Does Private Tuition Affect Efficiency of Government and Government Aided Schools? An Evidence of Higher Secondary Schools Based in Kolkata

This paper contributes to the literature by estimating yet unexplored role of private tuition in explaining output oriented technical efficiency levels (TEFout) of higher secondary stage (HS), as estimated applying BCC (1984) DEA model, using primary survey data for 25 government and government aided schools in Kolkata, India, collected using stratified random sampling method, after controlling for the other determinants of TEFout, considering private tuition taken by the students as an endogenous variables and also measuring the variation of TEFout not accounted by private tuition. The results show 56% sample schools are inefficient at HS; hence more of output can be produced using the existing resources; TEFout ranges between 0.652 and 1.000. A positive and significant influence of ‘percentage of private tuition taking students’ in determining the TEFout is evident. TEFout variation not explained by private tuition is very less, ranging only from 0.40% and 8.64% with 3.72% as mean, which is a serious concern. The findings also reflect, the positive role of less discussed factors on TEFout at HS namely: (i) Government targeted policy variable, like proportion of the girl student receiving ‘Kanyashree’ (an initiative taken by the Government of West Bengal to improve the life and the status of the girls by helping economically backward families with cash so that the marriage of their girl child before eighteen years is not being arranged, because of socio economic and financial problem), (ii) the amount of government fund received by the schools (excluding salary payments), reflecting a non-linear relationship with TEFout, but with positive marginal effect, implying an increase in government fund will increase TEFout, (iii) role of Headmaster/mistress (HM) in school management, like (a) interaction of HM with teachers & students and (b) interaction frequency with state department of education, while taking any policy decision for the school and (iv) School infrastructure related variables, like number of smart classroom in the school and whether librarian of the school is on duty. Suitable policies are suggested to enhance TEFout at HS of the schools and to reduce the dependence on private tuition.