Returns to child work play an important role in determining child labour and schooling through changing the opportunity costs of schooling
Poor families balance future returns to schooling against children’s current economic contributions. This means they respond to changes in returns to work. In particular, changes in returns to work affect household income, and therefore the affordability of schooling (‘income effect’). At the same time, such changes also affect the returns to child labour, hence the opportunity costs of schooling (‘price effect’). Understanding these effects and the underlying structure of household preferences helps to shed light on households’ decisions regarding human capital investments. Moreover, such understanding is crucial for thinking about the consequences of development programmes that affect both the costs and returns to schooling (e.g. PROGRESA in Mexico, NREGA in India, etc.). And while the underlying economic channels are theoretically well understood, separately identifying them empirically has remained a challenge.
The 1991 Indian tariff reform
In our paper (Bai and Wang 2020), we propose an empirical strategy that sheds light on the underlying income and price effects. Specifically, we take advantage of the 1991 Indian tariff reform as a natural experiment. India experienced substantial tariff declines in almost all sectors of the economy during the 1991 trade liberalisation reform. The average tariff declined from 86% in 1991 to 33% in 1997 across a total of 307 agricultural products. As documented in an earlier work by Edmonds et al. (2010), the steep tariff reductions were largely stipulated by external forces and came as a shock during the time, providing an excellent natural experiment setting.
We focus on the agricultural sector, which is the single largest child labour-intensive sector (ILO 2010). The degree of the tariff decline varied significantly across different crops (see Figure 1). We identify crops that are the most and least child labour-intensive, based on detailed labour input information in the IRIS-REDS Indian rural household survey. By exploiting differences in pre-reform crop compositions across Indian districts and tariff declines across crops over time, we compute district tariff measures for distinct crop categories. Using these disaggregate tariff measures, we are able to examine the differential impacts of tariff reductions for adult labour-intensive and child labour-intensive crops on schooling and child labour.
Figure1 Tariff rates by product
Impact on schooling and child labour
We find a net positive relationship between the overall district average agricultural tariff and school enrolment. However, this net result masks important heterogeneity. In particular, we find that while tariff declines for adult labour-intensive crops decrease schooling by one percentage point on average, tariff declines for child labour-intensive crops increase schooling by 0.5 percentage points (relative to the national baseline). The latter indicates a strong countervailing price effect. The results for various child work activities mirror the results for schooling.
Different effects for boys and girls
We document heterogeneous impacts for boys and girls. In particular, tariff declines of child labour-intensive crops exhibit a strong price effect for boys, but not for girls. This suggests that poor families, facing income shocks, do try to balance future returns to higher education against current opportunity costs of schooling. However, they do so mostly for boys. For girls, family income seems to dominate other considerations. One explanation, consistent with Shah and Steinberg (2017), is that in the Indian setting boys primarily substitute into market work and are therefore more responsive to changes in returns to child labour. By contrast, girls mostly substitute into unpaid domestic work and hence are mainly affected by shocks to adult wages and family income.
Schooling elasticities with respect to child labour and adult labour
Finally, we estimate schooling elasticities with respect to returns to adult labour and child labour. Our estimates suggest that a 10% reduction in the returns to adult labour decreases schooling by 2.3%. This number captures the net effect of the income channel, as well as the cross-price effect due to the substitution between adult labour and child labour in home production. On the other hand, a 10% reduction in the returns to child labour increases schooling by 8.6%, reflecting the net effect of income and own-price channels due to the substitution between schooling and various child work activities.
Our findings speak to several policy implications. Raising primary school enrolment is a major development imperative. In order to design effective policies to promote educational attainment, it is necessary to understand the circumstances that lead parents to send their children to work and quit school. Though family income remains the key determinant of child labour and schooling, returns to child work also play an important role through changing the opportunity costs of schooling. If the countervailing price effect is large, children may be pulled out of school during positive economic shocks, especially for sectors in which child labour is an imperfect substitute to adult labour. The results therefore suggest that in designing schooling and various redistribution policies, policymakers should differentiate between economic shocks and their effects on specific sectors.
Bai, J and Y Wang (2020), “Returns to work, child labour and schooling: The income vs. price effects”, Journal of Development Economics, 145.
Edmonds, E, N Pavcnik and P Topalova (2010), "Trade adjustment and human capital investments: Evidence from Indian tariff reform", American Economic Journal: Applied Economics 2(4): 42-75.
ILO (2010), “Accelerating action against child labour; global report under the follow-up to the ILO Declaration on Fundamental Principles and Rights at Work", International Labour Organisation.
Shah, M and B Millett Steinberg (2017), "Drought of opportunities: Contemporaneous and long-term impacts of rainfall shocks on human capital", Journal of Political Economy 125(2): 527-561.