Nighttime lights as a proxy for human development at the local level
Open accessAbstract
Nighttime lights, calculated from weather satellite recordings, are increasingly used by social scientists as a proxy for economic activity or economic development in subnational regions of developing countries where disaggregated data from statistical offices are not available. However, so far, our understanding of what nighttime lights capture in these countries is limited. We use geo-referenced Demographic and Health Surveys (DHS) from 29 African countries to construct indicators of household wealth, education and health for DHS cluster locations as well as for grid cells of roughly 50 × 50 km. We show that nighttime lights are positively associated with these location-specific indicators of human development, and that the variation in nighttime lights can explain a substantial share in the variation in these indicators. We conclude that nighttime lights are a good proxy for human development at the local level.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The R2 values in Table 2 are generally slightly lower than ranges reported in previous studies.
“Compared to previous studies of economic activity and nightlights, 𝑅 2 in Table 2 are in general slightly lower than ranges in previous studies [7, 15, 18, 29].”
From Under the Radar -- Auditing Fairness in ML for Humanitarian Mapping (2021) · cites this paper as [7]
The Results > Main results section reports how much variation in household wealth and other local development measures nighttime lights explain, providing figures for a previous study. Our copy does not give the citing paper’s Table 2 values, so it cannot establish that those values are generally slightly lower. (LLM, conf=0.78)
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Murray, D. D., Suzuki, K., Law, M. G., Trebicka, J., Neuhaus, J., Wentworth, D. N., Johnson, M. A., Vjecha, M. J., Kelleher, A. D., Emery, S., et al. (2015) · PLoS ONE · doi:10.1371/journal.pone.0139981 · Cited by 2,740 · see citing works
Measuring Economic Growth from Outer Space
Henderson, J. V., Storeygard, A., & Weil, D. N. (2012) · American Economic Review · doi:10.1257/aer.102.2.994 · Cited by 2,596 · see citing works
(2017) · The SHAFR Guide Online · doi:10.1163/2468-1733_shafr_sim010030025 · Cited by 2,357 · see citing works
Combining satellite imagery and machine learning to predict poverty
Jean, N., Burke, M., Xie, M., Davis, W. M., Lobell, D. B., & Ermon, S. (2016) · Science · doi:10.1126/science.aaf7894 · Cited by 1,664 · see citing works
Alternative Transformations to Handle Extreme Values of the Dependent Variable
Burbidge, J. B., Magee, L., & Robb, A. L. (1988) · Journal of the American Statistical Association · doi:10.1080/01621459.1988.10478575 · Cited by 1,425 · see citing works
Using luminosity data as a proxy for economic statistics
Chen, X., & Nordhaus, W. D. (2011) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1017031108 · Cited by 1,188 · see citing works
Rutstein, S. O., & Johnson, K. (2004) · doi:10.13140/2.1.2806.4809 · Cited by 984 · see citing works
Pre-Colonial Ethnic Institutions and Contemporary African Development
(2013) · Econometrica · doi:10.3982/ecta9613 · Cited by 953 · see citing works
Hodler, R., & Raschky, P. A. (2014) · The Quarterly Journal of Economics · doi:10.1093/qje/qju004 · Cited by 722 · see citing works
Self-citationMapping regional economic activity from night-time light satellite imagery
Doll, C. N. H., Müller, J., & Morley, J. G. (2005) · Ecological Economics · doi:10.1016/j.ecolecon.2005.03.007 · Cited by 709 · see citing works
National Institutions and Subnational Development in Africa *
Michalopoulos, S., & Papaioannou, E. (2013) · The Quarterly Journal of Economics · doi:10.1093/qje/qjt029 · Cited by 581 · see citing works
Night-Time Light Data: A Good Proxy Measure for Economic Activity?
