Illuminating Economic Growth

58 Pages Posted: 2 Jun 2019

See all articles by Yingyao Hu

Yingyao Hu

Johns Hopkins University - Department of Economics

Jiaxiong Yao

International Monetary Fund (IMF)

Date Written: April 2019

Abstract

This paper seeks to illuminate the uncertainty in official GDP per capita measuresusing auxiliary data. Using satellite-recorded nighttime lights as an additional measurementof true GDP per capita, we provide a statistical framework, in which the error inofficial GDP per capita may depend on the country's statistical capacity and the relationshipbetween nighttime lights and true GDP per capita can be nonlinear and varywith geographic location. This paper uses recently developed results for measurementerror models to identify and estimate the nonlinear relationship between nighttime lightsand true GDP per capita and the nonparametric distribution of errors in official GDP percapita data. We then construct more precise and robust measures of GDP per capita usingnighttime lights, official national accounts data, statistical capacity, and geographic locations.We find that GDP per capita measures are less precise for middle and low incomecountries and nighttime lights can play a bigger role in improving such measures.

Keywords: Low income countries, Economic growth, Development, Emerging markets, Technological innovation, Nighttime lights, measurement error, GDP per capita., real GDP, optimal weight, income country, official measure, middle income country

JEL Classification: E01, E23, C18, F16, O4, L31, D4, E2, E24, Z13

Suggested Citation

Hu, Yingyao and Yao, Jiaxiong, Illuminating Economic Growth (April 2019). Available at SSRN: https://ssrn.com/abstract=3397536 or http://dx.doi.org/10.2139/ssrn.3397536

Yingyao Hu (Contact Author)

Johns Hopkins University - Department of Economics ( email )

3400 Charles Street
Baltimore, MD 21218-2685
United States

Jiaxiong Yao

International Monetary Fund (IMF) ( email )

700 19th Street, N.W.
Washington, DC 20431
United States

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