The devil wears poverty rates

What could be more hipster than development statistics?

Dear creators of StatAttak, designers of development statistics-based clothes,

Today I stumbled upon your website, thanks to the twitter feed of Texas In Africa. I read your insightful story on how you came to care about development statistics:

…we came across ‚ÄúLife Expectancy at Birth.‚ÄĚ Andorra was the highest with 83.51 years, and all the way at the bottom was Mozambique with 31.1 years. This shocked and horrified us, especially since the average age of our small company is just under 28 years old. We spent the next couple of weeks telling this horrible statistic to everyone we met. Everyone we told was as shocked and appalled as we were. We quickly realized that telling people individually was gonna take too long, so we came up with the idea of StatAttak ‚Äď a t-shirt line based on statistics that people should be aware of. This way people would become walking billboards for these stats, and they would help spread the word. The hope is that once you see these numbers, you can‚Äôt help but want to change them.

What a fantastic idea – instead of donating money to charities have a reasonable chance of helping the poor, I can instead shell out $25 for a stylish, if illegible, t-shirt which will help raise that immeasurable asset of “awareness,” albeit only after some confused, drunken explanations at the parties I will be attending with said shirt.

Thank you StatAttak, for taking the context out of the statistics, allowing me to “make people want to change them”, even if I’m not giving them the slightest clue how best to do so.

Regards,

Matt Collin

PS – Even with my boring, un-statistical clothing, I get the feeling that I’m always a few years behind the fashion trends. T-shirts with time-varying statistics on them might go out of fashion a little faster (then again, even if Angola’s poverty rate is lower a year later, who’s going to know, right?)

Schr√∂dinger’s cat and the fall of African poverty

Poverty doesn't fall until we realize it's falling.

Poverty doesn't fall until we realize it's falling.

A new working paper by income-estimation guru Xavier Sala‚Äźi‚ÄźMartin (who still has the best homepage of any academic economist out there) and Maxim Pinkovskiy. The headline-worthy claims are all in the abstract:

The conventional wisdom that Africa is not reducing poverty is wrong. Using the methodology of Pinkovskiy and Sala‚Äźi‚ÄźMartin (2009), we estimate income distributions, poverty rates, and inequality and welfare indices for African countries for the period 1970‚Äź2006. We show that:

  1. African poverty is falling and is falling rapidly.
  2. If present trends continue, the poverty Millennium Development Goal of halving the proportion of people with incomes less than one dollar a day will be achieved on time.
  3. The growth spurt that began in 1995 decreased African income inequality instead of increasing it.
  4. African poverty reduction is remarkably general: it cannot be explained by a large country, or even by a single set of countries possessing some beneficial geographical or historical characteristic. All classes of countries, including those with disadvantageous geography and history, experience reductions in poverty. In particular, poverty fell for both landlocked as well as coastal countries; for mineral‚Äźrich as well as mineral‚Äźpoor countries; for countries with favorable or with unfavorable agriculture; for countries regardless of colonial origin; and for countries with below‚Äź or above median slave exports per capita during the African slave trade.

This is potentially exciting stuff which could do a lot to defeat the notion that African nations are permanently trapped in poverty, as well as underscore the importance of economic growth as a necessary (but perhaps not sufficient) mechanism for improving the lives of the poor.

I haven’t read the paper in detail yet, so I can’t make specific comments about its assumptions, but there are general reasons we should be wary about getting too excited. Some of the data use the infamous Penn World Tables, a series of GDP and purchasing power parity (PPP) estimates, which are constantly being revised and are often accused of being unreliable.

The accepted facts about poverty and income distribution around the world can change quite quickly when the basic assumptions behind the data and the functional forms evolve. It was only a few years ago when World Bank revisions dropped several million people back into poverty. The art of poverty estimation is like a strange, warped example of Schr√∂dinger’s cat, where many possibilities exist but we are unable to let the waveform collapse on a definitive result. This makes it particularly tricky for organisations to make precise statements about targeting the poor when we don’t even know how many there are (not that these concerns give them any pause).

Still, Sala‚Äźi‚ÄźMartin knows this stuff better than most. His assumptions are out there. Now is the time for those assumptions and their implications to be debated, not for the pundit war which will inevitably happen.

It would also be nice to see some positive media coverage, although I don’t expect that will happen.