Burden Sharing in NATO

Late last week we heard a lot about contributions to NATO. Except, that was not true. Because the idea of spending 2% of GDP on NATO is actually about a NATO member spending 2% of its GDP on its military. And within that 2%, at least 20% must be spent on hardware or R&D. There is a separate operating budget to which countries actually contribute funds. But before we look at all of this as a whole, I wanted to explore the burden sharing, which is what NATO terms the 2% of GDP defence expenditures.

I did something similar a couple of years ago back in 2014 during the height of the Russia–Ukraine crisis. However, here I looked at a narrower data set from 2011 to 2018 and then across all the NATO members. In 2014, NATO met in Wales and agreed that over the next ten years all members would increase their defence spending to 2% of GDP. We are only four years into that ten year plan and so most of these countries still have time to reach that level.

That's still a whole lot spent on defence
That’s still a whole lot spent on defence

Credit for the piece is mine.

Kavanaugh the Conservative

Last night President Trump nominated Merrick Garland to fill the seat left by Anthony Kennedy. Just kidding. But he is up for a vote in the Senate. Also just kidding.

No, instead, President Trump nominated a very conservative judge for the Supreme Court, Brett Kavanaugh. How conservative? Well, FiveThirtyEight explained in a piece that plotted the judge against his probably peers on the bench, based upon one measure of judicial ideology. And it turns out, spoiler, Kavanaugh sits just to the left of Clarence Thomas. And he sits pretty well to the right.

To the right, to the right, to the right goes the Court
To the right, to the right, to the right goes the Court

The graphic itself is an evolution of a piece from last Friday that looked at what were thought to be the four main candidates on Trump’s shortlist.

A definite lean to the right
A definite lean to the right

The final piece, with only Kavanaugh plotted, removes the other potential candidates. And it functions well, using the brighter orange to draw attention from the black dots of the sitting bench and the open dot of the vacant seat. My slight issue is with the predecessor graphic that shows the four candidates.

I probably would have just left off Barrett as she did not have a score. While I have no doubt that she would score to the right based upon all the reading I have done over the past several days, it feels a bit odd to place her on the graphic at all. Instead, I probably would have used an asterisk or a footnote to say that she did not have a score and thus was not placed.

Credit for the piece goes to Oliver Roeder and Amelia Thomson-DeVeaux.

Still a Loyalist

As most of you know, I am what would have been called a loyalist. That is, I disagree with the premise of the American Revolution. People often mistake that as saying I think Americans should be British. No, although I personally would not mind that. Instead, America would likely have been a lot more like Canada and it would have obtained its independence peacefully through an organic, evolutionary process leading to, likely, some kind of parliamentary democracy.

Every year, somebody digs up articles people have written about why the Revolution was a bad idea. I have seen a lot of them. But I had not seen this Washington Post article that looked at constitutional monarchies. It was published during the whole royal baby buzz back in 2013. It examines why constitutional monarchies are not so bad, and might even be better than presidential republics.

God save the Queen
God save the Queen

The above graphic is far from great. The same goes for the other graphic in the article. I probably would have added more emphasis on the constitutional monarchies as they get overwhelmed by the number of non-constitutional monarchies s in the scatter plot. That could be through a brighter blue or keeping the pink and setting the rest to a light grey. I perhaps would have added a trend line.

Credit for the piece goes to Dylan Matthews.

Trade with Canada

Yesterday we looked at trade with China. Today, we look at Canada, allegedly ripping off America. But what does the data say? Thankfully the Washington Post put together a piece looking at just that topic. And it uses a few interesting graphics to explore the idea.

The easiest and least controversial graphic is that below, which breaks down constituent parts of our bilateral trade.

The article also points out that very small dairy section, which is one focus of the administration's complaints. But look how tiny it is…
The article also points out that very small dairy section, which is one focus of the administration’s complaints. But look how tiny it is…

Note that the graphic does not just show the traditional goods part of the equation, but also breaks out services. And as soon as you consider that part of the economy the US trade deficit with Canada turns from deficit into surplus.

But the graphic also uses a pair of maps to look at that same goods vs. goods and services split.

The centre of it all…
The centre of it all…

Parts of the design of the map like the colours, meh. But the designers did a great job by breaking the standard convention of placing the Prime Meridian at the centre of the map. Instead, because the United States is the story here, the map places North America at the map’s centre. It does lead to a weird fracturing of the Asian continent, but so long as China is largely intact, that is all that matters to the trade story.

