This paper reviews the issues surrounding the derivation of estimates of the impact of child labour on school outcomes. The paper aims to review the current state of methodological and empirical knowledge concerning the impact of child labour on learning, to review existing data sets that could be used to address the issues, and to highlight areas where current research is lacking.

The discussion begins with a conceptual model of the interrelationship between child participation in school and in the labour force that highlights the various factors that enter these decisions. The discussion proceeds to a review of methods to estimate the impact of child labour on student learning using educational production functions. The fact that child labour and school attendance are influenced in part by the child’s performance in school complicates the estimation of the impact of child labour on learning.


Armed with this conceptual framework, we turn to alternative measures of the conceptual variables. The pros and cons of various measures of child labour and school performance are presented along with references to how these measures have been used in practice. The need for measures of school and household attributes as well as possible instruments that could be used to control for the endogeneity of child labour are also reviewed.

Next, the paper reviews issues regarding how one might design a sample survey to measure the consequences of child labour for school outcomes. The properties of existing data sets that have been used to analyse these questions are presented. The methodological issues reviewed in the first three sections of the paper are then illustrated using two multinational data sets, one from Latin America and one concentrated primarily on Central and Eastern Europe. Findings from previously published studies of the impact of child labour on schooling outcomes are reviewed. The paper concludes with a summary of questions that have not been adequately settled by existing research and data sets and makes suggestions for future research.