. Author manuscript; available in PMC: 2009 Dec 1.

Published in final edited form as: J Econ Psychol. 2008 Dec;29(6):810–831. doi: 10.1016/j.joep.2008.03.006

Table 6.

HRS: older adults – sample attrition

Sample	Sample Attrition

	Balanced Sample			Inverse Probability Weighting ^a

	All	Risk Averse	Risk Tolerant	All	Risk Averse	Risk Tolerant

Dependent Variable	Alcohol Participation	Alcohol Participation	Alcohol Participation	Alcohol Participation	Alcohol Participation	Alcohol Participation

Specification	1	2	3	4	5	6
Real Beer Tax	-0.5871*** (0.1998) [ε = -0.219]	-0.5446** (0.2398) [ε = -0.217]	-0.6751** (0.3621) [ε = -0.224]	-0.3671** (0.1797) [ε = -0.147]	-0.2902* (0.2115) [ε = -0.125]	-0.5451* (0.3331) [ε = -0.185]
Year Indicators	Yes***	Yes***	Yes***	Yes***	Yes***	Yes***
State Indicators	Yes***	Yes***	Yes***	Yes***	Yes***	Yes***
R²/Pseudo R²	0.151	0.153	0.130	0.137	0.134	0.146
Percent Correctly Classified	68.4	68.4	68.6	67.6	67.6	67.7
Observations	40,599	26,544	14,036	55,137	35,740	19378

Notes: See Table 3. Each column represents a separate regression model. All models include the extended set of covariates listed in Table 3.

Inverse probability weights are predicted using baseline characteristics (gender, race, ethnicity, education, parental education, religion, and native-born) along with other time-varying factors (age indicators, wave indicators, census division indicators), lagged covariates (income, marital status, health insurance), and health status and alcohol consumption in the prior wave.