What Really Happened to Nigeria’s Economy?

You may have heard the news that the size Nigeria’s economy now stands at nearly $500 billion. Taken at face value (as many commenters have seemed all to happy to do) this means that the West African state “overtook” South Africa’s economy, which was roughly $384 billion in 2012. Nigeria’s reported GDP for that year was $262 billion, meaning it roughly doubled in a year.

How did this “growth” happen? As Bloomberg reported:

On paper, the size of the economy expanded by more than three-quarters to an estimated 80 trillion naira ($488 billion) for 2013, Yemi Kale, head of the National Bureau of Statistics, said at a news conference yesterday to release the data in the capital, Abuja….

The NBS recalculated the value of GDP based on production patterns in 2010, increasing the number of industries it measures to 46 from 33 and giving greater weighting to sectors such as telecommunications and financial services.

The actual change appears to be due almost entirely to Nigeria including figures in GDP calculation that had been excluded previously. There is nothing wrong with this, per se, but it makes comparisons completely unrealistic. This would be like measuring your height in bare feet for years, then doing it while wearing platform shoes. Your reported height would look quite different, without any real growth taking place. Similar complications arise when comparing Nigeria’s new figures to other countries’, when the others have not changed their methodology.

Nigeria’s recalculation adds another layer of complexity to the problems plaguing African development statistics. Lack of transparency (not to mention accuracy) in reporting economic activity makes decisions about foreign aid and favorable loans more difficult. For more information on these problems, see this post discussing Morten Jerven’s book Poor NumbersIf you would like to know more about GDP and other economic summaries, and how they shape our world, I would recommend Macroeconomic Patterns and Stories (somewhat technical), The Leading Indicators, and GDP: A Brief but Affectionate History.

Constitutional Forks Revisited

Around this time last year, we discussed the idea of a constitutional “fork” that occurred with the founding of the Confederate States of America. That post briefly explains how forks work in open source software and how the Confederates used the US Constitution as the basis for their own, with deliberate and meaningful differences. Putting the two documents on Github allowed us to compare their differences visually and confirm our suspicions that many of them were related to issues of states’ rights and slavery.

Caleb McDaniel, a historian at Rice who undoubtedly has a much deeper and more thorough knowledge of the period, conducted a similar exercise and also posted his results on Github. He was faced with similar decisions of where to obtain the source text and which differences to retain as meaningful (for example, he left in section numbers where I did not). My method identifies 130 additions and 119 deletions when transitioning between the USA and CSA constitutions, whereas the stats for Caleb’s repo show 382 additions and 370 deletions.

What should we draw from these projects? In Caleb’s words:

My decisions make this project an interpretive act. You are welcome to inspect the changes more closely by looking at the commit histories for the individual Constitution files, which show the initial text as I got it from Avalon as well as the changes that I made.

You can take a look at both projects and conduct a difference-in-differences exploration of your own. More generally, these projects show the need for tools to visualize textual analyses, as well as the power of technology to enhance understanding of historical and political acts. Caleb’s readme file has great resources for learning more about this topic including the conversation that led him to this project, a New York Times interactive feature on the topic, and more.

Don’t Forget Your Forever Stamps

The price of a first-class US stamp is set to increase from 46 to 49 cents on January 26. Like Cosmo Kramer’s Michigan bottle redemption plan (see below), Allison Schrager and Ritchie King ran the numbers on whether it would be possible to provide from Forever Stamp arbitrage.

Could the scheme make money? Maybe–if you get the timing right and pay low interest on capital:

Assuming we sell all 10 million stamps for the bulk discount price of $0.475 each, our profit will be $150,000. Subtract out the $399 for the distributor database. Let’s also assume we spent the $3,500 for Check Stand Program plus, say, $300 to make the 100 displays for advertising in stores. That gives us $145,801.

If we do manage to shift the stamps in a month, the interest on our debt will be $29,000. That brings our profits to $116,801. Then we’ll return the equity to our shareholders, along with 50% of the profits.

That leaves us with the other 50%: $58,400.50. If you look at that as a profit on the $4.6 million initial outlay, it’s not very much: less than 1.3%. But remember, all that outlay was leveraged. So if you look at it as a return on our investment—$33.25 for shipping—it’s 175,541%.

Github for Government

What happens when you combine open source software, open data, and open government? For the city of Munich, the switch to open source software has been a big success:

In one of the premier open source software deployments in Europe, the city migrated from Windows NT to LiMux, its own Linux distribution. LiMux incorporates a fully open source desktop infrastructure. The city also decided to use the Open Document Format (ODF) as a standard, instead of proprietary options.

