- A-2 LPM Coefficient Stability While our coefficients are stable as we add covariates, that is not a sufficient condition for omitted variable bias to be negligible. Figures A-1 and A-2 are based on the omitted variable bias bounding approach of Oster (2015). We assume that the unobservables share at least some of the covariance properties of the observables we selected. Without this reasonable assumption, very little can be said about the merits of our identification strategy. The horizontal line in Figure A-1 shows the marginal e↵ect on exit from an additional 24 hours in the lead from specification (6) in Table A-3. The bias of this estimate depends on two unknown in-sample parameters: the R2 from a hypothetical regression of the outcome on all observed and unobserved determinants of exit, R2 MAX, and the coefficient of selection proportionality . A of one indicates that the observed and unobserved
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