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Labour Market Outcomes in Bangladesh: The Role of Poverty and Gender Norms

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Abstract

It is frequently argued that female participation in the labour market is important for economic growth and poverty reduction. Despite this, the role that extreme poverty and gender norms play in influencing such participation is far from fully understood. This article uses nationally representative household data to address this issue using data for Bangladesh. In line with prior – largely qualitative – work, we find that extreme poverty is indeed important in explaining some of the growth in female employment in Bangladesh; we find evidence of a positive relationship between extreme poverty and participation, especially for women. In addition, we find that among young single women there appears to be a growing acceptance of their employment in the labour market. Despite this, rigid social and cultural norms are still apparent among other groups of women, especially in the rural areas.

On affirme souvent que la participation des femmes au marché du travail joue un rôle important pour la croissance économique et la réduction de la pauvreté. Pourtant, l′influence de la pauvreté extrême et des normes de genre sur cette participation est loin d′être parfaitement comprise. Cet article tente d′apporter des éléments de réponse à cette question en s′appuyant sur des données représentatives sur les ménages du Bangladesh. Tout comme les travaux, essentiellement qualitatifs, effectués précédemment, nous constatons que la pauvreté extrême est un facteur important expliquant une partie de la croissance de l′emploi des femmes au Bangladesh; Nous démontrons que l′extrême pauvreté est positivement corrélée avec cette participation, particulièrement pour les femmes. En outre, nous constatons que les jeunes femmes célibataires semblent de plus en plus nombreuses à accepter leur propre participation au marché du travail. Cependant, des normes sociales et culturelles rigides continuent de régir les autres catégories de femmes, notamment en milieu rural.

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Notes

  1. We acknowledge as a side issue that long-term economic growth evidence indicates that women are a smaller percentage of the labour force at moderate levels of development than at either low or high levels of development – as recognized by prior papers such as Pampel and Tanaka (1986) and Goldin (1994).

  2. Only 42 women participate in the labour force for every 100 men (ILO, 2008).

  3. The latest poverty headcount figures are from Serajuddin et al (2010).

  4. Here, poverty is measured as per capita consumption below the poverty line, and extreme poverty is per capita consumption below the lower poverty line. See, Serajuddin et al (2010) and World Bank (2002) for further details.

  5. The ILO defines the vulnerable employed as someone who is self-employed with no employees (an own-account worker) or an unpaid family worker. The ILO argues that employment of this kind is least likely than other forms of employment to have formal work arrangements, access to benefits or social protection programmes.

  6. In this instance, we make use of data from the nationally representative Household Income and Expenditure Survey for 2000, which is a particularly rich data set for examining some of the issues surrounding labour participation and employment outcomes. The quality of the employment data is particularly good, relatively to other surveys, and the data set also provides a detailed measure of the household's poverty status, which is often not available in other surveys.

  7. A woman is thought to have her highest level of economic independence when she is engaged in wage and salaried work or is an employer; lower independence when she is an own-account worker (self-employed), and the least independence when she is an unpaid family workers (ILO, 2008).

  8. Kantor (2003) and Anderson and Baland (2002) make similar observations for India and Kenya, respectively.

  9. See, for example, Mahmud (1997) for metropolitan Dhaka; Salway et al (2003) for the slum dwellers in Dhaka; Kibria (1998) who interviews 70 garment workers and members of their households; Kabeer and Mahmud (2004a) who conduct a comparison of women working for the garment export sector and women working in the domestic market.

  10. See, for example, Khandker (1987) for rural Bangladesh, Amin (1997) for two rural villages in northern Bangladesh; and Anderson and Eswaran (2009) for married men and women in Matlab, a predominantly rural area 70 km southeast of Dhaka.

  11. Although ‘purdah’ literally means ‘curtain’ or ‘veil’, it is often used figuratively to describe this custom of female seclusion.

  12. Female-headed households are among the poorest in Bangladesh. Salway et al. (2003, p. 889), for example, find that ‘ … many of the poorest households represent a breakdown of the “patriarchal contract” …’ that is, are households without a male head.

  13. A small proportion of garment factories in Bangladesh operate within the county's export-processing zones (EPZs). Kabeer and Mahmud (2004a) argue that, although there is a ban on trade unions within the zones, wages and working conditions are generally better than elsewhere.

  14. Although there are more recent, nationally representative data for Bangladesh, there are issues regarding labour supply data accuracy that reflect the usage of the HIES 2000 data for this analysis, and given the poverty reduction that occurred through the 1990s the key examination of poverty is further justified.

  15. This involved calculating an upper and lower poverty line using food consumption and non-food consumption data from the HIES (2000) – see, World Bank (2002) for further details.

  16. Such a finding is in line with a report by the World Bank (World Bank, 2002), which uses the 2000 HIES data to show how participation rates vary across per capita expenditure deciles. They show that participation is greatest among the poorest and richest deciles, although the women tend to be employed in very different types of activities. They find that the majority of women from the poorest households work for wages in agriculture, manufacturing or on family enterprises, whereas women in the richest decile hold white-collar jobs, usually as teachers or health-care workers.

  17. See Paci and Sasin (2008) for a more detailed overview of the Bangladeshi labour market.

  18. We test this assumption in what follows using a Hausman test and find insufficient evidence to reject the null hypothesis that the errors are independent across alternative employment sectors. It should be noted that our results are also robust to estimating a multinomial probit model, which relaxes the independence of irrelevant alternatives assumption of the multinomial logit model.

  19. It should be noted that for completeness, the marginal effects are reported in the Appendix.

  20. By ‘average’, we mean the probability of participation calculated using the mean characteristics of the sample.

  21. Although these results provide strong evidence for a direct link between poverty and employment, there is, however, a potential bias in these estimates because of the likelihood of unobserved characteristics that explain both poverty and participation. We address this potential endogeneity by estimating the relationship between poverty and participation simultaneously as a recursive bivariate probit, and find that our results are robust to this potential bias (see, for example, Greene, 1997 and Bridges and Disney, 2010). These results are not presented here but are available on request.

  22. Indeed, interacting marital status with age we find that, not surprisingly, it is the young women who are also single that are more likely to participate in the labour market (see Table A2).

  23. The multinomial results are not reported here, but are available from the authors upon request, and support the findings of the logistic regressions.

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Acknowledgements

This research was undertaken with support from the ESRC's Global Poverty Research Group (GPRG) at the Universities of Manchester and Oxford (grant number M571255001). We are grateful to Shanker Chandra Saha for assistance with data extraction. The authors are grateful for helpful comments received from conference participants at EALE, 2009 and seminar participants at the University of Nottingham.

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Correspondence to Sarah Bridges.

Appendix

Appendix

Tables A1, A2 and A3.

Table A1 Labour participation rate (%) by sex: Bangladesh
Table A2 Maximum likelihood estimates of the probability of participation: Interaction effects (Marginal effects)
Table A3 Maximum likelihood estimates of labour market outcomes – Multinomial logit marginal effects

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Bridges, S., Lawson, D. & Begum, S. Labour Market Outcomes in Bangladesh: The Role of Poverty and Gender Norms. Eur J Dev Res 23, 459–487 (2011). https://doi.org/10.1057/ejdr.2011.14

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