Abstract
The childhood disease burden depends on the prevalence of infectious diseases, their case fatalities, and long-term morbidity. We propose a quantity–quality model of fertility choice under uncertainty that emphasizes morbidity and mortality from infectious disease. The fertility response to a decline in child mortality depends on the morbidity effect of the disease, the prevalence rate, and whether the prevalence or case fatality rate declines. Fertility follows mortality and morbidity, but since mortality and morbidity do not always move in the same direction, the fertility response may be dampened or nonmonotonic. Disease-specific evidence from sub-Saharan Africa supports these theoretical predictions.
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Notes
In general, i and d would depend on h 0 and on pre- and postnatal health inputs provided by the parent. Here, both are treated as parameters.
While we do not have precise estimates of the overall effect on labor productivity from all types of infectious diseases, we will entertain different values of δ to get an idea how childhood morbidity affects fertility outcomes.
Boldrin and Jones (2002) analyze endogenous donations from children who support parents in old age but do not include parental investment in children.
Under more general constant relative risk aversion (CRRA) preferences, the TFR actually increases in response to lower mortality. In Boucekkine et al. (2009), the inclusion of a labor-leisure trade-off ensures that fertility declines with mortality despite CRRA and certainty about child survival.
This isomorphism hinges on how preferences are modeled. If parents were altruistic in the Barro–Becker sense or derived warm glow from investment in each type of child, they would care about unhealthy children even if δ = 1. Both of these complicate the household’s decision problem without adding insight to the morbidity effect.
These 37 countries are Angola, Benin, Botswana, Burkina Faso, Burundi, Cameroon, Central African Republic, Chad, Congo, Democratic Republic of Congo, Cote d’Ivoire, Equatorial Guinea, Eritrea, Ethiopia, The Gambia, Ghana, Kenya, Liberia, Malawi, Mali, Mauritania, Mauritius, Mozambique, Namibia, Niger, Nigeria, Senegal, Sierra Leone, Somalia, South Africa, Sudan, Swaziland, Tanzania, Togo, Uganda, Zambia, and Zimbabwe. They accounted for 94% of SSA’s 2008 population (World Bank).
An alternative approach would be to consider the incidence and case fatality rates for each disease separately. Sample size restrictions make it harder to implement this. Additional data are necessary to estimate and compare the fertility and morbidity effects from various diseases.
Since all the δs are less than one, the weighted i for each country would be a fraction of the unweighted i. This alone would inflate the coefficient estimates on the weighted-i regressors in column 6 which differ from those in column 5 by a factor of 4.6. But this is, at best, a partial explanation since the coefficient estimate on d changes too as do the net effects reported in Table 3. The ratio of unweighted to weighted i in the dataset is 8 on average and ranges from 6.6 to 9.9.
Led by efforts of the WHO, polio has been eradicated in all but three countries: Afghanistan, Nigeria, and Pakistan.
Lower transmission areas are those at higher altitudes where fewer mosquitoes survive and where sporogony is slower.
The wage effect that contributes to a negative response of fertility to adult mortality in Young (2005) is absent in our model.
The Rockefeller Sanitary Commission began a hookworm eradication campaign in 1910 after discovering that 40 % of school-aged children were infected with the parasite.
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Acknowledgements
We would like to thank Alfredo Burlando, David Canning, Jason Lindo, Tom Murray, William Vasquez, and especially two anonymous referees and the editor of this journal for valuable suggestions. Feedback from seminar participants at various places this paper was presented is gratefully acknowledged as is Fiona Gore’s (WHO) help with the National Burden of Disease database. The usual caveat applies.
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Aksan, AM., Chakraborty, S. Childhood disease and the precautionary demand for children. J Popul Econ 26, 855–885 (2013). https://doi.org/10.1007/s00148-012-0430-z
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DOI: https://doi.org/10.1007/s00148-012-0430-z