, judges and juries had little impact.

[…]Maryland has executed three men since capital punishment was re-established there in 1978. Eight of the 13 men on death row today are black, according to the study. All 13 were sentenced to death for killing whites, it said, though 55 percent of the victims in all cases in which the death penalty was or could have been sought were not white.

I can’t say I am surprised, though I would like a national study attempt to isolate the effect of the race of the victim.

Race

Eve Tushnet has a series of thoughtful posts on race (1, 2, 3, 4, 5, 6, 6a, 7, 8, 8a, 9a, 9b, 9c, 9d, 9e). She discusses the employment study that I talked about earlier (1, 2, 3, 4). I don’t agree with all of Eve’s ideas but they are interesting nevertheless.

Racial Discrimination: #5

Kieran Healy links to a study focussing on the effects of a criminal record on job prospects.

Pager found a similar race effect to the study Kreuger writes about, but because she also looked at incarceration it brings it into sharper focus. She found that blacks “are less than half as likely to receive consideration by employers relative to their white counterparts, and black non-offenders fall behind even whites with prior felony convictions.” In other words, even though race and prior incarceration both negatively affect one’s employment opportunities, controlling for education and skills you’re better off being a white male with a felony conviction than a black male with no criminal record.

Racial Discrimination: #4

I like the data organized this way. For each want ad, four resumes were sent, two Whites and two Blacks.

Equal Treatment

87.37%

No Call-back

82.56%

1W+1B

3.46%

2W+2B

1.35%

Whites Favored

8.87%

1W+0B

5.93%

2W+0B

1.50%

2W+1B

1.43%

Blacks Favored

3.76%

1B+0W

2.78%

2B+0W

0.45%

2B+1W

0.53%

Another interesting breakdown is by occupation and industry.

Occupation % of Ads White callback rate Black callback rate Ratio
Executive and Managerial 14.5% 7.91% 5.95% 1.33
Administrative supervisors 7.7% 9.57% 5.85% 1.64
Sales representatives 15.2% 8.04% 5.09% 1.58
Sales workers, retail and personal services 16.8% 10.46% 7.05% 1.48
Secretaries 33.9% 10.49% 6.63% 1.58
Clerical workers, admin. support 11.9% 13.75% 9.96% 1.38

I would have expected similar results. At the highest level (executive and managerial) and the lowest (clerical workers, admin. support) discrimination is lowest.

Industry % of Ads White callback rate Black callback rate Ratio
Manufacturing 8.3% 6.93% 3.96% 1.75
Transportation and communication 3.0% 12.16% 14.86% 0.82
Wholesale and retail trade 21.5% 8.76% 5.71% 1.53
Finance, insurance and real estate 8.5% 10.63% 4.35% 2.44
Business and personal services 26.8% 11.30% 6.71% 1.68
Health, educational and social services 15.5% 12.14% 9.50% 1.28
Other/unknown 16.4% 8.71% 6.47% 1.35

Let’s now consider what the authors have to say about the hypothesis that the observed differences can be due to perceived social class rather than race of the applicants:

Second, perhaps employers are inferring more than just race from applicants’ names. More specifically, maybe employers are inferring social class. When employers read a name like “Tyrone” or “Latoya,” they may associate that name with the ghetto or other disadvantaged social background. Of course, because African Americans on average do in fact come from poorer backgrounds than Whites, this argument would have to be sharpened. These names would need to be more reflective of economic background than being African American already is. While plausible, several of our results are inconsistent with this interpretation. First, recall that the African American sounding names we use are not as atypical as they may seem. In fact. as Appendix 1 shows, they are quite common among African Americans. Second, for the subset of African American female names where we had access to data on social background (mother’s education to be precise), we found no correlation between social background and callback rates. Finally, and perhaps most telling, in Table 7, we found that African Americans are not helped more than Whites by living in more White or more-educated neighborhoods. If the African American names were mostly to signal negative social background, one might have expected a better address to yield greater returns for the African American names than for White names.

