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Averting Statistical Tragedies

Recent academic research shows that economic statistics generated by low-income countries are just as reliable as those from advanced economies. Far from throwing good money after bad, investing in poor countries’ statistical capacity is key to achieving their development goals.

NEW HAVEN – In a July 2020 article for Brookings Papers on Economic Activity, Tristan Reed and I showed that, contrary to expectations, COVID-19 deaths per capita were much lower in poorer countries than in richer ones. Readers immediately countered that this finding must be due to mismeasurement or a lack of data for these countries. Our result has since withstood scrutiny and the test of time, but the initial response was revealing: statistics originating in developing countries tend to be met with suspicion (and often are dismissed outright).

Is this bias justified? In a recent paper for the Journal of Economic Perspectives, “Why is Growth in Developing Countries so Hard to Measure?” my co-authors and I find that it is not. Notwithstanding a few highly publicized cases of data manipulation, growth estimates from developing countries are as reliable as those from advanced economies, on average.

To be sure, there is no single, well-defined metric for judging the quality of a country’s growth estimates. But the traditional approach in the economics literature is to look for correlation between estimates obtained using different data sources. Employing this method, we compared estimates based on three distinct sources: the System of National Accounts (SNA), household survey data, and newly available satellite data (mainly on nighttime light, and occasionally on vegetation).

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