africa

Africa at a Fork in the Road: Taking Off or Disappointment Once Again?
Ravallion, 2010). Reasonable people can and do disagree, and disagreements are
sure to plague any choice of weights for an inclusive growth index.
One way to avoid this problem is to use a “dashboard” of indicators rather than
a single index (Stiglitz and others, 2009; Ravallion, 2010). A car’s dashboard has
multiple indicators for key variables—oil pressure, engine temperature, fuel level—
that help you or your mechanic to assess the car’s status. Combining all of these
indicators into a single index of your car’s wellbeing probably would not be helpful,
except perhaps to tell you whether you should be driving it or not. 4
Ravallion (2010) argues that rather than “mashing up” many disparate indicators
into a single index, policymakers are better off seeing a dashboard that includes
all of the indicators that go into the index. His argument has two main points. First,
the weights used in building the index are rarely rooted in any sort of economic or
ethical theory. 5 They are chosen arbitrarily by the indices’ creators and can lead
to unattractive marginal rates of substitution between the components (Ravallion,
2010 lists examples.) Second, the trade-offs that the weights imply between the
various dimensions of the index are often opaque, and it is difficult for policymakers
to understand exactly how much the index will change if the value of an included
variable changes, and what the trade-offs might be between improvements in the
different variables. Thus, even though the main motivation of most such indices,
including a presumed inclusive growth index, is to focus policymakers’ attention
on something that matters, this focus will not do much good if policymakers do not
understand how their actions affect the value of the index. In fact, for most policy
purposes, Ravallion argues that the individual components of any purported index
are more useful. If we see the infant mortality rate go down, say, we have a pretty
clear sense of what that means and what policies might be responsible. That same
clarity is lacking in a “mash-up” index.
But the dashboard approach also has limitations. As a technical matter, it is a “columns
first” approach that does not take the second step of aggregating across the
rows of the matrix. As a consequence, the dashboard does not take into account
the correlation of deprivations (for example when poor health and nutrition are correlated
with lack of physical infrastructure and lack of schooling). And even though
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