Table 1.

Study Population and Lotterya

	All Survey Respondents		Prelottery Diagnosis of Depression		No Prelottery Diagnosis of Depression
	Control Mean	Treatment Control Differenceb	Control Mean	Treatment Control Difference	Control Mean	Treatment Control Difference
	(1)	(2)	(3)	(4)	(5)	(6)
Sample Characteristics (%)
Female	56.9	−0.44	66.8	2.49	51.6	−1.74
		(0.87)		(1.58)		(1.08)
Age 19‐34	36.0	−0.90	31.8	−1.95	38.3	−0.38
		(1.03)		(1.64)		(1.27)
Age 35‐49	36.4	0.16	36.4	1.44	36.4	−0.53
		(1.02)		(1.67)		(1.24)
Age 50‐64	27.6	0.73	31.9	0.51	25.3	0.90
		(0.94)		(1.61)		(1.11)
White	68.8	0.42	81.1	0.01	62.2	0.88
		(1.01)		(1.38)		(1.30)
Black	10.5	0.14	8.0	−0.26	11.9	0.32
		(0.61)		(0.92)		(0.78)
Other race	14.8	0.03	12.9	2.18	15.8	−1.13
		(0.80)		(1.23)		(1.03)
Hispanic	17.2	−0.19	10.0	0.11	21.1	−0.53
		(0.84)		(1.01)		(1.12)
Interviewed in English	88.2	0.25	96.6	−0.91	83.7	1.07
		(0.76)		(0.62)		(1.05)
Global test of balance, F‐statistic		0.20		1.49		0.55
p‐value		(0.99)		(0.15)		(0.83)
Effect of Lottery on Medicaid Coverage (%)
Ever on Medicaid during study period	18.5	24.14	22.8	24.10	16.1	24.23
		(0.90)		(1.58)		(1.09)

^aFor each sample, the first column reports the control mean of the variable. The second column reports estimated differences between treatments and controls for the dependent variable (shown in the left‐hand column), specifically the coefficient (with standard error in parentheses) on lottery based on estimating equation (1). The global test of balance rows report the pooled F‐statistics and p‐values from testing treatment‐control balance on all the above variables jointly. All regressions include indicators for the number of household members on the list and adjust standard errors for household clusters. All analysis is weighted using survey weights. Samples consist of all in‐person interview respondents (n = 12,229), those with a prelottery diagnosis of depression (n = 4,166) and without (n = 8,063).

^bResults for all survey respondents were previously reported in Baicker et al (2013).8