Birth Spacing and Neonatal Mortality in India

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Birth Spacing, Fertility and Neonatal Mortality in India:

Dynamics, Frailty and Fecundity

Sonia Bhalotra, University of Bristol

Arthur van Soest, RAND and Tilburg University
This version: September 2007

Using microdata on 30,000 child births in India and dynamic panel data models, we analyze causal effects of birth spacing on subsequent neonatal mortality and of mortality on subsequent birth intervals, controlling for unobserved heterogeneity. Right censoring is accounted for by jointly estimating a fertility equation, identified by using data on sterilization. We find evidence of frailty, fecundity, and causal effects in both directions. Birth intervals explain only a limited share of the correlation between neonatal mortality of successive children in a family. We predict that for every neonatal death, 0.37 additional children are born, of whom 0.30 survive.
Key words: fertility, birth spacing, neonatal mortality, health, dynamic panel data models, siblings, India
JEL codes: I12, J13, C33

Telephone: +44 117 9288418. Address: Sonia Bhalotra, Department of Economics, University of Bristol, 8 Woodland Road, Bristol BS8 1TN, UK.

1 Introduction

Interest in the determinants of child mortality has recently surged, with the inclusion of targets for child mortality amongst the Millennium Development Goals (Lawn et al. 2005, UNDP 2003), and short birth-spacing and high fertility are widely regarded as among the most important causes of early childhood death. However, reproductive behaviour is endogenous to mortality and both are influenced by characteristics and choices of families, some of which are difficult to observe. For these reasons, there is limited evidence of the true causal associations of these variables.

In developing countries, 30% of deaths are of children under five, compared to less than 1% in rich countries (Cutler et al. 2005). Almost half of child deaths are in the neonatal period, the first month of life, when the tie between mortality and fertility is closest (Cleland and Sathar 1984). About 4 million neonates died in 2000, 99% of them in developing countries, and 27% in India. The proportion of neonatal in under-5 deaths has increased, since interventions like immunization, control of acute respiratory infection, or oral rehydration have had more of an effect on post-neonatal death (Lawn et al. 2005). It is thus important to focus attention on the causes of neonatal death.

Despite a long-standing interest of economists and demographers in the relation between childhood mortality and reproductive behaviour, the literature is scarce in a complete micro-data analysis of all inter-relations of these variables (Wolpin 1997). The main contribution of this paper is to use panel data based on retrospective fertility histories to estimate causal effects of birth interval length on subsequent neonatal mortality risk and of neonatal mortality on subsequent birth interval length, controlling for unobserved heterogeneity in both processes (referred to as frailty and fecundity, respectively). It also provides estimates of the effects of expected mortality (hoarding) and realized mortality (replacement) on fertility. Third, we model the mortality dynamics within families, estimating both the extent to which observed persistence in death risk is explained by state dependence, and the contribution of endogenously determined birth-spacing to state dependence effects. Other contributions are methodological, relating to the way in which we deal with right-censoring of birth intervals and with the initial conditions problem that arises in dynamic models with unobserved heterogeneity.

Understanding the way in which biological and behavioural factors shape the family-level relation between reproductive behaviour and childhood mortality is crucial to understanding the demographic transition that has historically preceded economic growth (Kalemli-Ozcan 2002), and the endogenous processes by which societies evolve past the Malthusian spectre (Galor and Weil 2000). Time series analyses of historical data for today’s industrialized countries suggest that declining mortality stimulated fertility decline (e.g. Ben-Porath 1976, Eckstein et al. 1999), and a similar tendency can be seen in recent data for developing countries (e.g. Nyarko et al. 2003). Cross-sectional studies using household survey data have emphasized the reverse direction of causation, namely that high fertility, associated with close birth spacing or an early start to childbearing, causes an increase in childhood mortality (e.g. Cleland and Sathar 1984).

In families with multiple children, there is a recursive bi-causal relation of these variables. The death of a child is often followed by a shorter interval to the next birth, which may be explained either by volitional replacement (e.g. Olsen 1988) or by the fact that the mother stops breastfeeding, enabling her to conceive the next child sooner than otherwise (e.g. Chen et al. 1974). A short birth interval, in turn, increases the mortality risk of the next child in the family, possibly because the mother has not recuperated from the previous birth (e.g. DaVanzo and Pebley 1993). Thus vulnerable families are caught in a death trap, creating persistence in death risk within families. This mechanism operates by the endogenous shortening of intervening birth intervals. Of course a birth interval is only observed if the mother has another birth, and this fertility decision is also influenced by whether her previous birth survived or not. While these relationships have each been studied, their interactions have rarely been studied jointly, and unobserved heterogeneity, another potential source of correlation of death risks within a family, is often ignored.

The analysis in this paper provides estimates, using survey data from India, of a dynamic panel data model that describes the complete process of child survival and birth spacing (and thus fertility), allowing for endowment heterogeneity, input endogeneity, right-censoring and accounting for the initial conditions problem. We find evidence that childhood mortality risk is influenced by the pattern of childbearing, that is, by the timing and spacing of births, and that birth-spacing and fertility are, in turn, a function of realized mortality. We find a replacement effect of 0.37, in line with the few available estimates in the literature. The results suggest that the full impact of family planning interventions extends to reducing mortality and that mortality-reducing interventions like provision of piped water also affect birth spacing and fertility. Our finding of causal effects of sibling mortality on both mortality and reproductive behaviour implies that interventions that reduce mortality or lengthen birth intervals will have multiplier effects.

The paper is organized as follows. Section 2 summarizes related research. Section 3 describes the data. The econometric model is presented in section 4 and estimation and simulation results are reported in section 5. Section 6 summarizes and concludes.

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