Table 6.

Specification Checks: “Pre” = 1992-1993, “Post” = 1994-1995

	(1)	(2)	(3)	(4)	(5)	(6)
	Not Working		Self Employed		Part Time
veteran*post	0.0003	−0.0004	0.0023	−0.0024	0.0011	0.0022
	(0.0014)	(0.0012)	(0.0059)	(0.0053)	(0.0064)	(0.0059)
veteran	0.0108**	0.0087**	−0.0353**	−0.0068	0.0033	0.0066**
	(0.0017)	(0.0023)	(0.0041)	(0.0052)	(0.0025)	(0.0023)
married	−0.0261**	−0.0117**	0.0268**	0.0410**	−0.0358**	−0.0172**
	(0.0037)	(0.0042)	(0.0076)	(0.0087)	(0.0075)	(0.0056)
nonwhite	0.0180+	−0.0018	−0.1002**	−0.0677**	−0.0057	−0.0109
	(0.0106)	(0.0100)	(0.0118)	(0.0085)	(0.0086)	(0.0073)
pension		−0.0234**		−0.1723**		−0.0675**
		(0.0066)		(0.0048)		(0.0029)
health insurance		−0.0306**		−0.1603**		−0.0334**
		(0.0099)		(0.0131)		(0.0062)
Observations	16683	16683	16683	15868	13624	13624

Note: Coefficient estimates are taken from a probit regression as described in eq. (1). Marginal effects are reported. Regressions include age, state, year and education dummies and a constant. Health insurance denotes whether or not an individual is included in a health insurance plan in the previous year and pension denotes whether or not the individual has a pension. Robust standard errors in parentheses are clustered on veteran and year. Regression universe is restricted to men who were employed in the previous year. In column 4, industry last year public predicts failure perfectly and 815 observations are dropped.

⁺significant at 10%

^*significant at 5%

^**significant at 1%