 Should we use IV to estimate dynamic linear probability models with fixed effects?
 Andrew Adrian Pua

 2483 20190709 () Views:24151
 I give a set of pros and cons of this procedure and conclude that this procedure should be treated with caution, especially in fixedT settings. Even if we ignore the possibility that average marginal effects may not be pointidentified, directly applying IV/GMM estimators to this dynamic LPM identifies incorrectlyweighted average marginal effects, which may differ from the true average marginal effect, under largen, fixedT or largen, largeT asymptotics. I also show that there exist certain DGPs that can push the largen, fixedT limits of these IV estimators outside the identified set for the true average marginal effect. The only good news is that nonparametrically testing the point null of zero firstorder state dependence is possible with default routines. Unfortunately, this nonparametric test can have low power. In relation to this, I demonstrate through an empirical example that the resulting IV/GMM estimates of the average treatment effect of fertility on female labor force participation are outside the nonparametric bounds under monotonicity.
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