Mellander, C., Lobo, J., Stolarick, K., & Matheson, Z. (2015) · PLoS ONE · doi:10.1371/journal.pone.0139779 · Cited by 534 · see citing works
Sutton, P. C., & Costanza, R. (2002) · Ecological Economics · doi:10.1016/s0921-8009(02)00097-6 · Cited by 507 · see citing works
A global poverty map derived from satellite data
Elvidge, C. D., Sutton, P. C., Ghosh, T., Tuttle, B. T., Baugh, K., Bhaduri, B., & Bright, E. A. (2009) · Computers & Geosciences · doi:10.1016/j.cageo.2009.01.009 · Cited by 497 · see citing works
Stiglitz, J. E., Sen, A. K., Fitoussi, J., & Sarkozy, N. (2010) · Virtual Defense Library (Ministerio de Defensa) · Cited by 494 · see citing works
Census from Heaven: An estimate of the global human population using night-time satellite imagery
Sutton, P. C., Roberts, D. A., Elvidge, C. D., & Baugh, K. (2001) · International Journal of Remote Sensing · doi:10.1080/01431160010007015 · Cited by 477 · see citing works
PRIO-GRID: A unified spatial data structure
Tollefsen, A. F., Strand, H., & Buhaug, H. (2012) · Journal of Peace Research · doi:10.1177/0022343311431287 · Cited by 429 · see citing works
Farther on down the Road: Transport Costs, Trade and Urban Growth in Sub-Saharan Africa
Storeygard, A. (2016) · The Review of Economic Studies · doi:10.1093/restud/rdw020 · Cited by 409 · see citing works
The Global Distribution of Economic Activity: Nature, History, and the Role of Trade1
Henderson, J. V., Squires, T., Storeygard, A., & Weil, D. N. (2017) · The Quarterly Journal of Economics · doi:10.1093/qje/qjx030 · Cited by 398 · see citing works
Estimation of Gross Domestic Product at Sub-National Scales using Nighttime Satellite Imagery
Sutton, P. C., Elvidge, C. D., & Ghosh, T. (2007) · International journal of ecological economics and statistics · Cited by 334 · see citing works
Stiglitz, J. E., Sen, A. K., & Fitoussi, J. (2010) · The New Press eBooks · doi:10.1515/9781595585929 · Cited by 327 · see citing works
The Legacy of Historical Conflict: Evidence from Africa
BESLEY, T., & REYNAL-QUEROL, M. (2014) · American Political Science Review · doi:10.1017/s0003055414000161 · Cited by 322 · see citing works
A scale-adjusted measure of “Urban sprawl” using nighttime satellite imagery
Sutton, P. C. (2003) · Remote Sensing of Environment · doi:10.1016/s0034-4257(03)00078-6 · Cited by 293 · see citing works
Alesina, A., Michalopoulos, S., & Papaioannou, E. (2016) · Journal of Political Economy · doi:10.1086/685300 · Cited by 248 · see citing works
Development of a 2009 Stable Lights Product using DMSP-OLS data
Baugh, K., Elvidge, C. D., Ghosh, T., & Ziskin, D. C. (2010) · Proceedings of the Asia-Pacific Advanced Network · doi:10.7125/apan.30.17 · Cited by 235 · see citing works
Using night light emissions for the prediction of local wealth
Weidmann, N. B., & Schutte, S. (2017) · Journal of Peace Research · doi:10.1177/0022343316630359 · Cited by 215 · see citing works
Using remotely sensed night-time light as a proxy for poverty in Africa
Noor, A. M., Alegana, V. A., Gething, P. W., Tatem, A. J., & Snow, R. W. (2008) · Population Health Metrics · doi:10.1186/1478-7954-6-5 · Cited by 171 · see citing works
Ethnic favoritism: An axiom of politics?
Luca, G. D. D., Hodler, R., Raschky, P. A., & Valsecchi, M. (2017) · Journal of Development Economics · doi:10.1016/j.jdeveco.2017.12.006 · Cited by 166 · see citing works
Self-citationA sharper image? Estimates of the precision of nighttime lights as a proxy for economic statistics
Nordhaus, W. D., & Chen, X. (2014) · Journal of Economic Geography · doi:10.1093/jeg/lbu010 · Cited by 163 · see citing works
Estimation of Mexico’s Informal Economy and Remittances Using Nighttime Imagery
Ghosh, T., Anderson, S., Powell, R., Sutton, P. C., & Elvidge, C. D. (2009) · Remote Sensing · doi:10.3390/rs1030418 · Cited by 157 · see citing works
Detection of rural electrification in Africa using DMSP-OLS night lights imagery
Min, B., Gaba, K. M., Sarr, O. F., & Agalassou, A. (2013) · International Journal of Remote Sensing · doi:10.1080/01431161.2013.833358 · Cited by 156 · see citing works
Microfinance Banks and Financial Inclusion
Brown, M., Guin, B., & Kirschenmann, K. (2015) · European Finance Review · doi:10.1093/rof/rfv026 · Cited by 130 · see citing works
Intensive and extensive margins of mining and development: Evidence from Sub-Saharan Africa
Mamo, N., Bhattacharyya, S., & Moradi, A. (2019) · Journal of Development Economics · doi:10.1016/j.jdeveco.2019.02.001 · Cited by 111 · see citing works
Economic shocks and civil conflict at the regional level
Hodler, R., & Raschky, P. A. (2014) · Economics Letters · doi:10.1016/j.econlet.2014.07.027 · Cited by 87 · see citing works
Self-citationWho's in the Dark—Satellite Based Estimates of Electrification Rates
Elvidge, C. D., Baugh, K., Sutton, P. C., Bhaduri, B., Tuttle, B. T., Ghosh, T., Ziskin, D. C., & Erwin, E. H. (2011) · doi:10.1002/9780470979563.ch15 · Cited by 52 · see citing works
Explaining Subnational Infant Mortality and Poverty Rates: What Can We Learn from Night-Time Lights?
