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Police Shootings by State v. Percent of the Population that is Black

After my recent post on police shootings I was curious and did some googling on the topic. By coincidence, right about that time Peter Moskos (i.e., Cop in the Hood) wrote this:

I looked at the Washington Post data of those shot and killed by police in 2015 and 2016 and broke it down by states with more and fewer African-Americans. States that are more than 10 percent African American include 21 states plus D.C. (198 million people, 18 percent black, 36 million blacks). There are 29 states less than 10 percent African American (126 million people, 6 percent black, 7 million blacks).

 

Killed by Police v. Black Share of the Population

 

People, all people, are 1.6 times more likely, per capita, to be shot and killed by police in states that are less than 10 percent black compared to states more than 10 percent African American. Blacks are still more likely than whites, per capita to be shot overall. But this ratio (2.6:1) doesn’t change significantly based on how black a state is.

For both whites and blacks, the likelihood of being shot by police is greater in states with fewer blacks. And the difference is rather large. There are seven states less than two percent black. In 2015 and 2016, zero blacks were shot and killed in Maine, New Hampshire, Utah, Vermont, Wyoming, Idaho, and Montana. But if you think cops don’t shoot people in these states, you’re wrong. Compared to the four states with the highest percentage of African-American (Mississippi, Louisiana, Georgia, and Maryland are more than 30 percent black), the overall rate of police-involved killings in states with few blacks is higher. And this is despite a lower rate of overall violence.

There’s more at the link, including his data. I haven’t had an opportunity to go through the numbers, but I am not seeing a reason to disbelieve them offhand. I have a couple of theories (which are not entirely unrelated to each other) as to what is going on, but I’m curious about what readers think.

As an aside… regular readers may recall my earlier look at Washington Post data on police killings which led me to conclude one or two things that don’t fit the narrative the media, to include the Washington Post, seems to like to support.

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US life expectancy flat for third year

US life expectancy flat for third year

Life expectancy in the United States has stalled for three straight years, the government announced Wednesday.

A child born last year can expect to make it to 78 years and 9 1/2 months — the same prediction made for the previous two years.

In most of the years since World War II, life expectancy in the U.S. has inched up —- thanks largely to medical advances, public health campaigns and better nutrition and education. The last time it was stuck for three years was in the mid-1980s.

What does this mean for the future solvency of Social Security? Beats the crap out of me. But it sure casts doubt on all those who preach “demography is destiny” and “we are all living longer so work until you are 70”.

On a more mathy note small changes in input into Social Security models can have amazing effects on output, particularly over 75 year actuarial projections. Tweak some mortality and immigration assumptions and results change dramatically. We don’t even have to go the MJ.ABW. Though More Jobs. At Better Wages would itself have some outsized effects.

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The Economics of History, Douthat-Style

I try not to pay attention—and not provide a direct link—to the NYT’s Stupidest Conservative. It’s one of the greatest advantages of having Susan of Texas around: you can go there and see anything I might write, done better, and (in this case) with cute graphics.

But when Brad DeLong falls down on the job—dealing well with the social, but not at all with the economic, aspect—it is time to go once (and, I hope, only once) into the breach.

Douthat, as quoted by DeLong:

Prior to 1973, 20 percent of births to white, unmarried women (and 9 percent of unwed births over all) led to an adoption. Today, just 1 percent of babies born to unwed mothers are adopted, and would-be adoptive parents face a waiting list that has lengthened beyond reason.

First thing to note: these are not necessarily comparable sets, for reasons detailed by Amanda Marcotte (op. cit. DeLong as well). Since the babies of today are conceived more voluntarily (in concept; my perpetual caveat about access certainly abides here), you would expect those eligible to be adopted to decline as well. That is, the 19% drop (or 95% drop in percentage terms) in white babies being adopted (or maybe it’s a 8% drop from 9% to 1%, which would be 89% in percentage terms) is the effect you would expect with fewer “unwanted” births. People don’t offer children for adoption unless they can’t raise them.

So Douthat’s statistics do, if anything, show that overall life is improved since 1973. We can agree that fewer unwanted babies is a good thing, no?

