Table 3:

EA Score and Selection

	[1]	[2]	[3]	[4]	[5]	[6]
Individual EA Score and Individual Variables	Q1	Q2	Q3	Q4	Q4–Q1	Q4–Q1 p-value
Panel A: Retired Households, Ages 65–75 (Main Sample)
Male	0.38	0.41	0.41	0.43	0.045	0.057
Birth Year	1935.19	1934.65	1934.28	1934.00	−1.19	< 0.01
Age	69.96	70.05	70.09	70.29	0.33	< 0.01
Panel B: Retired Households, Ages 55–85
Male	0.38	0.39	0.41	0.42	0.04	0.049
Birth Year	1934.89	1934.65	1933.30	1932.90	−1.98	< 0.01
Age	70.89	71.13	71.85	72.31	1.42	< 0.01
Panel C: All Households, Ages 50–75
Male	0.42	0.43	0.42	0.44	.026	0.13
Birth Year	1939.98	1939.64	1939.17	1939.31	−0.68	0.02
Age	63.64	63.40	63.62	63.43	−0.22	0.05
Panel D: All Households, Ages ≤ 85
Male	0.40	0.41	0.41	0.43	0.02	0.12
Birth Year	1938.56	1938.22	1937.28	1937.39	−1.17	< 0.01
Age	65.65	65.83	66.35	66.36	0.72	< 0.01

Notes: This table assesses the relationship between the EA score and gender, birth year and age in alternate samples. Columns [1]-[4] separate individuals into quartiles of the individual EA score distribution and report average values of demographic variables for each quartile. Column [5] reports the difference in average values of each variable between the fourth and first EA quartiles, while Column [6] reports the p-values associated with these differences. In Panel A, we consider our baseline sample of retired households with members aged 65–75. In Panel B, we report statistics for a larger sample that includes retired households with members aged 55–85. In Panel C, we consider a sample that includes all households (retired and non-retired households) with members aged 50–75. Panel D includes all households with members aged no more than 85.