First, I scraped data on participation at all Olympic games from 1896 to 2012 from Sports Reference.com. I’m only going to comment on the summer games here. Before we start, an important note: This is a silly throw away project and I in no way verified the quality of the Sports Reference data. Caveat Emptor.
To start, let’s look at how the gender balance of each team’s Olympic athletes changes over time. Each grey line is one of 225 countries that participated in at least one Olympic games. The black line is the cross-team average for each games. Note that the black line doesn’t tell you the overall fraction of women competing in each games because it counts every country equally rather than every athlete. Female participation is trending up and it begins a real climb in the mid 1980s.
In a very weak sense, this seems consistent with my hunch above: we know that from 1896 to the present women’s rights have improved and this seems to be tracked by the fraction of women in the Olympics. However, this is really weak evidence. Let’s compare across countries to get a better sense of how female Olympics participation and women’s political participation correlate.
This next graph only uses data from the year 2012. The y-axis is the fraction of all athletes are that are female in each of 205 countries in the 2012 Olympics. The x-axis is the fraction of seats held by women in each country’s national parliament. The blue line is an OLS fit line and the grey area is a 95% confidence interval. There is absolutely no relationship between these variables.
Hmm, so that is dispiriting. I really expected a relationship, but there is just nothing. In another surprise, I compared the same Olympic data against GDP per capita. Everything covaries with GDP per capita, right? Wrong. Again, there is just nothing here. Countries that are richer, and countries with more female parliamentarians, are no more likely to have more women competing in the Olympics than poorer countries or countries with more male-dominated politics.
My analysis finished here, but I had posted the web scraping code on twitter and asked other people to analyze the data. Happily, Adam Chilton did just that. I’ve posted his graphs below.
He is looking at a gender equality index and he gets basically the same finding as me for 2000. More gender equal places do not have more women on their Olympic teams. However, he finds that there was a relationship between gender equality and female Olympic participation in 1976. I have no clue what to make of this changing pattern. My main take away from all of this was that my original hunch was wrong. It appears that the ratio of male to female Olympians is not a decent cross-national indicator of women’s rights. The null hypothesis wins.
About two weeks ago, my first child, Isaac was born. We spent a standard two days in the hospital and then went home. After about 5 hours at home, in his third day of life, Isaac developed a fever of 103 and we went straight to the ER. After a few days of tests, we learned that Isaac’s blood and kidneys were infected with enterococcus and that he probably had bacterial meningitis. This kind of thing is incredibly uncommon and no one really knows how he got infected. He was just incredibly unlucky…
…except that he really wasn’t.
For four years now, I’ve been teaching international development. One of my first questions to my students is: “If you knew nothing about yourself (e.g. gender, race) or where you would be born, when would you like to be born?” (I think I got this question originally from Angus Deaton?) The students can choose any time from the dawn of humanity to the present day. After a bit of thought, students quickly converge on “now” as the right answer. I like to stress to them that “now” is the right answer not only because the world is wealthier and more people have iPhones. Women are treated far better today than at any time in the past, more people have political freedoms today, and far fewer children die.
Isaac is doing well. He is 13 days into a 21 day course of antibiotics and in his 16th day of life. He is eating well, he is above his birth weight, he has had no seizures, he has no signs of cranial inflammation, and he is doing regular baby stuff. He is expected to make a complete recovery. Untreated, he would have almost certainly died. He is damn lucky to have been born now in America.
I’ve known these statistics (well, aside from the ones on meningitis) for some time, but they carry a lot more emotional weight now. Most babies in Isaac’s situation still die. Development is the process of making that not so.
PS
Meningitis is pretty rare, so if the thought of babies dying moves you then probably the best thing you can do at the moment is to donate to the Against Malaria Foundation. Giving out insecticide-treated bed nets is one of the most reliable ways of reducing child mortality.
PPS (April 3, 2016)
At about 6 ½ months old, Isaac is doing very well. He is at or above average on pretty much everything that we can measure. His first month of life was terrifying for us, but he really was incredibly lucky. Thanks to everyone for the well wishes.
Chris Blattman recently argued that a lot of aid spent on skills training did little to help poor people. He also asked for “comments and criticisms,” and so Tom Pepinsky followed by calling for more ethnographic research aimed at identify specific constraints on households and more political economy research on institutions. The contention is that we need to focus more on the smallest stuff (households) and the biggest stuff (national institutions). Ken Opalo agreed and emphasized the importance of working with local elites in ways that make development goals compatible with their incentives. (My paraphrasing might be misrepresenting the authors, so do read all three posts)
Now, ethnographic analyses to actually understand what is going on and careful analyses of institutions and elite interests are all Good Things, but I’m skeptical of their ability to make aid work better and I’m very skeptical of any outsider’s ability to manipulate them.
I’m thinking out loud right now, but my reading of the literature on aid effectiveness suggests to me that aid works best when donors either do simple things over and over (polio vaccine) or produce global public goods (research to boost crop production). I think this emphasis on simplicity is more contentious than it sounds. To be clear: I think that institutions and local political battles are the most important things keeping poor countries poor. I also think that these things will not be changed by aid programs, and I think trying to influence them is probably a waste of money. In that sense, I think that aid cannot solve or probably even improve on the main factors that influence long-run development. I’m pretty sure that that should not be the job of aid. Instead, I’m for targeting aid to specific things that help poor people and where impact can either be measured or where we have very good evidence that the “treatment” works. This includes a range of health measures (e.g. vaccines, bed nets) or cash transfers. There probably is room to tweak these simple interventions based on a better understanding local context, but even then I worry about the ability of actual people to carry out these tweaks well. My hunch is that “tweaks for local context” without rigorous and iterative analysis and some kind of incentive-changing feedback loop probably won’t produce the learning that would make aid more effective.
I made a twitterbot that posts pseudo-random tweets formed from samples of text from the five most recent World Development Reports. My reasons for writing the bot, in order of importance, were: I wanted to learn something new in R, I thought that the results would make me laugh, I had a little bit of time to kill at ORD after the MPSA conference, and finally, I thought that the resulting development babble might make us think a little about how development experts communicate. Here is one example tweet:
It recognized that legal equality was not revealed as shown by the expansion of the variation in crime rates in agrarian economies.
I was not aware of the recent success in the Guatemalan sugar industry. Since the 1980s, sugar production in the country has increased at an annual rate of about 7%, far outstripping similar countries. Rising production has occurred in tandem with better working conditions.
A new paper (ungated here) by Alberto Fuentes stresses the role that a “small team of managers motivated by Elite Solidarism, an interpretation of the Vatican II Catholic Social Doctrine” played in bringing about the changes. I haven’t read it carefully yet, but it strikes me as a good example of how ideas can have independent causal power. A more general version of this argument is well expressed in Dani Rodrik’s recent paper “When Ideas Trump Interests.” The two together seem like a good match for teaching about constructivism and the role of ideas in economic policy making.
