On Balance: Using Cost-Benefit Analysis to Make the World a Better Place

If you had billions of dollars to make the world a better place, and could spend it however you wanted, how would you maximize your impact? This is not just a thought experiment, but a daily concern for the world’s governments, philanthropists, and multilateral institutions. Since 2004, Copenhagen Consensus has been using cost-benefit analysis to help decision makers identify highly effective interventions. While most cost-benefit analysis seeks the best solution for a single problem, Copenhagen Consensus takes a wider view, looking across all major domains for policies that improve social welfare.

 

Our approach is, first, to identify smart ideas across 15 to 20 relevant policy domains by consulting widely in the region or country in which we’re working. This process typically generates more than a thousand ideas. An advisory council then whittles this list down to around 100—with preference given to ideas that are likely to be highly cost-effective or those backed with significant funding and political will. We then work with some of the world’s top economists to analyze the costs and benefits of these 100, insofar as data and other constraints permit.

Working with top economists is both a humbling and a rewarding experience, and coordinating across 20 to 30 teams requires vigilance to ensure that the teams follow the guidance we provide. One key challenge is ensuring that similar assumptions, such as discount rates or the value of mortality risk reductions, are used across analyses. We also try to ensure consistency in the underlying health, demographic and economic data. We also face significant challenges because the level of rigor possible and quality of evidence varies across disciplines. The only solution is to be very clear about the quality and source of data and evidence, accompanied by the appropriate caveats.

Moreover, different academic disciplines have built up ways of working and norms that are not necessarily compatible with those of other disciplines. For example, education economists, in calculating the returns to schooling, tend not to account for unemployment, labor force participation and wage growth, the idea being that the effects of these would roughly cancel each other out in say an analysis of primary vs. secondary education. However, these effects must be included when comparing primary education to rural roads or household sanitation, for example, because they cannot be assumed to cancel out in the same way.

A related challenge is encouraging researchers to estimate benefits not typically measured in their field. Agricultural economists tend to care most about yields and farmer profit. Poverty economists will generally measure the effects of interventions on consumption. However, it is reasonable to assume that both of these would have effects on health, which might be more highly valued than the market value of yield or consumption growth—producing a higher benefit-cost ratio (BCR). We’ve found the best approach is to bring together a multi-disciplinary team.

The research component takes around 12 to 15 months. At the conclusion, the research is summarized in a league table (ranking) of interventions based on the BCR. A panel of eminent economists, usually including Nobel Laureates, studies the new research and prioritizes the interventions, based on the cost-benefit results and their own insights and judgements. This prioritized list and the league table are presented to decision makers, who are encouraged to implement those towards the top of the list.

Below is an example of the top interventions by BCR in nutrition, electricity, and energy from our project in Haiti, sponsored by the government of Canada (the full chart of 85 interventions is here). A similar graph could also feature net benefits, but we focus on BCR since developing countries tend to be acutely resource constrained both in terms of money and management attention, and any new interventions are likely to displace existing ones. However, we make sure that interventions reach a minimum size threshold so that very small projects that might have artificially high BCRs are not considered. The report on Preventative Nutrition Interventions for Haiti, by Reina Engle-Stone and co-authors, found that wheat flour fortification was the highest ranked intervention, with a BCR of 24.

Although it is not the only factor determining priorities, this simple BCR chart can be compelling. It distils hundreds of pages of peer-reviewed research into one simple graph. When we presented this to the President of Haiti, Jovenel Moïse, his first reaction was surprise: it had not occurred to him that one of the most effective interventions for his country would be fortifying wheat with iron and folic acid.

In this particular case, wheat flour fortification had several advantages over other interventions. First, a significant portion of the population consumes wheat regularly; 40% of urban and 34% of rural Haitians indicate they eat bread 3-4 times per week. Second, only a handful of flour millers process almost all of the wheat consumed in the country, and the fortification powder is relatively inexpensive.

Third, the problems addressed by the intervention – anemia and neural tube defects – are very prevalent in Haiti. About half of Haitian women and children are anemic and the rate of neural tube defects is 3-4 times higher than the rate with full coverage of folic acid.

Consequently, wheat flour fortification is particularly compelling for Haiti because only two or three entry points are needed to address a wide-spread health problem, and people do not need to change their behavior to generate the benefits. After seeing the results, President Moïse promised to enact the intervention within six months. It was subsequently co-funded by the United States Agency for International Development (USAID) with technical support from experts at University of California, Davis, some of whom had authored the Copenhagen Consensus report.

Besides Haiti, Copenhagen Consensus has been able to convince governments across the world to enact more effective policies. For example, following our Bangladesh project in 2016, the government expanded e-procurement to all departments, in part based on the evidence of our report estimating the BCR of the intervention at a phenomenal 700 (Abdallah, 2017).

The Bangladesh project highlights an interesting and important insight from our multi-intervention cost-benefit research: the best interventions provide significantly more effective uses of a marginal dollar than the median intervention—by 1 to 3 orders of magnitude.

As another example, in an exercise we conducted in the state of Rajasthan in India, the top intervention—improved screening and treatment for tuberculosis—had a BCR of almost 180; the median intervention had a BCR of 4.5. Similarly dispersed distributions have been documented in cost-effectiveness reviews of health and education interventions in the developing world (Ord, 2013; McEwan, 2015).

Source: Rajasthan Priorities project. Red bar represents median intervention with BCR of 4.5.

What are the implications of the wide range in BCRs across interventions? Oxford philosopher Toby Ord has noted in a 2013 essay, “The Moral Imperative Toward Global Cost-effectiveness in Global Health,” that it is critical to identify the outliers and push for their implementation (Ord, 2013). Such an approach is likely to be better than making incremental improvements in existing spending. For example, if the average intervention in a policy space has, say, a BCR of five and the most effective intervention possible is 500, doubling the efficiency of 99% of funds under control would deliver as much social good as shifting 1% of funds to the most effective intervention available.

Copenhagen Consensus approaches research with a mission of maximizing social welfare. Thus, it is important for us to do as many cost-benefit analyses as possible – usually more than 75 per project – to increase the likelihood that we identify an outlier. Overall, we hope that we inject useful information into the policy space, and provide information that is usually absent where it is needed most.

We are constantly looking for more ways to collaborate with the community of cost-benefit analysts, so please drop me a line if you’d like to know more: [email protected]

References
Abdallah, Wahid. 2017. “Electronic Public Procurement in Bangladesh” in Bangladesh Priorities: Helping Make Vision 2021 a Reality ed. Bjorn Lomborg and Mahfuzar Rahman, BRAC University Press, Dhaka

McEwan, Patrick J. 2015. “Improving Learning in Primary Schools of Developing Countries: A Meta-analysis of Randomized Experiments.” Review of Education Research, 85(3): 353-394
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