This all just goes to show that it is important to begin a conversation about policy with facts and understand the actual starting point rather than the perceived starting point.

Credit for the piece goes to Philip Bump.

Philly Rules

Yo. C’mon, bro. This jawn is getting tired. Just stop already.

If you did not catch it this week, the most important news was Donald Trump disinviting the Super Bowl champions Eagles to the White House to celebrate their victory over the Patriots. He then lied about Eagles players kneeling during the US anthem—no player did during the 2017 season. He then claimed that the Eagles abandoned their fans. Yeah, good luck convincing the city of that.

So naturally we have a Friday graphic for youse.

That's 25,304.
That’s 25,304.

Full disclosure: I root for the Patriots. But I mean, seriously, can’t youse guys do the math?

Primarily California

Today is primary day and everyone will be looking to the California results. Although probably not quite me, because Eastern vs. Pacific time means even I will likely be asleep tonight. But before we get to tonight, we have a nice primer from last Friday’s New York Times. It examines the California House of Representatives races that we should be following.

53 districts are a lot to follow in one night…
53 districts are a lot to follow in one night…

Like most election-related pieces, it starts with a map. But it uses some scrolling and progressive data disclosure. The map above, after a bit of scrolling, finally reveals the districts worth following and their 2016 vote margins.

Out of all 53, these are the districts the Times says to watch
Out of all 53, these are the districts the Times says to watch

From there the article moves onto a bit of an exploration of those few districts. You should read the full article—it’s a short read—for the full context on the California votes today. But it does make some nice of bar and line charts to plot the differences in presidential race vs. congressional race margins and the slow Democratic shift.

Credit for the piece goes to Jasmine C. Lee and Karen Yourish.

Forecasting the American Midterm Elections

We are inching ever closer to the US midterm elections in November. In less than a week the largest state, California, will go to the polls to elect their candidates for their districts. So late last week whilst your author was on holiday, the Economist released its forecast model for the results. They will update it everyday so who knows what wild swings we might see between now and the election.

I will strike out against the common knowledge that this is a wave election year and Democrats will sweep swaths through Republican districts in an enormous electoral victory. Because while Democrats will likely win more overall votes across the country, the country’s congressional districts are structurally designed to favour Republicans as a result of gerrymandering after the 2010 Census redistricting. The Economist’s modelling handles this fairly well, I think, as it prescribes only a modest majority and gives that likelihood as only at 2-in-3. (This is as of 30 May.)

But how is it designed?

The big splashy piece is an interactive map of districts.

The overall state of the US in the 30 May run of the model
The overall state of the US in the 30 May run of the model

It does a good job of connecting individual districts to the dots below the map showing the distribution of said seats into safe, solid, likely, leaning, and tossup states. However, the interactivity is limited in an odd way. The dropdown in the upper-right allows the user to select any district they want and then the district is highlighted on the map as well as the distribution plot below. Similarly, the user can select one of the dots below the map to isolate a particular district and it will display upon the map. But the map itself does not function as a navigation element.

Selecting the newly drawn Pennsylvania 6th
Selecting the newly drawn Pennsylvania 6th

I am unsure why that selection function does not extend to the map because clearly the dropdown and the distribution plot are both affecting the objects on the map. Redeeming the map, however, are the district lines. Instead of simply plopping dots onto a US state-level map, the states are instead subdivided into their respective congressional districts.

But if we are going so far as to display individual districts, I wonder if a cartogram would have been a better fit. Of course it is perfectly plausible that one was indeed tried, but it did not work. The cartogram would also have the disadvantage of, in this case, not exhibiting geographically fidelity and thus being unrecognisable and therefore being unhelpful to users.

Now the piece also makes good use of factettes and right-left divisions of information panels to show the quick hit numbers, i.e. how many seats each party is forecast to win in total. But the map, for our purposes, is the big centrepiece.

Overall, this is solid and you better bet that I will be referencing it again and again as we move closer to the midterms.

Credit for the piece goes to the Economist Data Team.

Irish Abortion Referendum

On Saturday Ireland announced the results of a referendum on changing its constitution to remove Article 8, which had made abortion illegal except in the case of risk of death to the mother. And that was it, none of the usual rape or incest clauses. I want to look at a little coverage of the results and we will start with the Irish Times.