As of November last year, the city saved more than €11.7 million because of the switch. More recent figures were not immediately available, but cost savings were not the only goal of the operation. It was also done to be less dependent on manufacturers, product cycles and proprietary OSes, the council said.

We’ve talked before about how more city governments could follow the open data, open government initiatives of NYC, using tech to benefit citizens rather than (only) creating initiatives to attract tech companies to the area. This shift in emphasis, toward harnessing the power of technology for widespread gains in happiness, is likely to become even more important following recent protests against tech employees in the Bay Area.

Open data and open government will take the principles of open source and use them to make an even bigger social and political impact. One tool from open source that can be adapted for use by these newer movements is Github. We will continue to follow these trends here, and if you are interested in this trend you can also check out Github and Government for more success stories.

What Can We Learn from Games?

ImageThis holiday season I enjoyed giving, receiving, and playing several new card and board games with friends and family. These included classics such as cribbage, strategy games like Dominion and Power Grid, and the whimsical Munchkin.

Can video and board games teach us more than just strategy? What if games could teach us not to be better thinkers, but just to be… better? A while ago we discussed how monopoly was originally designed as a learning experience to promote cooperation. Lately I have learned of two other such games in a growing genre and wanted to share them here.

The first is Depression Quest by Zoe Quinn (via Jeff Atwood):

Depression Quest is an interactive fiction game where you play as someone living with depression. You are given a series of everyday life events and have to attempt to manage your illness, relationships, job, and possible treatment. This game aims to show other sufferers of depression that they are not alone in their feelings, and to illustrate to people who may not understand the illness the depths of what it can do to people.

The second is Train by Brenda Romero (via Marcus Montano) described here with spoilers:

In the game, the players read typewritten instructions. The game board is a set of train tracks with box cars, sitting on top of a window pane with broken glass. There are little yellow pegs that represent people, and the player’s job is to efficiently load those people onto the trains. A typewriter sits on one side of the board.

The game takes anywhere from a minute to two hours to play, depending on when the players make a very important discovery. At some point, they turn over a card that has a destination for the train. It says Auschwitz. At that point, for anyone who knows their history, it dawns on the player that they have been loading Jews onto box cars so they can be shipped to a World War II concentration camp and be killed in the gas showers or burned in the ovens.

The key emotion that Romero said she wanted the player to feel was “complicity.”

“People blindly follow rules,” she said. “Will they blindly follow rules that come out of a Nazi typewriter?”

I have tried creating my own board games in the past, and this gives me renewed interest and a higher standard. What is the most thought-provoking moment you have experienced playing games?

The Economy That Is Stanford

Five of the six most-visited websites in the world are here, in ranked order: Facebook, Google, YouTube (which Google owns), Yahoo! and Wikipedia. (Number five is a Chinese-language site.) If corporations founded by Stanford alumni were to form an independent nation, it would be the tenth largest economy in the world, with an annual revenue of $2.7 trillion, as some professors at that university recently calculated. Another new report says: ‘If the internet was a country, its gross domestic product would eclipse all others but four within four years.’

That’s from this London Review of Books piece by Rebecca Solnit. The October, 2012, research report on which the claim is based is here, based on survey data. Solnit’s piece is interesting throughout, including a discussion of parallels and differences between the tech boom and the Gold Rush.

Political Forecasting and the Use of Baseline Rates

As Joe Blitzstein likes to say, “Thinking conditionally is a condition for thinking.” Humans are not naturally good at this skill. Consider the following example: Kelly is interested in books and keeping things organized. She loves telling stories and attending book clubs. Is it more likely that Kelly is a bestselling novelist or an accountant?

Many of the “facts” about Kelly in that story might lead you to answer that she is a novelist. Only one–her sense of organization–might have pointed you toward an accountant. But think about the overall probability of each career. Very few bookworms become successful novelists, and there are many more accountants than (successful) authors in the modern workforce. Conditioning on the baseline rate helps make a more accurate decision.

I make a similar point–this time applied to political forecasting–in a recent blog post for the blog of Mike Ward’s lab (of which I am a member):

One piece of advice that Good Judgment forecasters are often reminded of is to use the baseline rate of an event as a starting point for their forecast. For example, insurgencies are a very rare event on the whole. For the period January, 2001 to August, 2013, insurgencies occurred in less than 10 percent of country-months in the ICEWS data set.

