http://www.nber.org/papers/w15199.pdf
Measuring Economic Growth from Outer Space

J. Vernon Henderson, Adam Storeygard, and David N. Weil
NBER Working Paper No. 15199

July 2009, Revised December 2010
JEL No. E01,O47,Q1,R11

ABSTRACT

GDP growth is often measured poorly for countries and rarely measured at all for cities or subnational
regions. We propose a readily available proxy: satellite data on lights at night. We develop a statistical
framework that uses lights growth to augment existing income growth measures, under the assumption
that measurement error in using observed light as an indicator of income is uncorrelated with measurement
error in national income accounts. For countries with good national income accounts data, information
on growth of lights is of marginal value in estimating the true growth rate of income, while for countries
with the worst national income accounts, the optimal estimate of true income growth is a composite
with roughly equal weights. Among poor-data countries, our new estimate of average annual growth
differs by as much as 3 percentage points from official data. Lights data also allow for measurement
of income growth in sub- and supranational regions. As an application, we examine growth in Sub
Saharan African regions over the last 17 years. We find that real incomes in non-coastal areas have
grown faster by 1/3 of an annual percentage point than coastal areas; non-malarial areas have grown
faster than malarial ones by 1/3 to 2/3 annual percent points; and primate city regions have grown
no faster than hinterland areas. Such applications point toward a research program in which “empirical
growth” need no longer be synonymous with “national income accounts.”

6. Conclusion
Satellite night-lights data are a useful proxy for economic activity at temporal and geographic
scales for which traditional data are of poor quality or are unavailable. In this paper, we develop
a statistical model to combine data on changes in night lights with data on measured income
growth to improve estimates of true income growth. One assumption of the model is that　measurement error in growth as depicted in the national income accounts is uncorrelated with the
measurement error that occurs when the change in light is used to measure growth. While there
are many potential sources of error in using lights growth to measure income growth, none of
them suggest this assumption is inappropriate. But if one wanted to, the framework could be
adjusted to allow for such correlation.
Our methodology involves estimating both a coefficient that maps light growth into a
proxy for GDP growth and also an optimal weight to be applied in combining this proxy with
national accounts data. For countries with high-quality national accounts data, the information
contained in lights growth is of little value in improving income growth measures. However, for
countries with low-quality national accounts data, the optimal composite estimate puts roughly
equal weight on lights growth and national accounts data. We apply the methodology to low and
middle income countries with very low quality national accounts data, as rated by the World
Bank. For these 30 countries, we get a new set of income growth numbers for the years 1992/3–
2005/6. These estimates differ from measured WDI real GDP growth numbers by up to 3.2% per
year. We also estimate that among low and middle income countries, the elasticity of growth of
light emanating into space with respect to income growth is close to one.
For all countries, lights data can play a key role in analyzing growth at sub- and
supranational levels, where income data at a detailed spatial level are unavailable. To illustrate
this and build on the theme that research directions in empirical growth need no longer be
synonymous with national income accounts data, we examine three issues in growth analysis
applied to sub-Saharan Africa. We look at whether over the last 17 years coastal areas have
grown faster than non-coastal areas; whether primate cities have grown faster than hinterlands;
and whether malarial areas have had a better growth experience compared to non-malarial areas.
The answer to all these questions is no, which leaves for future research the question of why.

仮にその国の発光の総量が発電の総量の関数であったとしても、電力料金は国毎に異なり、電力料金が高い国ほど、電力がＧＤＰに占める割合は高くなる。
高い料金の電力をじゃぶじゃぶ使う国ほど、見かけの光量よりも豊かな国とみなすのが、ＧＤＰの豊かさの指標としての特性である。