2017 Firearm Statistics (Graphs)

Keeping us up to date.

The following are graphs from imgur, cooked up by u/alphabetcereal on Reddit. They replicate many of the graphs I’ve provided in prior articles, but with updated data for 2017 and slightly different data sources. The originals can be found here, and are republished with permission. Commentary after each graph is mine.

Not shown in this graph (but shown in a later one) — black people are also predominantly the victims of firearm homicide as well. Even more stark, would be to show male/female and age breakdowns, which show that the predominant firearm homicides (and homicide victims) within the black community are men in their teens and early twenties. We’ve spoken about why in some depth before.

Increasingly, I’m of the opinion that these statistics are related to the emergence of an honor culture within the young black male community, rooted in a distrust of the judicial system as a fair arbiter of disagreements. This is particularly true in black market trade, where enforceable contracts and small claims courts are unavailable.

Not shown in this graph is handgun homicides, which dominate all weapon types because handguns are concealable. Also note, that the 403 murders in this chart are by all rifles, not specifically “assault rifles,” and “assault rifles” are a vast minority of all rifles. The Republican Congressional Baseball Field Shooter, for instance, used a rifle that wouldn’t even be considered an “assault rifle.” It also bears mention that magically evaporating all the rifles would likely just push most of these numbers into the “handgun” umbrella, saving very few lives. Presuming magical gun evaporation were possible of course, which it isn’t.

White people generally murder white people, and black people generally murder black people. This is repeatedly shown in the research literature. Most murders are not of random strangers, they are almost always of people the murderer knows personally, over some kind of personal disagreement.

Firearm homicides have been basically stable, below 5/100,000 this century. Were this graph extended back 100 years, we’d see two peaks, one in the early 90s and one in the early 80s, with the last stable low plateau similar to the one we’re experiencing now back in the 1950s. We showed that for overall homicides here.

Public perception of firearm homicides is completely detached from fact. This is due to changes in the revenue model of modern media, where the media pushes fear to drive clicks. We spoke in detail about that here.

This is an interesting graph, one we haven’t touched on before, but marries up with some of the data presented in our gun solutions article. I personally do not like the inclusion of “one generation after Roe v Wade” in the graph. I think it implies a correlation that probably isn’t supported by longer time scale data or worldwide data. As mentioned above, there were two peaks in the longer time scale data, one in the early 90s and one in the early 80s, which marry up much better with the drug war. Other countries with different abortion laws (and different gun laws) also saw a reduction in homicide over the same time scale. While it’s possible that abortion law had some effect, it would take a much more detailed analysis than this to convince me. I think the graph author may question the veracity of that case as well.

This is something we haven’t yet presented, and is an interesting approach. We did an intuitive look at this by color coding the data points blue/red/purple in our first article. Bivariate correlations are very difficult to draw here, for a number of reasons, and even if we could draw a correlation, there would be a question of causality and a question of culture. Do homicide rates affect gun laws, or do gun laws affect homicide rates? Certainly gun ownership rates tend to depress gun laws because of the ballot box. And so on.

This is interesting, and new to HWFO. We haven’t done a specific look at bivariate correlation between firearm homicide and poverty, but have mentioned the relationship between GINI coefficient (wealth inequality) and homicide several times. (1) (2) (3) The AJPH study in (1) found GINI coefficient to be about five times more predictive than gun ownership rate for firearm homicide, in their multivariate analysis.

The same AJPH study found black population ratio to be slightly more predictive than even GINI coefficient, which we spoke about in (1) as well. That’s born out in this bivariate graph. It’s important to note here, that black poverty is a confounder in each of the prior two graphs.

This graph should look very familiar. We’ve presented these sorts of graphs for the USA, for Europe, for the World, for violent countries, and for peaceful countries. We’ve done them for the Human Development Index Top 20. We’ve also had fun unraveling angry twitter trolls attempts to warp them with bad statistical procedures. That last link is probably the most entertaining of the three, albeit least informative, if you’re in the mood to dive down internet rabbit holes.

This is new for HWFO. I haven’t seen something like this done before, but it’s curious that the regions chosen loosely match our recent attempt to carve the country up into four smaller countries based on college football conferences. (or cultural history, which turns out to be the same thing) I don’t think we can take much from this graph without adjusting for racial confounders, since lots of black folks live in the south.

I present these graphs for completeness with the imgur album, but can’t comment much on what it means without knowing how the regression was done.