Table 2

Regression results

ExposureOutcomeEffect estimate (SE)
Schooling (n=5316; 4.4 years of education pre-reform)
Model 1: first stageReform indicatorYears of schooling0.65*** (0.20)
Malaria (n=5316; 34.9% malaria positive pre-reform)
Model 2: intention-to-treatReform indicatorMalaria positive−4.8** (2.4)
Model 3: 2SLS (IV)Years of schoolingMalaria positive−7.5* (3.9)
Anaemia (n=5316; 41.2% moderate or serious anaemia prereform)
Model 2: intention-to-treatReform indicatorAnaemia−5.4** (2.5)
Model 3: 2SLS (IV)Years of schoolingAnaemia−8.2* (4.3)
Vector control (n=5316; 77.5% owns net pre-reform; n=4558; 47.9% all children aged <5 years slept under net pre-reform)
Model 3: 2SLS (IV)Years of schoolingOwn mosquito net−0.5 (2.9)
Model 4: 2SLS (IV)Years of schoolingAll children aged <5 years slept under a bednet last night10.1** (4.8)
  • For malaria, anaemia and vector control outcome, regression coefficient and SEs were multiplied by 100 and reported on a percentage point scale. Per cent malaria positive refer to the prevalence among children of mothers in the 1980 cohort. Model 1 was estimated by OLS method; model 2 by OLS linear probability method; model 3 by IV-2SLS method, in which binary indicator for being born 1982 or later was used as an excluded IV for maternal years of schooling and model 4 by IV-2SLS with sample owns mosquito net. All model controls for full set of children’s age-in-months indicators, a linear term of maternal year of birth, indicator for survey year, indicator for survey month, indicator for child sex, indicator for ethnic groups and age of the mother. No weights were used. Kleibergen-Paap Wald rk F statistic in the first stage models were 10.4.

  • *p<0.10, **p<0.05,***p<0.01.

  • IV, instrumental variable; OLS, ordinary least square; 2SLS, two-stage least square.