End Poverty Day tomorrow comes among heightened discussion about poverty’s causes, its measurement and what we can do to end it.
The international extreme poverty line has been updated to $1.90/day, the recent Global Monitoring Report projects that the number of people living below this line will fall below 10% this year, and the Bank has just announced it’s stepping up efforts to boost data collection in the poorest countries, many of which suffer from “data deprivation”.
New Poverty Data Widget
These headlines are great, but how do you actually get to the data? If you want to quickly find how many people live below the international poverty line in a given country, you can use and embed this new widget that’s connected to the World Bank’s PovCalNet database:
4 more ways of accessing poverty data
Here are some other tools I find useful for accessing poverty data:
The share of the global population that is working-age has peaked at 66% and is now on the decline. The share of the elderly is anticipated to almost double to 6% by 2050, while the global count of children is stabilizing at 2 billion. Read more.
- We’ve talked before about population and life expectancy so it’s no surprise that we’re fond of Nathan Yau’s superb visualization “Years you have left to live, probably” which presents US survival curves in a refreshing manner.
- The World Bank has just updated the international poverty line from $1.25 to $1.90 per day. There’s a lot to read about both the rationale behind, and the implications of this revision. A good place to start is this blog by our colleagues in the research department and the associated technical paper explaining the data, methodology and results. If you’re a little more visually inclined, we’ve also produced a series of “understanding poverty” explainers.
- Like me, David Evans is a fan of “The Martian” - Andy Weir’s hit novel that’s just received the hollywood treatment. In the story, hundreds of millions are spent trying to bring astronaut Mark Watney home from Mars. David quotes Richard Thaler who notes “we rarely allow any identified life to be extinguished solely for the lack of money. But of course thousands of “unidentified” people die every day for lack of simple things like mosquito nets, vaccines, or clean water.” More on why the difference between an “identified life” and a “statistical life” matters.
As we continue to see headlines and editorials almost every day about migrants and refugees, it's not surprising when UNHCR reports that the number of forcibly displaced people has reached 60 million worldwide for the first time since World War II. This figure includes internally displaced people, refugees, and asylum seekers.
While many are on the move as refugees, others migrate willfully at rates that have also reached unprecedented levels. Below, I've explored some trends in regional, country- and economic-level migration and refugee data. But first: What's the difference between a migrant and a refugee?
According to UNHCR, a refugee is any person who has been forced to flee their country of origin because of a fear of persecution. A migrant, on the other hand, is one who leaves their country voluntarily for reasons such as employment, study, or family reunification. A migrant is still protected by their own government while abroad, while a refugee lacks protection from their country of origin.
Here are some things that caught our attention last week:
You’ve probably seen one or more of the hundreds of proofs of the Pythagorean Theorem but I was delighted to see that the Bank’s Chief Economist Kaushik Basu has added his own proof to the list which uses a nice little lemma about isosceles triangles.
“If you can write a for-loop you can do statistical analysis” says Jake Vanderplas in his fine presentation on “Statistics for Hackers”. While there are a lot of “statistics for x kind of person” tutorials, I like this one for using fairly intuitive computation approaches.
I enjoyed two episodes of some regularly listened to podcasts last week - “Partially Derivative - The Data of Everything” hosted by Vidya Spandana, Jonathan Morgan, and Chris Albon who hosted an illuminating show on “The Data of Journalism”. And over on Jon Schwabish’s PolicyViz Podcast, NPR’s Alyson Hurt spoke about their newsroom dataviz workflow.
On a sad note, Jake Brewer died suddenly this weekend. A model public servant, he was a huge believer in the power of civic technology to improve people’s lives, and I count myself among the thousands of people inspired by his work and thinking.
And we’re back! Here are some things that caught our attention last week:
“Freedom to Tinker” is one of my favorite blogs. The folks at Princeton’s Center for Information Technology Policy have a habit of discussing the most interesting issues at the intersection of technology, society and policy. Last week they discussed how “Ancestry.com can use your DNA to target ads”
Glenn Mcdonald from music technology company EchnoNest built the charming visual application “Every Noise at Once” which provides an “algorithmically-generated, readability-adjusted scatter-plot of the musical genre-space, based on data tracked and analyzed for 1385 genres” With samples.
On the theme of data visualization, how about some “Data Physicalization”? Pierre Dragicevic and Yvonne Jansen maintain this fantastic list of physical visualizations ranging from Mesopotamian clay tokens to the London Eye used as a donut chart. Now where did I put my 3D printer?
OK, one more visualization (and potentially enormous distraction if you’re so inclined) “The True Size Of” lets you pick countries on a (Mercator projected) map and drag them around to compare their “real” sizes. Obligatory XKCD.
If you’re in the data science business these days, the chances are you’ve used Amazon Web Services or AWS. You will also know that they like to name their services things like “Elastic Beanstalk” or “Swinging Orangutan” which is charming, but unhelpful. The folks at Expedited SSL wrote a great primer on “AWS in Plain English”. And I was (probably) kidding about the Orangutan.
Last week, the UN released updated population figures and projections. I just had a chance to go through them and the great key findings document (PDF, 1MB) that accompanies them.
But before I dive in, how accurate are these projections? What kind of track record do UN demographers have? The most comprehensive answer I could find was Nico Keilman’s 2001 paper which Hans Rosling refers to in this video. He notes that in 1958, when the UN projected the population in 2000 to be ~6 Billion (it was then 42 years into the future) they ended up being out by less than 5%. The short answer is: these projections are pretty good.
There are 7.3 billion people alive today and while the world’s population continues to grow, it’s growing more slowly than in the past. We can expect to see an additional billion people added over the next 15 years, and about a billion more 10 years later, reaching a total population of 9.7 billion in 2050.
Here are some things that caught our attention last week:
If you’re anything like me, you’re a sucker for algorithm visualization. These sorting algorithm animations and Mike Bostock’s visualizations of sampling, shuffling, sorting and maze generation are among my favorites. So I was delighted to find R2D3’s Visual Introduction to Machine Learning.
Dat is like Git for data - a “version-controlled, decentralized data tool for collaboration between data people and data systems.” It’s a much-needed tool and the development team just announced that it’s hit beta status - do check it out.
Trade blocs are intergovernmental agreements intended to bring economic benefits to their members by reducing barriers to trade.
Some well known trade blocs include the European Union, NAFTA and the African Union. Through encouraging foreign direct investment, increasing competition, and boosting exports, trade blocs can have numerous benefits for their members.
In Latin America, Mercosur and the more recently formed Pacific Alliance blocs together represent about 93 percent of the region's GDP at 2014 market prices. Who participates in these trade blocs and how do they compare?
Size, membership and performance of Mercosur and The Pacific Alliance
The Pacific Alliance is a Latin American trade bloc formed in 2011 among Chile, Colombia, Mexico, and Peru. Together the four countries have a combined population of about 221.3 million and GDP of $2.1 trillion. The Southern Common Market (Mercosur) created in 1991, includes Argentina, Brazil, Paraguay, Uruguay, and Venezuela. Together the five Mercosur countries have 285.0 million inhabitants and GDP of $3.5 trillion.
One of the areas intended to benefit from these agreements, trade within the blocs, accounts for about 4 percent of the Pacific Alliance's total trade and about 14 percent in Mercosur.