Friday, September 30, 2016

Two roads diverged

I'm taking a break from contemporary affairs in order to follow up on an obscure post from the early days of this blog.  In 1951, a Gallup poll asked "Which of these two jobs would you personally prefer a son of yours to take--assuming he is equally qualified:  a skilled laborer's job at $100 a week or a white-collar desk job at $75 a week?"  and a parallel question about preference between "a college professor's job at $4,000 a year or a factory foreman's job at $6,000 a year?" 66% chose the laborer's job over the white-collar deck job, and 56% chose a foreman over the professor.

What factors influenced the choice?  Two obvious possibilities are education and one's own job.  People might like their sons (or hypothetical sons) to do what they had done, so more educated people would tend to favor the jobs that required more education, and people would tend to prefer jobs that were similar to their own.  Both of those turned out to be true.  Here is a comparison by occupation, showing the percentage favoring the white-collar job for each pair.

                       Desk Job     Professor
Professional            45%           63%
Farmer                  23%           30%
Business                38%           39%
White Collar            47%           58%
Blue Collar             26%           36%
Service                 28%           32%

Another obvious possibility is income, although I'm not sure about what to expect, but Gallup didn't ask about it then.  There were no clear differences by race or gender, but there was a difference by the size of the community:  the larger the town, the more likely people were to prefer the white collar job.

                       Desk Job       Professor
under 2,500              26%            34%
2,500-10,000             28%            44%
10,000-100,000           35%            42%
100,000-500,000          34%            42%
over 500,000             39%            51% 

The difference by size of town remained statistically significant even after controlling for education and income.  As for why, my thought is that people who lived in larger places might have wider frames of reference--they would be aware of a wider range of careers and occupations--and would tend to think about prospects for advancement rather than just the immediate pay difference.

[Data from the Roper Center for Public Opinion Research]

Tuesday, September 20, 2016

More on police shootings

Over the summer, a paper by Roland Fryer got a lot of attention.  He summarized his findings:  "there are racial differences--sometimes quite large--in police use of force, even after accounting for a large set of controls ... Yet, on the most extreme use of force--offi cer-involved shootings--we are unable to detect any racial di fferences...."  You could restate this by saying that there is more anti-black bias in non-lethal force than in lethal force, and it's not clear if there is any bias (in either direction) in the use of lethal force.  The difference between lethal and non-lethal force was surprising to me--I figured that if there was bias, it would be more pronounced for the more extreme use of force.  I thought his paper was convincing on that point, partly because of the evidence he presented and partly because of a simple comparison to the data on fatal shootings by police that I've written about before.   Blacks comprise 27% of those fatally shot by the police.  This is considerably higher than their share of the total population, but not relative to other forms of negative involvement with the criminal justice system.  For example, blacks make up 39% of those arrested for violent crime.

The difficulty is in figuring out whether 27% is more, less, or about the same as what it would be if police shootings took place without regard to race--that is, if a white person and a black person in the same situation faced the same risk of being shot--which is why Fryer said "we are unable to detect any" racial differences rather than "there are no" or even "there appear to be no."

Although the data Fryer used has a lot more detail, the data I used also has some advantages:  it covers the whole nation and has more cases.  It includes a variable for whether the person who was killed was attacking a police officer, "other," or "unknown" and one for what kind of weapon, if any, they had.  I combined those into a new variable with three values:  people who were not attacking ("other" or "unknown") and unarmed (or "undetermined"), people who were armed but not attacking, and people who were attacking.  I'll call them low, medium, and high levels of apparent threat.  The breakdown of people killed by apparent threat:

            Black   Hispanic   White
low          35%      22%       39%
medium       26%      20%       48%
high         26%      16%       55%

There are statistically significant racial differences--the share of blacks and Hispanics is highest for the lowest threat level. You could also put it in terms of the chance that a person will be killed by the police when they are unarmed and not attacking:  blacks have about six times the risk of non-Hispanic whites, and Hispanics have about three times the risk.

The limitation of this comparison (and the ones Fryer did) is that we don't know the number of people who were in a comparable situation but were not fatally shot.  So it's possible that blacks and Hispanics were just less likely to be in the low-threat relative to the high threat situations.  That doesn't seem likely to me--the low-threat situations can include a wide variety of circumstances (e. g., bystanders who were killed by accident), so it seems the racial distribution of people in them in them should be closer to that in the general population.  It's also possible that police are unbiased in low-threat situations but less likely to kill blacks and Hispanics in high-threat situations.  However, the most plausible interpretation seems to be that there is some anti-black bias in fatal police shootings.

PS:  There were a total of 1,499 fatal shootings in the 18 months covered by the data: 133 low threat, 418 medium, and 948 high.

Monday, September 12, 2016

Cui bono?

