I doubt The Case Against Education will spend more than two pages on the effect of education on crime.  But I’ve already spent a month getting ready to write those two pages.  Why so long?  Because (a) so much has been written on the topic, yet (b) researchers rarely report the precise numbers I want, so I’m also supplementing some of their statistical work to get a better handle on what’s going on.

What am I looking for?  Estimates of the effect of education on crime that take both ability bias and signaling seriously.  So first, I want to see regressions of criminality on education and a wide variety of control variables – cognitive, attitudinal, behavioral, and social.  Second, I want to see “sheepskin” regressions that estimate criminality as a function of both discrete credentials and continuous educational attainment measures.

Let me share some of the main ability bias results I’ve been extracting from the NLSY.  Whenever this famous, long-running data set re-interviews respondents – typically every one or two years – it notes their current place of residence.  One of those residential options is “Jail.”  If you regress the total number of times the respondent was interviewed in jail on his years of education, you get:


Naively interpreted, every extra year of education leads you to spend .07 fewer interviews in jail.  Adding in demographics, plus a measure of observations with missing residential information, makes little difference:


What about controlling for measured intelligence in the form of the AFQT?


So far, the effect of education on criminality looks pretty robust – two-thirds of the initial effect remains.  But what if we add a bunch of “non-cognitive” controls?  In particular, what if we adjust for scores on the Pearlin Mastery Scale, as well as suspensions from school, drinking, marijuana use, sex, and running away from home? 

Aside: For many of these variables, the NLSY measures not just what you did, but how early and/or how often you did it.  SUSPENDED is 1 if you were ever suspended; SUSPENDNUM is the number of times you were suspended.  SEXAGE is the age you first had sex; VIRGIN is whether you had ever had sex at the time of the survey.  You get the idea.


Behold.  With a little statistical elbow grease, the estimated effect of education on incarceration falls by over 2/3rds.  Critics of The Bell Curve will eagerly point out that, adjusting for everything else, measured intelligence (AFQTREV) is only a marginal issue.  But this doesn’t mean that education is all-important, or that ability bias can be safely ignored.  Instead, there are a bunch of high-risk teen behaviors that simultaneously lead to educational failure and the slammer – most notably suspension, running away from home, and having sex.  If you’re the kind of kid who defies adult expectations, whether you actually stay in school is much less important than it looks.

Coming soon: Crime and the sheepskin effect in the NLSY