Measuring people’s preferences

Approach

We surveyed over 1,800 low-income individuals across four diverse regions in Ghana and Kenya. Three main methods¹ were used to capture how respondents trade-off between averting deaths of individuals of different ages and increasing consumption:

1. We asked individuals for their willingness-to-pay (WTP) to reduce the risk of death for themselves and their children.²
2. We asked respondents to take the perspective of a decision-maker in their community and choose between programs that:
   1. Save lives of different ages;
   2. Save lives and provide cash transfers.

We also collected qualitative data on beneficiaries’ reasoning when making these trade-offs, and data on beneficiaries’ lives that can be used to inform GiveWell staff’s moral weights.³

Findings

• Respondents place a higher value on averting a death⁴ than predicted by most extrapolations from studies in high-income countries (HICs).
  • Our central estimate of value placed on averting death for individuals 5 and older was $40,721, which is 1.7 times higher than the current GiveWell staff median.
• Respondents consistently value the lives of individuals under 5 higher than individuals 5 and older, which is consistent with HIC studies but contrary to median GiveWell moral weights.
  • Our central estimate of value placed on averting death for individuals under 5 was $65,906, which is 4.9 times higher than the current GiveWell staff median.

Qualitative data suggests these high valuations are driven by a large proportion of individuals making two arguments. The first argument asserts the importance of accounting for the potential held by all individuals to achieve high economic and social value over their life course. A second common argument is that life holds inherent value and therefore no amount of money is sufficient to forego the chance to save a life.

Implications

For GiveWell, incorporating the preferences captured in this study and described above would result in:

1. Placing a higher value on averting deaths relative to doubling consumption,
2. Placing a higher value on averting the death of individuals under 5 than individuals 5 and older.

This would lead to higher relative cost-effectiveness of charities whose good is achieved primarily by averting the death of young children (e.g. Helen Keller International, Malaria Consortium, and Against Malaria Foundation, etc.).⁵

Beyond GiveWell, this study demonstrates that it is possible to inform the complex, moral trade-offs faced in development by capturing the preferences of the people affected by these decisions. It also represents a substantial addition to the existing literature on individual cross-outcome preferences, in which low-income populations and particularly those in Sub-Saharan Africa, have previously been severely underrepresented.

In a development sector that is generally reluctant to rigorously compare different types of
outcomes, we believe this study could make the use of portfolio-level cost-effectiveness analysis more appealing. We encourage additional research to further develop an understanding of beneficiary preferences across program areas and from different populations.