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Table 6 Quantile treatment and average effect estimation of the cash transfer on mental health using US-weights and Malawi-weights

From: Validation of the SF12 mental and physical health measure for the population from a low-income country in sub-Saharan Africa

 (1)
1st Quantile
(0.1)
(2)
2nd Quantile
(0.25)
(3)
3rd Quantile
(0.50)
(4)
4th Quantile
(0.75)
(5)
5th Quantile
(0.9)
(6)
Average Effect
Model (1) Estimation of quantile treatment and average effects on mental health using the Malawi-weighted SF12 mental health measure
Treated4.599***1.9000.4580.1160.0211.124*
(1.690)(1.200)(0.852)(0.512)(0.296)(0.640)
Constant42.259***12.34735.025***43.526***53.298***59.915***
(3.812)(9.984)(7.213)(4.402)(2.657)(2.289)
Model (2) Estimation of quantile treatment and average effects on mental health using the US-weighted SF12 mental health measure
Treated5.305***1.6140.9610.192−0.0551.129
(1.696)(1.353)(1.163)(0.525)(0.082)(0.798)
Constant39.889***42.957***52.086***56.034***59.422***50.014***
(8.008)(6.845)(5.170)(2.705)(0.790)(3.118)
  1. The outcome variable is mental health by quantiles after the intervention for (1)–(5). The outcome variable in (6) is the change in mental health. We control for the following covariates at baseline: mental health measured by the respective SF12, membership of a local AIDS-committee, the frequency over the past months of visits to a place to see a drama, to dance, to drink beer, and to the market, self-perceived local AIDS-prevalence, probability of infant mortality, probability of a drought or equivalent food shock in the next 12 months, the number of people who have died as a result of AIDS known by the respondent, the number of funeral visits in the past month, a binary variable indicating if the individual ever smoked, one if he/she is currently smoking and one measuring the average number of days a week alcoholic drinks are consumed, a binary variable indicating if the individual lives in a house with a metal roof as a proxy for income, subjective wellbeing, a binary variable indicating the HIV-status of the individual, ethnic background (Yao, Tumbuka, Chewa or another ethnicity), educational attainment (none, primary, secondary tertiary), marital status (binary variable), the number of children living in the household, age, gender, and the number of the household members, a set of dummies for the region of origin of the respondent and a binary variable indicating if the respondent received a couple or individual cash transfer. The sample size is 790. Bootstrapped standard errors for quantiles are in parenthesis; clustered standard errors for the ITT are in parenthesis *** p < 0.01, ** p < 0.05, * p < 0.1. We bootstrapped the estimates on 500 repetitions