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Causal links from fertility to poverty: what do we know and how can we find out more?. Robert Eastwood Department of Economics Sussex University. November 2006. FERTILITY DECLINE AND POVERTY DECLINE: EVIDENCE FROM CROSS-COUNTRY REGRESSIONS AND OTHER MACRO ANALYSIS
Causal links from fertility to poverty: what do we know and how can we find out more?
Department of Economics
FERTILITY DECLINE AND POVERTY DECLINE: EVIDENCE FROM CROSS-COUNTRY REGRESSIONS AND OTHER MACRO ANALYSIS
Growth effects/ distribution effects
Growth effects: Kelley-Schmidt 1995 find for the 1980s that the fertility fall in the median developing country (about 4 per 1000 in the net birth rate) raised growth rates of GDP/person by about 1.4% p.a.
Distribution effects: Eastwood-Lipton 1999 find lagged poverty-reducing effects even when controlling for mean household consumption. At a ten-year horizon gains from growth and distribution contribute equal amounts to poverty reduction. The median fertility fall, as above, is estimated to lower dollar-a-day poverty incidence from 18.9% to 12.6% at the mean.
Transitional effects versus steady-state effects: consider growth and distribution separately.
Transitional effects already discussed by DC. Key issue for Africa is whether extra supplies of labour (female participation rate) and savings will be productively used, as in East Asia.
Are there benefits of fertility decline in steady state, or are all the benefits transitional? In (demographic) steady state we need to consider age structure, and the level and rate of growth of population
Permanent age structure effect: higher life expectancy analogous to a once-for-all technological advance (return to human capital, lower costs of child mortality).
In Kelley-Schmidt, the answer from cross-country econometrics was no for the 1960s and 1970s, because some cases of low population growth were due to low fertility (good) and others due to high mortality (bad).
Theory suggests very long-lasting, but not eternal, growth gains from slower population growth via more capital-deepening or less capital-shallowing (Solow model).
Can we say, in practice, which countries are experiencing capital shallowing, and how important is the population growth effect?
For Africa, recent World Bank estimates, which take account of exhaustible resource depletion and pollution, give the answers: ‘most’ and ‘substantial’.
Gross national saving is adjusted up for education spending and down for depreciation, natural resource depletion (energy, metals, minerals, net deforestation) and pollution damage (particulates and CO2 emissions) to give adjusted net saving.
A measure of tangible capital, including land, is then used to arrive at a population-growth-adjusted estimate of national savings gaps. Out of 32 African countries all but 5 have positive population growth adjusted ‘savings gaps’ and for 14 countries the gap exceeds 20% of GNI/cap.
These estimates ignore soil degradation (might add 5% of GNI/cap) and, for Africa, CO2 emissions. The population growth effects are large – for many African countries adjusted net saving is positive but wealth per capita is nevertheless falling.
Dependency effect: disproportionate fall, in poor households, in household members per person of working age.
Acquisition effect: disproportionate rise, in poor households, in acquisition of consumables per person of working age.
Which is more important? Do distributional gains arise (a) arithmetically, because fertility falls are concentrated in poor households (dependency effect) or (b) via rises in real wages and/or employment, disproportionately benefitting poor households that rely most on income from labour (acquisition effect).
NB Labour supply effects are complex: a positive acquisition effect could arise initially via employment (raised female participation), and later via real wages (fewer entrants to the workforce).
It can be both, whether via dependency or acquisition.
To illustrate the acquisition effect in steady state, consider the example of Niger - WB estimated population-adjusted saving gap=50% of GNI/capita, seven-eighths of which is attributable to its population growth rate of 3.3% p.a.
Lower population growth in this case would, independently of the demographic transition, reduce capital-shallowing, raise real wages and employment and reduce poverty.
FERTILITY DECLINE AND POVERTY DECLINE: EVIDENCE FROM HOUSEHOLD STUDIES
Can we link micro to macro in principle?
Only partly. A cross-section micro study cannot pick up macro effects of reduced fertility, such as those operating through the real wage (either via eventually lower labour supply - or increased labour demand consequent on higher savings and investment).
Fertility demand versus supply
For both scientific and policy purposes it is critical to know to what extent variations in fertility reflect demand and supply factors. This remains very controversial.
On the view that most variation in fertility is variation in desired fertility (Pritchett 1994), the scientific consequence is that it becomes very difficult to identify effects of exogenous changes in fertility on household well-being (e.g. poverty, schooling, participation, child health), because of a lack of instruments.
Datta Dupta and Dubey, JDS 2006. Attempt to identify a link from higher fertility to higher household poverty risk for India by exploiting son-preference. Use ‘starting with two girls’ as an instrument for finishing with more than two children. Find a positive but insignificant effect.
Illustrates the difficulty of identifying the effects of interest using a cross-section of households. (1) Macro effects cannot be picked up, (2) Unless instruments are very strongly correlated with the variable instrumented (first stage F-stat > 10) little confidence can be placed on the results (Bound, Jaeger and Baker 1995).
The policy consequence of the Pritchett view is that attention is focussed on market failures and externalities in making the case for policy interventions.
Conversely, if significant fertility variation can be attributable to supply-side factors, e.g. family planning effort (FPE), then at the scientific level it becomes easier to identify the consequences of (exogenous) fertility variation and of FPE itself, and at the policy level, attention will be directed to FPE.
Miller 2005 (DC’s presentation). Excellent example of both of the above points for urban Colombia. Scientific: possible to identify fertility-to-education effects for women, using exogenous variation in FPE. Policy: possible to do a rough cost-benefit calculation of FPE against alternative interventions.
Are there any examples in Sub Saharan Africa where we have had reasonably exogenous variation in FPE across a country or region? If so, is there data?
Explanations for high fertility and fertility-reducing policies
Many plausible candidates to explain continued high levels of desired fertility in parts of SSA (e.g. household structures that allow externalization of child costs, opportunities for female employment, absence of public provision for the elderly) but testing and quantification seem very difficult. Too few exogenous instruments with sufficient cross-household variation.
More promising, perhaps, to try to identify effects of FPE, but are there Matlab or Colombia-like examples for Africa with exogenous variation in FPE effort?
At present we know too little about the relative returns to demand-side and supply-side fertility-reducing policies in SSA.
Optimistic view, by analogy with East Asia, would be that extra savings and female labour supply, initially, would combine to raise output and reduce poverty. This requires rises in labour demand together with effective financial intermediation mechanisms.
Questions about the agricultural/non-agricultural balance cannot be avoided. To the extent that the potential for extra employment is predominantly in agriculture, and extra savings generated in rural areas, potential returns to agricultural research and land reform are raised: the introduction of new varieties and land equalization both have the potential to raise agricultural employment.
Research on India (Ravallion/Chen) has demonstrated the importance there of agricultural growth for poverty reduction.