Table 19.

Regression analysis results of missing data

Missing = 1	alc_missing	INCOME_missing	UNEMP_missing
INCOME2	−0.005**		0.007***
	(0.002)		(0.002)
INCOME3	−0.003		−0.007***
	(0.002)		(0.002)
INCOME4	−0.011***		−0.016***
	(0.002)		(0.002)
INCOME5	−0.017***		−0.017***
	(0.003)		(0.002)
INCOME6	−0.016***		−0.019***
	(0.003)		(0.002)
GYMNASIET	−0.008***	−0.019***	0.009***
	(0.002)	(0.002)	(0.001)
UNIVERSITET	−0.007***	−0.025***	0.013***
	(0.002)	(0.002)	(0.001)
LNAGE	−0.013***	0.017***	−0.010***
	(0.002)	(0.003)	(0.001)
MALE	0.012***	−0.015***	−0.010***
	(0.001)	(0.001)	(0.001)
INACTIVE	−0.008***	0.033***
	(0.002)	(0.002)
UNEMP	0.007*	0.049***
	(0.004)	(0.005)
STUDENT	−0.003	0.028***
	(0.003)	(0.003)
COHABIT	−0.006***	0.000	0.005***
	(0.001)	(0.001)	(0.001)
Observations	132,239	140,949	134,973
R-squared	0.028	0.012	0.007

Monitor project data years 2004–2011. Month dummies to capture resampling effects and seasonality and regional dummies are included in all models (reference categories: Stockholm and January). Robust standard errors are reported in parentheses. Testing the null of no effect: *** p < 0.01; ** p < 0.05; * p < 0.1