The authors make a plausible case, but not an air-tight one in my opinion. I think a batch of neutral-sounding names, i.e. common names equally popular among whites and blacks, would have given a good comparison. Also, the authors did not have access to much social/economic data; only data about mothers’ high school education for a small subset is not enough. I would guess that there is a bigger jump in social/economic status if the mother is college-educated as opposed to the difference between “completed high school” vs “not completed high school.” (I do not have any data on this, but would appreciate if someone could point me to it.)

In the end, I have no doubt that there is racial discrimination in hiring, though definitely has gone down quite a lot over the years. The authors do make a better case than a lot of the previous studies, but their case is all about discrimination among first names. There is definitely correlation with race, but is it causation? I am not completely convinced.

NOTE: All the tables and quotes belong to Bertrand and Mullainathan and are from their paper “Are Emily and Brendan More Employable than Lakisha and Jamal? A Field Experiment on Labor Market Discrimination.” All copyrights belong to the authors or to the publisher of their paper.

Racial Discrimination: Post 3

Looking at the data for the different names from the previous post, a few things come to mind.

There is a great variation even within a category. What is the reason for that? Do people like Kristen so much better than Emily? Ebony over Aisha? What’s wrong with Neil? What is Brad doing right (other than sharing his name with Brad DeLong)? Can the authors explain it? Is the difference between blacks and whites due to choosing these specific subset of all names instead of race? What if the researchers had chosen all white names with results like Neil and all black ones like Jermaine? Is that even possible? Here is what the authors say:

Not surprisingly, we find variation in callback rates across names. Chance along would produce such variation because of the rather small number of observations in each cell. We therefore formally test the hypothesis that the names within each sex-race category produce the same effect. We estimate a probit regression of the call back dummy on all the personal first names, allowing for clustering of the observations at the employment ad level. For all but one sex-race category, we cannot reject the hypothesis that all the first name effects are the same. Only for African American female names do we reject this null at a significant level. Five out of nine female African American names (Aisha, Keisha, Tamika, Lakisha and Tanisha) do worse than the worst female White name. The last four female names (Latoya, Kenya, Latonya and Ebony) perform only slightly below the average White female name.

We investigated two possible explanations for these name specific effects among African American females. First, we considered the possibility that employers might be relatively less familiar with some of the worst performing names and it is this lack of familiarity that motivates their callback behavior. However, we found no obvious correlation between name-specific call back rates and the relative frequency of each of the names, at least in the Massachusetts birth certificates. Second, we considered the possibility that the name fixed effects reflect differences in social class or economic background. To assess the relevance of this interpretation, we used some limited Massachusetts birth certificates data on mothers’ education. More specifically, for each of the five most common African American female names in our sample (Aisha, Ebony, Keisha, Tamika and Tanisha), we were able to obtain information on the fraction of mothers having completed high school. We found no obvious relationship between the name-specific callback rates and mothers’ education. (Footnote: Female names by ascending mother education are: Tamika, Keisha, Tanisha, Ebony and Aisha.)

A number of black names in the study (Aisha, Rasheed, Kareem, Jamal, Hakim) seem like Arab in origin. Did that affect the results in any way? We see that Aisha, Rasheed and Kareem do badly but Jamal and Hakim don’t.

Bertrand and Mullainathan selected these names based on three factors: the popularity of these names among babies born in Massachusetts between 1974 and 1979; a high ratio of frequency in one race to the frequency in the other race; and as a result of a public survey which asked people to guess race and other features just based on a first name. If I was doing this study, I would include popular names that are equally popular among blacks and whites as well. That would give me something to measure my results against. Also, I would like to see the results of the public survey. Did they ask about education, income, intelligence, etc.? For example, was there a correlation between the call-back rates and any of the features they asked on the public survey?

Even though last names used were also race-specific, they do not analyze the effects of last names. “Because sample sizes are not large enough to separately consider each first and last name combination, we focus on first names.

I should also mention Bertrand and Mullainathan found that the observed differences in callback rates for blacks and whites are statistically significant.

NOTE: All the tables and quotes belong to Bertrand and Mullainathan and are from their paper “Are Emily and Brendan More Employable than Lakisha and Jamal? A Field Experiment on Labor Market Discrimination.” All copyrights belong to the authors or to the publisher of their paper.