Mapping GDP and PPPs at Sub-National Level Through Earth Observation in Eastern Europe and CIS Countries

M S Andreano,G Savio,R Benedetti,F Piersimoni

doi:10.34023/2313-6383-2019-26-11-70-84

Abstract

Following the line of research, originated from the paper by Henderson et al. (2012), this article focuses on how “observations from the above, in the form of night-lights satellite data, might contribute in mapping at very fine geographical level (ideally, one square km), two core macroeconomic indicators used extensively in the Sustainable Development Goals monitoring and reporting framework: Gross Domestic Product (GDP) and Purchasing Power Parities (PPPs). Recent empirical economic studies have paid increasing attention on the association between night-lights observations and economic growth, in order to estimate a consistent and objective level of economic activities at subnational level. In the present paper, analyses are carried out on a panel of 17 Eastern Europe and CIS countries for the period 2000-2013 and use is made of indicators constructed from satellite images in the form of night lights, as processed by the US Department of Defense, and its Defense Meteorological Satellite Program’s OperationalLinescan System. Estimations of GDP in current US dollars and PPP terms are carried out at both national and sub-national level, and results are compared with the official available information. Estimates of GDP and PPP were also compared, at national level, with those in the World Bank data-set, showing similar behaviours. Results are used to obtain gridded maps of GDPs and PPPs.

Highlights

Following the line of research originated from the paper by Henderson et al [1], this article focuses on how «observations from the above», in the form of night-lights satellite data, might contribute in mapping at very fine geographical level, two core macroeconomic indicators used extensively in the Sustainable Development Goals (SDG) monitoring and reporting framework: GDP and PPPs
This research uses extensively the set of information coming from satellite images, as processed by the US Department of Defense, and its Defense Meteorological Satellite Program’s Operational Linescan System (DMSP-OLS)
Higher mean values of digital number (DN) are found in richer realities having top GDP per capita values in terms of PPPs, Czechia, Poland, Slovakia, Hungary and Russia, showing a clearly positive correlation between lights and GDP, which seems at odds with Martinez [20] findings of a negative relation between GDP and night-time lights

Summary

Introduction

The adoption of the Sustainable Development Goals in September 2015 by the United Nations General Assembly is calling National Statistics Offices (NSOs) worldwide to underpin a data revolution, as they are asked to extend both the scope and disaggregation of the data traditionally produced, and measure new economic, social and environmental phenomena, leaving none behind. After testing for the existence of temporally and spatially stable elasticity of GDP both in real and PPP terms with respect to lights, the estimated coefficients are used to map economic activity and parities at very fine geographical level, offering two sets of information that are mostly needed for SDGs monitoring and reporting. We are fully aware that the estimations provided in this paper cannot replace primary statistics produce by NSOs of the region We hope these estimates will be of some use for policy makers and researchers for their policy intervention, analyses and discussion, and contribute in partially answering the increasing demand for more spatially disaggregated macroeconomic data to further advance the sustainable development agenda. The last Section of the paper summarizes main results and concludes

Night-Lights Data from Satellite Images

Model and Empirical Results

Conclusions