In August 2008, a Gallup/USA Today poll asked "If _____ is elected president, who do you think his policies would benefit the most – the wealthy, the middle class, or the poor, or all about equally?" for John McCain and Barack Obama.  In late June and early July of this year, a survey sponsored by the American Enterprise Institute and Los Angeles times asked the same question about Donald Trump and Hillary Clinton.  The results:

                    McCain    Trump            Obama    Clinton
Wealthy              53%       54%               16%      36%
Middle Class         19%       15%               33%      19%
Poor                  1%        2%               22%      12%
All equally          25%       20%               25%      25%

The distribution of answers is almost the same for Trump as it was for McCain, but the distribution for Clinton is quite a bit different from what it had been for Obama--fewer saying the poor or middle class, and more saying the wealthy.  The 2008 survey also asked about voting intention (the 2016 survey did not).  As you might guess, people who thought a candidate would benefit the middle class or everyone about equally were a lot more likely to support him than those who thought he would benefit the rich.  Things were more complicated with the poor--the few people who thought McCain's policies would benefit the poor were overwhelmingly in favor of him (88%, although it was only eight people); the larger number who thought Obama's policies would benefit the poor were strongly against him (26%).

If you combine the 2008 estimates with the 2012 opinions, perceptions of who benefits from Clinton's policies are costing her about 7 percentage points compared to Obama.  Although I wouldn't take the exact number very seriously, it seems safe to say that she's not getting as much benefit as he was.

Why would Clinton be viewed so much differently than Obama was?  One possibility is that it's a fixed part of her image--maybe people are thinking of the well-compensated speeches she's made to Wall Street firms.  Another possibility is that the contrast with Bernie Sanders made people think of her as more favorable to rich, and that as people start focusing on the contrast with Trump perceptions will change (or maybe already have changed).  The fact that Trump is not seen as much different from McCain is interesting, since claims that he would help the working and middle classes have been a big part of his campaign.

[Data from the Roper Center for Public Opinion Research]

Tuesday, September 6, 2016

Are they blue?

One of the major themes of election reporting in this campaign has involved "blue-collar" or "working class" support for Donald Trump.  But few surveys ask people about their occupations today, so usually journalists treat class as equivalent to education.  For example, a Los Angeles Times story entitled "How do Americans view poverty? Many blue-collar whites, key to Trump, criticize poor people as lazy and content to stay on welfare," said the racial difference in opinions about who had the greatest responsibility for helping the poor "lay almost entirely with blue-collar whites--those without college degrees."  Of course, education is associated with occupation, but how strong is the association?  The Current Population Survey contains information on both education and occupation.  Civilian occupations are classified into 22 groups:  

Business and Financial Operations
Computer and mathematical science
Architecture and engineering
Life, physical, and social science
Community and social service
Education, training, and library
Arts, design, entertainment, sports, and media
Healthcare practitioner and technical

Healthcare support
Protective service
Food preparation
Building and grounds cleaning and maintenance
Personal care and service

Office and administrative support

Farming, fishing, and forestry
Construction and extraction
Installation, maintenance, and repair
Transportation and material moving

I divided them into four groups, with divisions indicated by the blank lines.  The last group of occupations corresponds with what people normally call "blue-collar"--they involve making or extracting some tangible product.   The first and third groups would clearly be "white collar" jobs--the difference is that the first generally involves more skill and higher pay than the third.  The second group is hard to classify by the blue collar/white collar distinction--like most white-collar jobs, they produce services rather than goods, but in terms of skills and autonomy, they are closer to blue-collar jobs.  

The occupational distribution of people with different amounts of education (rearranging the order to put the two white collar groups together):

                         White Collar
                Manager/Prof  Other   Service  Blue-Collar               

Not HS graduate         7%    17%        34%       41%
HS only                19%    25%        22%       34%
Some College           29%    31%        21%       19%
College Grad           64%    22%         8%        7%
Master's               84%    10%         3%        3%
Professional/Doctoral  92%     4%         2%        1%

Few blue-collar workers have college degrees, but a lot of people without college degrees are NOT blue-collar workers.   Considering everyone without a college degree, only 29% are blue-collar workers in the narrow or traditional definition.  Another 23% are service workers, so on a broader definition you could say a little over half are blue-collar workers.  

The reason that lacking a college degree is not synonymous with having a blue-collar job is partly that there just aren't that many blue-collar jobs in the United States any more, and partly that even people with only a high school diploma have a decent chance of obtaining a white-collar job (which might involve supervising blue-collar workers).  

Looking at it from one direction, it's strange that given the contemporary interest in class, few surveys bother to ask people what kind of work they do.  Looking at it from another direction it's strange that when given a straightforward measure of education, people call it "class" rather than "education."