The variance framework clarifies a lot. The harder part may sit inside the “bounded downside” category itself.
Global health interventions look convex partly because the downside appears measurable and contained. But “unlikely to cause harm” and “bounded downside” often get conflated in ways that deserve more scrutiny. An intervention with weak evidence, scaled substantially, can produce harm that only surfaces in aggregate — substitution effects crowding out stronger alternatives, institutional credibility consumed on interventions that underperform, donor attention patterns that persist beyond the evidence. None of those show up as direct harm in a single-program evaluation.
The distribution may look bounded from inside one intervention and fat-tailed from the portfolio level. That asymmetry seems worth naming before treating global health as the safe side of the variance line.
Yes, I agree, it is non-trivial to assess (approximately, probably) bounded downside and this needs to be done on a case-by-case basis, including in global health.
However, if you find that there are fat tails on a portfolio level but none on the individual intervention level, then the individual intervention was probably not assessed comprehensively? Interaction effects and second order effects matter, of course, but at least a portion of them should arguably be credited back to individual iterventions as you assess them.
The variance framework clarifies a lot. The harder part may sit inside the “bounded downside” category itself.
Global health interventions look convex partly because the downside appears measurable and contained. But “unlikely to cause harm” and “bounded downside” often get conflated in ways that deserve more scrutiny. An intervention with weak evidence, scaled substantially, can produce harm that only surfaces in aggregate — substitution effects crowding out stronger alternatives, institutional credibility consumed on interventions that underperform, donor attention patterns that persist beyond the evidence. None of those show up as direct harm in a single-program evaluation.
The distribution may look bounded from inside one intervention and fat-tailed from the portfolio level. That asymmetry seems worth naming before treating global health as the safe side of the variance line.
Yes, I agree, it is non-trivial to assess (approximately, probably) bounded downside and this needs to be done on a case-by-case basis, including in global health.
However, if you find that there are fat tails on a portfolio level but none on the individual intervention level, then the individual intervention was probably not assessed comprehensively? Interaction effects and second order effects matter, of course, but at least a portion of them should arguably be credited back to individual iterventions as you assess them.