Wednesday, July 4, 2012

Does correcting for self selection change the policy question

Consider an experiment of whether job training after layoff increases the probability of being re-employed. A ‘naive’ treatment effect would be to compare the effects of those who enrolled in job training and those who didn’t. The estimated effect would then be the difference in likelihood of being employed for those with job training and those without. The policy question addressed here is whether job training increases the likelihood of employment.

But the econometrician would argue that those who did not enrol in job training are different from those who did and that these characteristics are unobservable to him (the econometrician, e.g. motivation might be unobservable). In order to accurately estimate the impact of job training one would have to compare apples to apples, i.e. those who applied for job training but were (randomly) rationed out of the program. This gives the correct estimated impact. But the policy question now seems to be whether those who applied for job training but were not denied increases the likelihood of being employed. I would argue that this is NOT the policy question of interest.

The policy instrument is to shift people into job training - assuming that the impact is or can be positive. But by estimating the impact only for “motivated” people this naturally assumes that the unmotivated will not be treated. Suppose the following:

  • A randomized control trial of a job training program is run and impacts estimated.
  • The impacts are found to be large and cost benefit analysis shows that the benefits are positive on net.
  • What happens when the program is scaled up, i.e. rolled out to the entire population of unemployed (instead of just to the treatment and control who were "similar" in the trial)? Should we assume that the impacts would still be the same as in the RCT? Are the participants on the now scaled up program still similar? An RCT advocate would argue yes - but - isn't the original intent of scaling up a program to get as many people as possible to participate regardless of the original composition of the treatment and control groups?
  • Should the scaled up program be the same as the RCT, i.e. a static program that doesn't enroll anyone but just allows the "motivated" to enroll themselves? What if there was an effort to try to get the recalcitrant unemployed into the program - after all since the benefits are positive, don't we want to extend the benefits to as many as possible? If there were such an effort would the estimated impacts still be the same as in the trial?
  • Suppose that after the completion of the trial we find that the population of unemployed has changed so that there are now more women than men? Do we deny one gender the treatment because it is no longer the same as those in the randomized trial?

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