Skip to content

Month: February 2012

The Good, the Bad, and the Stranger

Once upon a time, in a land far away, there lived two brothers. The first brother was like an ox: strong, dutiful, and hard-working. The second brother was like a rotten apple – useless, menacing, and foul. The first brother set up a small enterprise, which quickly took root and sprawled. Soon, he needed to hire a helping hand. He could either employ his brother, who was wicked and lazy but still a relation, or a Stranger, who was diligent and qualified, but came from some distant God-forsaken place. At this point the story forks and you, the reader, have to choose which path to take: – You hire the stranger. The enterprise grows and prospers. Your brother vanishes in misery. Every Christmas you send him a present to an address he has long abandoned. This is the way of the capitalist. – You hire the brother. He might be trouble, but he is of your own blood. And, on his advice, you close your community to strangers. Soon, your brother stops showing up for work, and when he does, he shows up drunk. You quarrel and curse, but you stay loyal, and the enterprise rapidly goes into wreck. But you go down together. This is the way of the nationalist. – You hire the stranger. Every month you take a generous slice from your profit and a big cut from the stranger’s salary, and you give them to your brother. Your brother acquires a big TV, junk food addiction, and…

No use for big data in electioneering, according to Hollywood

Over the last year two major Hollywood movies that touch upon the use of big data and sophisticated data analysis hit the big screen. Which, of course, is two more than the mean (or was that the median). Moneyball shows how crunching numbers helps win baseball games and Margin Call shows how crunching numbers helps ruin financial firms. It’s kind of fun to see Brad Pitt and Kevin Spacey stare at spreadsheets and nod approvingly while being explained some statistical subtleties. But watching someone stare at somebody else’s spreadsheets quickly becomes tiresome … which probably explains why Regressing with the Stars, Dotchart Master, and America’s Next Multilevel Model haven’t yet taken over reality TV. So I was really disappointed to see that a third 2011 movie – The Ides of March – misses a golden opportunity to show the use of big data and sophisticated analysis for winning elections. The movie revolves around the primary presidential campaign of George Clooney (pardon, Governor Mike Morris) and the dirty politics behind the scenes. But for Hollywood in 2011, electioneering is still a game of horse-trading, media spinning and good-ol’ stabs in the back. All these things about election campaigns are probably true, but I was disappointed that there were no fancy graphs plotting approval ratings and prediction market quotes, no real-time election forecasts (or nowcasts) at which  George Clooney to stare and nod approvingly, no GIS-supported campaign targeting, not even focus groups, twits, facebook pages, not to speak of google circles. Now,…


Science visualization challenge 2011 192 answers to the question ‘What is your favorite deep, elegant, or beautiful explanation?’ Higher education for the masses [commentary by Felix Salmon] Researchers feel pressure to cite superfluous papers

Writing with the rear-view mirror

Social science research is supposed to work like this: 1) You want to explain a certain case or a class of phenomena; 2) You develop a theory and derive a set of hypotheses; 3) You test the hypotheses with data; 4) You conclude about the plausibility of the theory; 5) You write a paper with a structure (research question, theory, empirical analysis, conclusions) that mirrors the steps above. But in practice, social science research often works like this: 1) You want to explain a certain case or a class of phenomena; 2) You test a number hypotheses with data; 3) You pick the hypotheses that matched the data best and combine them in a theory; 4) You conclude that this theory is plausible and relevant; 5) You write a paper with a structure (research question, theory, empirical analysis, conclusions) that does not reflect the steps above. In short, an inductive quest for a plausible explanation is masked and reported as deductive theory-testing. This fallacy is both well-known and rather common (at least in the fields of political science and public administration). And, in my experience, it turns out to be tacitly supported by the policies of some journals and reviewers. For one of my previous research projects, I studied the relationship between public support and policy output in the EU. Since the state of the economy can influence both, I included levels of unemployment as a potential omitted variable in the empirical analysis. It turned out that lagged unemployment is positively related to the volume of policy output. In the paper, I mentioned this result in passing…