Free delivery care and supply-side incentives in Nepal’s poorest districts: the effect on prenatal care and neonatal tetanus vaccinations

ABSTRACT

In July 2005, Nepal introduced the ‘Safe Delivery Incentive Programme’, which included free delivery care and supply-side incentives for women in the poorest districts. Using a difference-in-differences model and microdata from the Demographic and Health Surveys, we find the policy increased the probability of prenatal care and neonatal tetanus vaccinations, offsetting disparities between women in the poorest districts and rest of Nepal. Moreover, it was associated with a change in the source of prenatal care, from ‘other’ providers to nurses/midwives. Finally, we find that health investment decisions are interconnected across pregnancy stages; free delivery and supply-side incentives affected prenatal care.

KEYWORDS:

• User fee exemptions
• supply-side incentives
• prenatal care
• neonatal tetanus
• Nepal

Acknowledgments

This work was supported by the USDA National Institute of Food and Agriculture under Hatch project 1016011. We use data from the Demographic and Health Surveys. In 2018, an earlier version of this paper was presented to the School of Economics at the University of Maine, University of Maine Student Symposium and Maine Economic Conference. We are grateful to participants, as well as Ewa Kleczyk and Mario Teisl for helpful comments.

Disclosure statement

No potential conflict of interest was reported by the authors.

Data

The data used in this paper are available from the Nepal Demographic and Health Surveys – 2006 (https://dhsprogram.com/what-we-do/survey/survey-display-268.cfm) and 2011 (https://dhsprogram.com/what-we-do/survey/survey-display-356.cfm).

Free delivery care and supply-side incentives in Nepal’s poorest districts: The effect on prenatal care and neonatal tetanus vaccinations

Supplementary material

Supplemental data for this article can be accessed here

Notes

1. Sustainable Development Goals were preceded by Millennium Development Goals, which also emphasised child and maternal well-being – ‘reduce child mortality’ and ‘improve maternal health’ (United Nations 2015). Our study coincides with the Millennium Development Goals. However, we refer to the Sustainable Development Goals throughout the paper because our analysis not only examines a past policy, but also informs current and future policy-making in support of these goals.

2. For comparison, in North America, the neonatal mortality ratio was four and the maternal mortality ratio was 17 (World Bank 2019).

3. Women have more flexibility in the price paid for home delivery (Borghi et al. 2006b).

4. It is possible that health clinics were not equipped to address the increased demand that ensued from the transfer (Gaarder, Glassman, and Todd 2010).

5. For example, a meta-analysis by Lassi et al. (2013) suggests that ‘mid-level health workers’ (e.g. nurses, midwives, auxiliary health workers) and physicians differ in the nature of and satisfaction with care. Moreover, while child and maternal outcomes are comparable, ‘the quality of care can be poor when mid-level health workers are not properly supervised or are inadequately trained’ (page 828).

6. Results are robust to including unmarried women in the sample.

7. The World Health Organisation now recommends eight prenatal care visits (World Health Organization 2016).

8. The DHS contains a wealth index based on ownership of assets, such as televisions, bicycles, construction materials, water access and sanitation. It has been validated in Nepal (Borghi et al. 2006a). We define ‘poor’ as the bottom two quintiles and ‘rich’ as the top two quintiles. ‘Middle’ is the middle quintile. Alternatively, ‘middle’ can be defined as the middle 40 percent, with ‘rich’ as the top quintile (Bhatt et al. 2018).

9. The non-agricultural sector includes professional, clerical, sales, service and manual labour.

10. Results are robust to using logit regressions.

11. Another threat to identification is that women could have opted into the treatment group by moving to one of the poorest 25 districts, however this is unlikely. Devereux et al. (2017) find little evidence that geographic targeting of social transfers (like free delivery) induces migration from ineligible to eligible areas. In Nepal, migration tends to flow from the hill to terai/lowland ecological zones, related to education and employment (Sharma et al. 2014), while the treatment districts are largely located in the mountain and hill zones (Lamichhane, Sharma, and Mahal 2017).

12. Bhatt et al. (2018) find that women were six times more to likely to participate in four or more prenatal care visits after the expansion.

Additional information

Funding

This work was supported by the USDA National Institute of Food and Agriculture under Hatch project 1016011.

Notes on contributors

Sujita Pandey

Sujita Pandey is from Kathmandu, Nepal. She holds a Bachelor of Arts in Economics and Master of Science in Economics, both from the University of Maine. She is now a PhD student in Economics at Dalhousie University. Sujita’s research interests include child and maternal health.

Angela Daley

Angela Daley is an Assistant Professor of Economics at the University of Maine. She has a PhD in Economics from Dalhousie University. Angela works in the areas of health and labour economics, poverty and inequality, social policy.