Carlos Ivan Simonsen Leal suggests emphasizing trade and investment integration in global development agendas in order to spread the benefits of globalization and generate economic growth.
Challenge
Developing evidence-oriented policies that target both short-term realities and the middle to long-term structural determinants of poverty.
Proposal
In recent years, many countries have put in place “social policies” targeting poverty and inequality in the form of direct cash transfers. There are many theoretical and practical advantages to this design: unlike policies involving the provision of goods (or scrip/food stamps specifically earmarked for approved purposes), direct cash transfers acknowledge the power of individual decision-making and market forces in maximizing the end-user welfare. Moreover, although cash transfers may seem like a short-term solution to structural problems, they can also be used to implement incentive schemes towards long-term improvements, particularly in the case of education. In Brazil, for example, the conditional cash transfer (CCT) portion of Bolsa Escola/Bolsa Família tries to incentivize families to send their children to school rather than having them work to complement the family’s income.
While these programs are generally believed to have been successful, there is relatively scarce information on their effectiveness, optimal design and size. On the one hand, because cash transfers are financed by society as a whole with their present and future taxation, there should be significantly more accountability: not only how much is spent in cash transfers, but whether society’s getting the expected results for each marginal dollar invested. On the other, the design of such programs is often haphazard, reflecting the stratification and consolidation of politically-irrevocable policies over time, but it’s largely unknown how to improve them. Both of these issues require an extensive involvement of real data to make sense of what’s really going on beyond the mental models of policy-makers and analysts.
There are already some examples of cash transfer policies that have been developed in tandem with strategies for data acquisition and testing, such as Progresa/Oportunidades in Mexico. Beyond evaluating whether policies are sufficient and cost-effective, evidence-oriented policy-making can also help improve the design of policies by means of quasi-experimental and experimental tests, particularly Randomized Controlled Trials (RCTs). Policy developments that incorporate the ability of running tests on mechanism design ideas and implementation details hold the possibility for significantly better anti-poverty policy in the future.
Given these early experiences and the potential upsides and downsides of direct cash transfer policies (particularly when conditioned to longer-term personal investments such as education), we recommend:
- International development agencies should track cash transfer policies around the world on a continuous basis in order to produce comparative intelligence;
- As much as possible, international agencies should track actual implementation details and results as closely as possible, rather than rely merely on the macro results which may have to do with other factors as well;
- Development agencies should develop “best practices” guidebooks in light of their analysis of international experience and their theoretical understanding of economic policy and policy-making;
- Testing and iterative design should be emphasized in such “best practices”, as well as concrete policy advisories and possible agreements for foreign aid.
Barrientos, Armando, and Juan M. Villa (2013). “Evaluating Antipoverty Transfer Programs in Latin America and Sub-Saharan Africa: Better Policies? Better politics?” WIDER Working Paper, No. 009.
Galiani, Sebastian, and Patrick J. McEwan (2013). “The Heterogeneous Impact of Conditional Cash Transfers.” Journal of Public Economics, No. 103: 85-96.
Rawlings, Laura B., and Gloria M. Rubio (2005). “Evaluating the Impact of Conditional Cash Transfer Programs.” The World Bank Research Observer, 20.1: 29-55.
