The rise of empirical econ, in one chart


Goddammit I need more memory

I apologize for the click-baiting title, but this is pretty cool. John C. McCallum has assembled a (rough) estimate of the price of computer memory (mainly RAM) over time. I’ve adjusted the prices for inflation and graphed it over time. The results are pretty amazing (keep in mind the y-axis is log-scale).


Without cheap memory, you can say goodbye to big data sets and complex calculations which really enabled empirical econ to take off. Sure, CPU speeds matters as well and the RCT folks were always a little less reliant on large data sets, but can you imagine having to bootstrap those standard errors with 2mb of RAM? File this under “things are getting better.” Hat tip to Data is Plural, a newsletter you really should subscribe to if you like random data sets.

I’m upset that my football team lost, so I’m going to have to ask you to leave the country


I AM THE LAW! Except when the Broncos lose. Then I just turn to jelly.

In the NYT, immigration judges contemplate how biases might creep into the decisions they make:

In all, 336 people from 13 countries and even more ethnic backgrounds appeared in San Francisco’s immigration court recently over three days. All of them were facing possible deportation, because they either were in the United States illegally or had committed crimes serious enough to jeopardize their legal presence as noncitizens. One challenge facing Judge Marks was deciding whether to deport some of them immediately after they had testified. Another challenge was her own biases.

“You have to go through some hypotheticals in your brain,” said Judge Marks, wrestling with the weighty decisions she must make, the little time she has to make them and all the impressions she and her judicial colleagues form from the bench about the immigrants before them.

“Would I treat a young person the same way I’m treating this old person?” she said. “Would I treat a black person the same way I’m treating this white person? This situation of rush, rush, rush as fast as we can go, it’s not conducive to doing that.”

The solution? Anti-bias training:

Now, as the country struggles with how these instinctive judgments shape our lives, the Justice Department is trying to minimize the role of bias in law enforcement and the courts. More than 250 federal immigration judges attended a mandatory anti-bias training session in August, and this summer the Justice Department announced that 28,000 more employees would go through a similar exercise.

This seems reasonable, but what about factors that influence decisions that go beyond the characteristics of the immigrant? Enter a recent (unpublished) paper by Daniel Chen:

I detect intra-judge variation in judicial decisions driven by factors completely unrelated to the merits of the case, or to any case characteristic for that matter. Concretely, I show that asylum grant rates in U.S. immigration courts differ by the success of the court city’s NFL team on the night before, and by the city’s weather on the day of, the decision. My data including half a million decisions spanning two decades allows me to exclude confounding factors, such as scheduling and seasonal effects. Most importantly, my design holds the identity of the judge constant. On average, U.S. immigration judges grant an additional 1.5% of asylum petitions on the day after their city’s NFL team won, relative to days after the team lost. Bad weather on the day of the decision has approximately the opposite effect. By way of comparison, the average grant rate is 39%. In contrast, I do not find comparable effects in sentencing decisions of U.S. District Courts, and speculate that this may be due to higher quality of the federal judges, more time for deliberation, or the constraining effect of the federal sentencing guidelines.

Yikes. If it’s true, then there are all sorts of external factors which affect the fates of thousands of asylum seekers, some of whom are turned away because the judge is just having a bad day. This wouldn’t be the first paper to find that irrelevant, external factors influence judicial decisions. A recent paper by Ozkan Eren and Naci Mocan find similar effects (this time via college football – go figure) on decisions in juvenile courts. Others have found that judges are less likely to rule in the defendant’s favour when they are hangry.

Maybe judges should take some sort of mood test before they are allowed to review cases. Or maybe, despite what the folks at ProPublica think, it’s time to let the machines do the work for us.

Hat tip to Charles Kenny for the Chen paper.