I might have toned down the red a wee bit, though
I might have toned down the red a wee bit, though

Their presentation is straightforward, a parliamentary-like slider and a small choropleth. All the colours link to each other and you will note that at first glance there is no variation in the colours on the map. Instead they present the binary choice, yes or no. To get the details of the vote, the user needs to select the Yes% or No%. From those we see not a lot of variation—probably not unsurprising given the overwhelmingness of the vote—as the Dublin area had the most yes, the rest of Ireland fairly solidly yes, and only Donegal in the northwest voting no, and even then, barely so.

I'm not quite loving these colours at all…
I’m not quite loving these colours at all…

But then we have the Guardian’s results map. And I am a wee bit lost. The bin definitions offer a bit more granular detail and so the sweeping results from the Irish Times results can here be seen as a bit more simplified. I probably would have shifted the colours and kept the yes on one side of the spectrum and not mixed the yellows and oranges into the positive, or yes, side. The stunning part of the result was, after all, that only Donegal voted no. So I would expect the colour of the choropleth to reflect that sharp break and less the gradation seen here. It’s a curious choice.

But more importantly, I am left wondering about the data, the titles, or the descriptions—I cannot be sure. The key bit is the callout of Roscommon-Galway. The text says the constituency voted 57.2% yes. But the colour would seem to indicate that it voted 65–69% no. A simple mistake? Perhaps. But then I look at the wording of the legend and maybe not. Could percentage of yes vote mean something more like the expected total or the percentage of registered voters? Probably not, but I cannot quite figure out what is going on in Roscommon-Galway. And if it is a data error, it is only made more noticeable because they point out that is one of only two constituencies described in the text.

Post script: After writing this and doing some more investigation over the long holiday weekend, I found a different map that appears to be more in sync with the results. The above was probably a mistake that just didn’t get pulled down and replaced. Below is the correct one. But it goes to show you how an incorrect graphic can cause confusion.

There we go.
There we go.

Credit for the Irish Times piece goes to the Irish Times graphics department.

Credit for the Guardian piece goes to the Guardian graphics department.

Gun Control Legislation

Back in March I posted about a great graphic from the New York Times editorial board they made in the wake of the Parkland, Florida school shooting. Saturday morning, the day after Friday’s Santa Fe, Texas school shooting, I was reading the paper and found the updated graphic.

That is a whole lot of months since Sandy Hook…
That is a whole lot of months since Sandy Hook…

Yeah, almost nothing has changed. Congress passed and the president signed an omnibus spending bill that included language to improve reporting on background checks.


Now from a design standpoint, what’s nice about this graphic is its restrained use of colour. The whole piece works in black and white. Of course it helps that there is nothing to show that needs to be highlighted in the data.


Credit for the piece goes to the New York Times graphics department.

Turning the Midwest Red

Continuing with election-y stuff, I want to share a fascinating map from the Washington Post. The article came out last week, and it is actually incredibly light in terms of data visualisation. By my count, there were only two maps. The article’s focus is on interviews with Trump voters in 2016 and how their opinions of the president have changed over the last year or so. If you want to read it, and you should as it is very well written, I will warn you that it is long. But, to the map.

I may have used an even lighter shade for 2012 counties…
I may have used an even lighter shade for 2012 counties…

What I loved about this map is how it flips the usual narrative a bit on its head. We talk about how much a candidate won a county in 2016, or even how much the vote shifted in 2016. And anecdotally we talk about “ancestral Democrats” flipping to Trump. But this map actually tries to chart that. It reveals the last time a county actually voted for a Republican presidential candidate—the darker the red, the further back in time one has to go.

Counties that vote Democratic are white, because why do we need them for this examination. Omitting them was a great design decision. Much of the country, as we know or can intuit, voted Republican in 2012 for Mitt Romney. But what about before then? You can see how the upper Midwest, along the Mississippi River, was a stronghold for Democrats with some counties going as far back as the 1980s or earlier. And then in 2016 they all flipped and that flipping was most significant there—of some additional interest to me are the counties in Maine, the Pacific Northwest, and along Lake Erie near Cleveland.

In short, this was just a brilliantly done map. And it sets the tone for the rest of the article, which is interviews with residents of those counties called out on the map.

Credit for the piece goes to Andrew Braford, Jake Crump, Jason Bernert and Matthew Callahan.