Abstract
This paper analyses the contribution that girls make to the rural economy in India through their involvement in the labour market as well as in household chores. We model this in the context of the very different institutional and familial arrangements for girl children prevalent in different parts of India. Analysing the determinants of these activities within a multivariate probit model, we find that the best possible outcome for girls is in districts with high female literacy because here the probability of schooling increases and the probability of work decreases. Less satisfactory but still acceptable outcomes arise in districts where the female labour participation is high. Our results also show that the presence of very young siblings in the household worsens the probability of girls going to school or even working. The presence of older female siblings improves the chances of schooling while that of older male siblings increases the probability of girls doing household chores.
Acknowledgements
The authors are grateful for a research grant from the Department for International Development that enabled them to do this research. We are also grateful to Marina Della Guista and participants of the International Association for Feminist Economics conference held at Oxford, 2004 for comments on earlier drafts of this paper.
Notes
1. A common saying in India.
2. It is important to recognise that chores often take girls outside the home, for example, to the river or water pipe for water. However, these activities are performed in a very feminine context (with few males being around) and are, therefore, considered generally more acceptable for girls. In very traditional households, chores like the daily shopping for groceries are considered male preserves, which females only undertake if they are escorted.
3. Worked in household enterprises (paid and unpaid), salaried regular/wage employee, casual wage labourer in public and other works.
4. Note that no other caste distinctions can be addressed because the NSS data does not provide a finer caste breakdown.
5. There are very few parents with tertiary education, especially amongst mothers in this sample (only 3% of the mothers and 7% of the fathers in the entire sample have tertiary education).
6. The model does not control for household income and, therefore, this result may reflect the fact that SC-ST households are lower income households. We have tested this by running the model after controlling for household income and found that the results for SC-ST remain unchanged. However, we do not include it as our main results because income is likely to be endogenous in the model and this may affect our coefficients.
7. In the case of all four options, the turning point of this variable is very small.
8. To consider whether some of the sibling effect is lost by grouping all children together into the same regression, we re-estimated the model after separating out the sample into the 5–9 year olds and the 10–15 years olds (see Appendix, and for the results). Our results indicate that for both samples (0–9 years and 10–15 years), having younger male siblings does decrease schooling but has a marginal impact on the probability of work. It also increases the probability of doing nothing. However, there is no systematic impact that female siblings of different ages have on schooling and work probabilities in these two separate sub-samples. Both sets of results, like our combined sample results, however, clearly indicate that older female siblings increase the probability of schooling and decrease the probability of doing chores or doing nothing. The impact of older male siblings varies across the two samples however.
9. It might, of course, reflect some misreporting of household chores. However, this is very hard to allow for in the current context. There is, however, considerable evidence (Bacolod and Ranjan, Citation2006; Biggeri et al., Citation2003) that a substantial number of children across the world do not go to school or work or do household chores.