But if I’m reading Douthat’s prose correctly, there’s a far greater structural problem. Concentrating only on “white” babies— that is, conceding that Douthat is considering a bare majority, if that, of the country—we see that the system he fondly remembers produced a 20% surplus of children born out of wedlock for whom the state or its equivalents needed to care.

Even ignoring the conditions under which many of those births occurred, that basically means that for one in every five children born out of wedlock, no more than four were successfully adopted.

The odds are that the ratio is much higher: after all, “births to white, unmarried women” is a large set. Some of those were likely by choice. Some of those likely were followed soon thereafter by marriage. Some of them had “pre-arranged” adoption within the family (or de facto adoption by the woman’s extended family; see Palin, Bristol, for a contemporary example).

I don’t know the numbers, but if you told me that the above accounted for slightly more than half of the category, I wouldn’t be surprised.

But that leaves about 40% of those babies needing to be adopted. And by Douthat’s own data, only 20% of them were.

So the best-case scenario is that, for each one of us who was adopted, there was a minimum of 1/4 of a person who wasn’t—and probably closer to a 1:1 ratio.

In Douthat’s world, women are supposed to feel guilty ex post because they made a decision. Does that mean that adoptees in the U.S. are supposed to feel guilty because they were adopted and someone else wasn’t? Or that our parents should feel guilty because they chose us, and not someone else?

From an economic analysis, the pre-1973 situation was one of significant excess supply, and the current 1% adoption rate is beneficial to the chances of a potential adoptee being adopted, while the “would-be adoptive parents [who] face a waiting list” have both an abundant opportunity to provide a relatively better lifestyle for children born in developing economies and to take interim steps such as fostering to ensure that they really want to change their lifestyle enough to raise children.

No economist in his right mind would consider the pre-1973 environment romanced by Douthat to be more optimal than the current one, unless he really loves human suffering and wasting human capital.

UPDATE: Tom Levenson at Balloon Juice went out and found some numbers that—to no one’s surprise, I trust—don’t support Douthat’s Delusion either.

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The Texas Miracle, Yet Again

We keep hearing about the Texas Miracle.  It’s been mythic since “openly gay” Governor Rick Perry declared that Texas was in great shape, in no need of stimulus monies at all—after receiving enough to turn his state’s fourteen-figure budget deficit into a surplus. (UPDATE: Links added. And that final link was rather prophetic.)

So when the WSJ’s Economics Blog listed the Personal Income gains for major metropolitan areas (and some that wish they were), it came as no surprise that the great state of Texas has four areas on the list that show no decrease in Personal Income over each of the past two years.  After all, there are only 85 areas of the 367 listed by the WSJ that show non-declines in Personal Income both from 2007 to 2008 and from 2008 to 2009.

Such an accomplishment certainly could not be matched by states with Severe Crises, such as Illinois or California, could it?

ca and il

Oops.  Four for each state.  Well, at least all of those started (and ended) well below the National Average.  Surely, Texas, with Austin and Dallas and Houston will show greater growth.

tx

Oh, well.  In fact, looking at the Bottom 10—the lowest total Personal Income areas that show no loss in each of the past two years, we find:

bottom10

The bottom two and three of the bottom seven are in Texas.  So the only one of the four that actually grew from a decent start is the one that has had a major influx in the form of the growth of Fort Hood.  Let’s hear it for Private Enterprise!

But still four areas that didn’t decline (well, much; McAllen drops $1, but that’s rounding error) over the two years.  Only a few states can match that.  In addition to California and Illinois, they are:

  • Georgia
  • Indiana
  • Maryland
  • Michigan
  • Missouri, and
  • Illinois

Meanwhile, two states have more than four metropolitan areas of growth.  I fully expect to hear about the “miracle” of five areas of West Virginia:

WV

but fear there will be little about that bastion of Northeastern Liberalism, Pennsylvania and its seven areas with two straight years of Personal Income growth—including the Pittsburgh area, which is notably above the national average after trailing it in 2007.

PA

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Strange Data Point of the Day

Looking at Population Change data derived from version 6.2 of the Penn World Tables.

It appears that the population of Kuwait declined by 55.46% in 1991, only to increase 48.64% in the following year.

I’m inclined to think of this as measurement error, not a mass exodus following by a mass return after the invasion. But that’s mainly because I think we would have heard if fully half of the population of the country had left.

Anyone have any information otherwise?

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