Desired fertility and the impact of population policies

Ninety percent of the differences across countries in total fertility rates are accounted for solely by differences in women's reported desired fertility. Using desired fertility constructed from both retrospective and prospective questions, together with instrumental variables estimation, it is shown this strong result is not affected by either ex-post rationalization of births nor the dependence of desired fertility on contraceptive access or cost. Moreover, despite the obvious role of contraception as a proximate determinant of fertility, the additional effect of contraceptive availability or family planning on fertility is quantitatively small and explains very little cross country variation. These empirical results are consistent with theories in which fertility is determined by parent's choices about children within the social, educational, economic, and cultural environment that parents, and especially women, face. They contradict theories that assert a large causal role for expansion of contraception in the reduction of fertility.Reproductive Health,Gender and Social Development,Life Sciences&Biotechnology,Biodiversity,Poverty Reduction Strategies

Wealthier is healthier

With cross-country, time series data on health (infant and child mortality, and life expectancy) and per capita income, the authors estimate the effect of income on health. They use instrumental variables estimation to identify the effect of income on health that is structural and causal, isolated from reverse causation (healthier workers are more productive and hence wealthier) or incidental association (some other factor may cause both better health and greater wealth). The long-run income elasticity of infant and child mortality in developing countries lies between 0.2 and 0.4. Using those estimates, they calculate that in 1990 alone, more than half a million child deaths in the developing world could be attributed to poor economic performance in the 1980s.Health Economics&Finance,Inequality,Economic Theory&Research,Governance Indicators,Health Monitoring&Evaluation

More for the poor is less for the poor : the politics of targeting

Standard economic analyses suggests that when the budget for redistribution is fixed, transfers should be targeted to (that is, means-tested for) those most in need. But both economists and political scientists have long recognized the possibility that targeting could undermine political support for redistribution, and hence reduce the available budget. The authors formalize this recognition, developing a simple economy in which both nontargeted (universally received) and targeted transfers are available. The policymaker chooses the share of the budget to be spent on each type of transfer while the budget is determined through majority voting. Their results are striking. If the policymaker ignores political feasibility and assumes that the budget is fixed, she will choose full targeting of transfers -in the process minimizing social welfare and the utility of the poor. By contrast, when the policymaker recognizes budgetary endogeneity, she will choose zero targeting, spending theentire budget on the universally received transfer. Social welfare, the budget for redistribution, and the utility of poor agents are all maximized in the resulting equilibrium.Environmental Economics&Policies,Services&Transfers to Poor,Health Economics&Finance,Economic Theory&Research,Poverty Impact Evaluation,Services&Transfers to Poor,Rural Poverty Reduction,Economic Theory&Research,Environmental Economics&Policies,Safety Nets and Transfers

Does more for the poor mean less for the poor? The politics of tagging

Proposals aimed at improving the welfare of the poor often include indicator targeting, in which non-income characteristics (such as race, gender, or land ownership) that are correlated with income are used to target limited funds to groups likely to include a cincentration of the poor. Previous work shows that efficient use of a fixed budget for poverty reduction requires such targeting, either because agents'income cannot be observed or to reduce distortionary incentives arising from redistributive interventions. Inspite of this, the authors question the political viability of targeting. After constructing a model that is basically an extension of Akerlof's 1978 model of"tagging", they derive three main results: 1) Akerlof's result continues to hold: that, ignoring political considerations, not only will targeting be desirable but recipients of the targeted transfer will receive a greater total transfer than they would if targeting were not possible. 2) A classical social-choice analysis-in which agents vote simultaneously about the level of taxation and the degree of targeting-shows that positive levels of targeted transfers will not exist in equilibrium (an unsurprising finding, given Plott's 1968 theorem). It also shows that a voting equilibrium often will exist with no targeting but with non-zero taxation and redistribution. 3) In a game in which the policymaker chooses the degree of targeting while voters choose the level of taxation, the redistributive efficiency gains from tagging may well fail to outweigh the resulting reduction in funds available for redistribution. These results may be extended readily to account for altruistic agents. The authors stress that even when these results hold, the alternative to targeted transfers - a universally received lump-sum grant financed through a proportional tax - will nonetheless be supported politically and will be quite progressive relative to the pretransfer income distribution.Economic Theory&Research,Services&Transfers to Poor,Poverty Impact Evaluation,Environmental Economics&Policies,Poverty Monitoring&Analysis,Services&Transfers to Poor,Rural Poverty Reduction,Environmental Economics&Policies,Poverty Impact Evaluation,Safety Nets and Transfers

Good Policy or Good Luck? Country Growth Performance and Temporary Shocks

Much of the new growth literature stresses country characteristics, such as education levels or political stability, as the dominant determinant of growth. However, growth rates are highly unstable over time, with a correlation across decades of .1 to .3, while country characteristics are stable, with cross-decade correlations of .6 to .9. Shocks, especially those to terms of trade, play a large role in explaining variance in growth. These findings suggest either that shocks are important relative to country characteristics in determining long-run growth, or that worldwide technological change determines long-run growth while country characteristics determine relative income levels.