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. Author manuscript; available in PMC: 2020 Oct 23.
Published in final edited form as: J Aging Health. 2018 Jun 28;31(2):293–321. doi: 10.1177/0898264318782096

Table A2.

ATE of Retirement Sequences on Functional Ability.

Complete-early Late-early Partial-early Compact-early Partial-complete

Age 0.02 (0.01)** 0.02 (0.01)** 0.02 (0.01)** 0.02 (0.01)** −0.05 (0.01)***
Age2 −0.01 (0.00)*** −0.01 (0.00)*** −0.00 (0.00)*** −0.01 (0.00)*** 0.00 (0.00)
ATE 0.62 (0.05)*** 0.69 (0.05)*** 0.60 (0.05)*** 0.58 (0.06)*** −0.01 (0.04)
ATE × Age −0.08 (0.02)*** −0.02 (0.02) −0.02 (0.02) −0.04 (0.03) 0.04 (0.02)***
ATE × Age2 0.01 (0.00)*** 0.00 (0.00) 0.00 (0.00)* 0.00 (0.00) −0.00 (0.00)

Observations 26,010 22,854 24,678 20,550 16,020
Individuals 4,335 3,809 4,113 3,425 2,670
Blocks 1,620 1,130 1,410 774 1,100

Compact-complete Ambiguous-complete Late-complete Ambiguous-early Ambiguous-late

Age −0.05 (0.01)*** −0.08 (0.03)** −0.05 (0.01)*** 0.02 (0.01) −0.07 (0.07)
Age2 0.00 (0.00) 0.00 (0.00) −0.00 (0.00) −0.00 (0.00)*** 0.00 (0.01)
ATE −0.03 (0.06) −1.09 (0.18)*** 0.11 (0.05)** −0.36 (0.14)*** −1.01 (0.12)***
ATE × Age 0.03 (0.03) 0.25 (0.12)** 0.01 (0.02) 0.10 (0.09) 0.08 (0.08)
ATE × Age2 −0.00 (0.00) −0.02 (0.01)* 0.00 (0.00) −0.01 (0.01) −0.01 (0.01)

Observations 11,892 13,866 14,196 22,524 10,710
Individuals 1,982 2,311 2,366 3,754 1,785
Blocks 625 606 943 934 416

Ambiguous-partial Ambiguous-compact Partial-late Compact-late Partial-compact

Age −0.02 (0.02) −0.06 (0.03)* −0.01 (0.01) −0.01 (0.01) −0.03 (0.02)
Age2 0.00 (0.00) 0.00 (0.00) −0.00 (0.00)* −0.00 (0.00)* −0.00 (0.00)
ATE −0.90 (0.10)*** −0.88 (0.09)*** −0.08 (0.05)* −0.12 (0.07)* 0.00 (0.06)
ATE × Age 0.07 (0.05) 0.09 (0.04)** −0.00 (0.02) −0.00 (0.03) 0.02 (0.02)
ATE × Age2 −0.01 (0.00)* −0.01 (0.00)** 0.00 (0.00) −0.00 (0.00) 0.00 (0.00)

Observations 12,534 8,406 12,864 8,736 10,560
Individuals 2,089 1,401 2,144 1,456 1,760
Blocks 519 462 871 491 561

Note. As the full matching procedure creates blocks of individuals, where one treated individual is matched with one or more controls (or vice versa), the ATE is estimated using a hierarchical regression model with weights that correct for the number of treated and control individuals in each block. Intercepts and random components are omitted. ATE = average treatment effect.

*

p < .05.

**

p < .01.

***

p < .001.