From this baseline, we can then incorporate information about the specific countries at hand and their recent history… Mozambique has not experienced an insurgency for the entire period of the ICEWS dataset. On the other hand, Chad had an insurgency that ended in December, 2003, and another that extended from November, 2005, to April, 2010. For the duration of the ICEWS data set, Chad has experienced an insurgency 59 percent of the time. This suggests that our predicted probability of insurgency in Chad should be higher than for Mozambique.

I started writing that post before rebels in Mozambique broke their treaty with the government. Maybe I spoke too soon, but the larger point is that baselines are the starting point–not the final product–of any successful forecast.

Having more data is useful, as long as it contributes more signal than noise. That’s what ICEWS aims to do, and I consider it a useful addition to the toolbox of forecasters participating in the Good Judgment Project. For more on this collaboration, as well as a map of insurgency rates around the globe as measured by ICEWS, see the aforementioned post here.

A Chrome Extension for XKCD Substitutions

This morning’s XKCD had some fun suggestions for replacing key phrases to make news articles more fun:

Regular readers may recall my Doublespeak Chrome extension, which works on the same principle. In short order, I was able to create a new app, XKCDSub, that works the same way: install the extension, and when you click its icon it will open your current page in a new tab with the phrases replaced. Here is an example of the extension in action on Elon Musk’s Wikipedia page:

elon

The code is open source on Github. You can find it in the Chrome webstore here.

The Economics of Movie Popcorn

The Smithsonian’s Food & Think blog recounts a long history of movie theaters’ objections to popcorn. They wanted to be as classy as live theaters. Nickelodeons didn’t have ventilation required for popcorn machines. Moreover, crunchy snacks would have been unwelcome during silent films.

But moviegoers still wanted their popcorn, and street vendors met their demand. This led to signs asking patrons to check their coats and their corn at the theater entrance.

Eventually, movie theater owners realized that if they cut out the middleman, their profits would skyrocket.  For many theaters, the transition to selling snacks helped save them from the crippling Depression. In the mid-1930s, the movie theater business started to go under. “But those that began serving popcorn and other snacks,” Smith explains, “survived.” Take, for example, a Dallas movie theater chain that installed popcorn machines in 80 theaters, but refused to install machines in their five best theaters, which they considered too high class to sell popcorn. In two years, the theaters with popcorn saw their profits soar; the five theaters without popcorn watched their profits go into the red.

Much more here, including how movie theater demand changed the types of popcorn that are grown.

PopcornPortionSizeExample

Popcorn and other concessions are important to theaters because a large percentage of ticket sales (especially during the first couple of weeks after a movie premieres) go to the studio. Recent figures I’ve seen are that concession sales are 80-90 percent profit, whereas in the opening weekend only about 20 percent of the sale price goes to the theater. This means that concessions can make up nearly half the profit for a theater–no wonder they try to keep viewers from bringing in their own refreshments.

Small bags of popcorn have now turned into buckets, perhaps in an effort to justify charging $8-10 rather than the nickel such snacks sold for when “talkies” were new. This transition is covered in the book Why Popcorn Costs So Much at the Movies and an interview with the author is here.

 

Visualizing Political Unrest in Egypt, Syria, and Turkey

The lab of Michael D. Ward et al now has a blog. The inaugural post describes some of the lab’s ongoing projects that may come up in future entries including modeling of protests, insurgencies, and rebellions, event prediction (such as IED explosions), and machine learning techniques.

The second post compares two event data sets–GDELT and ICEWS–using recent political unrest in the Middle East as a focal point (more here):

We looked at protest events in Egypt and Turkey in 2011 and 2012 for both data sets, and we also looked at fighting in Syria over the same period…. What did we learn from these, limited comparisons?  First, we found out first hand what the GDELT community has been saying: the GDELT data are in BETA and currently have a lot of false positives. This is not optimal for a decision making aid such as ICEWS, in which drill-down to the specific events resulting in new predictions is a requirement. Second, no one has a good ground truth for event data — though we have some ideas on this and are working on a study to implement them. Third, geolocation is a boon. GDELT seems especially good a this, even with a lot of false positives.

The visualization, which I worked on as part of the lab, can be found here.  It relies on CartoDB to serve data from GDELT and ICEWS, with some preprocessing done using MySQL and R. The front-end is Javascript using a combination of d3 for timelines and Torque for maps.

gdelt-icews-static

GDELT (green) and ICEWS (blue) records of protests in Egypt and Turkey and conflict in Syria

If you have questions about the visualizations or the technology behind them, feel free to mention them here or on the lab blog.