Much of the development work is about behavior change, the assumption that with extra resources and knowledge people (also known as beneficiaries) will do things better in the future. Nowadays there is an increasing shift towards the 'at-risk' label (although 'vulnerable' is still going strong) to justify targeting: youth at-risk, women at-risk, children at-risk. However, Kerwin's job market paper "The Effect of HIV Infection Risk Beliefs on Risky Sexual Behaviors: ScaredStraight or Scared to Death?" suggests that we may be wrongly identifying both target groups and responses.
Abstract
"Economists
typically assume that risk compensation is uniformly self-protective - that
people
become more careful as the health risks of their actions increase. However,
risk-seeking, or
fatalistic, responses can also be rational: increased risks can lead people to
take fewer precautions.
I extend the typical model of risk compensation to show that fatalism is a
rational response
to sufficiently high risks if people do not have perfect control over all possible
exposures,
and if the condition in question is irreversible. This result holds even for
people who do not
understand how to add up probabilities. I test this model's implications by
randomizing the
provision of information on HIV transmission risks to people in Malawi, a
country with a severe
HIV epidemic where there is qualitative evidence of fatalistic responses to the
virus.
Average risk
responses are self-protective and statistically significant, but small in magnitude: the mean
risk elasticity of sexual behavior is roughly -0.6. To test the model of
rational fatalism,I develop
a method of decomposing 2SLS estimates of the risk elasticity of sexual
behavior by baseline
risk beliefs. Consistent with the predictions of my theoretical framework, I find that this
elasticity varies sharply by baseline risk beliefs: the risk elasticity varies
from -2.3 for the lowest
initial beliefs to 2.9 for the highest initial beliefs. 13.8% of the population
has a positive elasticity,
suggesting they are fatalistic."
While the study focuses on HIV, how we handle 'at risk' groups is conceptually similar across the sectors. In most cases, targets are identified according to socioeconomic status, employment, location, age and other indicators of potential risk. The advantage of this method is that is relatively easy to identify people with this criteria. The study adds yet another criteria: fatalism, an indicator extremely relevant and yet very difficult to measure (somehow some behaviors can be used as proxy). A fatalist view will not attempt to mitigate the risks but rather embrace them and assume the worst already, making traditional risk education infective (as it tends to highlight negatives as a preventive methodology).
We see a similar issue regarding suicide bombers, gang membership and other high risk behaviors, where the at-risk profile is wide enough to include thousands (if not millions) and yet the actual number of joining are well below. Maybe what we need is better psychological profiling in order to be more precise in both identifying beneficiaries and tailoring the message.
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