*Names in bold indicate Presenter
The UN Millennium Development Goal established as the first two objectives to eradicate extreme poverty and hunger, and to ascertain that all children consummate primary schooling. Improving early child development is a paramount step to reach these goals. What poverty does is to reduce the changes of people of receiving formal education; and at the same time, education is one of the main factors that contribute to reduce poverty. In less developed countries, poverty will increase the changes of suffering from bad health and nutrition conditions. Recent studies have shown, that this situation reduces the abilities of children to achieve decent educational outcomes.
A poor health condition can affect the ability to learn for a variety of reasons, including reducing the years enrolled, lower daily attendance, and less efficient learning per day spent in school. Even though India has made some progress with respect of level of primary attendance, still the quality of the achievement can be compromised because of the high level of malnutrition in children.
The cognitive achievement, can be considered as the end product of an education production function which depends on parental characteristics and the early home environment, hence we could seek to analyze the productivity relationship between different types of inputs and test score for the children.
We can analyze the relationship between child development and achievement, based on: i) OLS regressions; ii) structural models; and iii) natural or controlled experiment. Due to the lack of reliable data on cognitive skills for most developing countries, there is no much research that focus on the connection between production function and achievement. In developing countries there are some studies that rely on the randomized strategy. Thus, an important question is how to analyze the production functions when there exist unobservable inputs and there is also risk of endogeneity. Structural models are not usually found in the development literature, although it is growing in popularity. This methodology can overcome the problem of data limitation and also can be helpful to perform counterfactual policy evaluation that goes beyond what is contained in experimental studies.
The longitudinal dataset collected by the Young Lives Project in the state of Andhra Pradesh which tracks three cohorts of children (born in 1994/95 and 2001/2) through household visits in 2002, 2007 and 2009 present very suitable data in order to estimate the production function of school achievement as a function of the household, school, and individual inputs; in particular, the quality of the child development can be analyzed in order to have a clearer understanding of the effect on the school achievement.