Chen, X. (2015) · Spatial Demography · doi:10.1007/s40980-015-0009-x · Cited by 16 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
African leaders and the geography of China's foreign assistance
Dreher, A., Fuchs, A., Hodler, R., Parks, B. C., Raschky, P. A., & Tierney, M. J. (2019) · Journal of Development Economics · doi:10.1016/j.jdeveco.2019.04.003 · Cited by 319 · see citing works
Self-citationDrivers of global mangrove loss and gain in social-ecological systems
Hagger, V., Worthington, T. A., Lovelock, C. E., Adame, M. F., Amano, T., Brown, B. M., Friess, D. A., Landis, E., Mumby, P. J., Morrison, T. H., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-33962-x · Cited by 267 · see citing works
Machine learning in agricultural and applied economics
Storm, H., Baylis, K., & Heckelei, T. (2019) · European Review of Agricultural Economics · doi:10.1093/erae/jbz033 · Cited by 227 · see citing works
Global emergence of unprecedented lifetime exposure to climate extremes
Grant, L., Vanderkelen, I., Gudmundsson, L., Fischer, E. M., Seneviratne, S. I., & Thiery, W. (2025) · Nature · doi:10.1038/s41586-025-08907-1 · Cited by 153 · see citing works
Leveraging mobile phones to attain sustainable development
Rotondi, V., Kashyap, R., Pesando, L. M., Spinelli, S., & Billari, F. C. (2020) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1909326117 · Cited by 146 · see citing works
High-Resolution Maps of Material Stocks in Buildings and Infrastructures in Austria and Germany
Haberl, H., Wiedenhofer, D., Schug, F., Frantz, D., Virág, D., Plutzar, C., Gruhler, K., Lederer, J., Schiller, G., Fishman, T., et al. (2021) · Environmental Science and Technology · doi:10.1021/acs.est.0c05642 · Cited by 127 · see citing works
Cao, Q., Zhang, X., Lei, D., Guo, L., Sun, X., Kong, F., & Wu, J. (2019) · Journal of Cleaner Production · doi:10.1016/j.jclepro.2019.03.125 · Cited by 112 · see citing works
Bluhm, R., Dreher, A., Fuchs, A., Parks, B. C., Strange, A. M., & Tierney, M. J. (2018) · SSRN Electronic Journal · doi:10.2139/ssrn.3262101 · Cited by 105 · see citing works
GeoQuery: Integrating HPC systems and public web-based geospatial data tools
Goodman, S., BenYishay, A., Lv, Z., & Runfola, D. M. (2018) · Computers & Geosciences · doi:10.1016/j.cageo.2018.10.009 · Cited by 102 · see citing works
Dreher, A., Fuchs, A., Hodler, R., Parks, B. C., Raschky, P. A., & Tierney, M. J. (2021) · World Development · doi:10.1016/j.worlddev.2020.105291 · Cited by 95 · see citing works
Self-citationReexamining the Effect of Refugees on Civil Conflict: A Global Subnational Analysis
Zhou, Y., & Shaver, A. (2021) · American Political Science Review · doi:10.1017/s0003055421000502 · Cited by 72 · see citing works
Measuring the impact of insurance on urban earthquake recovery using nightlights
Nguyen, C., & Noy, I. (2019) · Journal of Economic Geography · doi:10.1093/jeg/lbz033 · Cited by 69 · see citing works
Spatial Patterns of Development: A Meso Approach
Michalopoulos, S., & Papaioannou, E. (2018) · Annual Review of Economics · doi:10.1146/annurev-economics-080217-053355 · Cited by 69 · see citing works
The local economic impacts of natural disasters
Schippers, V. (2022) · doi:10.33540/1250 · Cited by 65 · see citing works
Ruckelshaus, M. H., Reguero, B. G., Arkema, K. K., Compeán, R. G., Weekes, K., Bailey, A., & Silver, J. M. (2020) · International Journal of Disaster Risk Reduction · doi:10.1016/j.ijdrr.2020.101795 · Cited by 64 · see citing works
Environmental Impacts of Planned Capitals and Lessons for Indonesia’s New Capital
Teo, H. C., Lechner, A. M., Sagala, S., & Campos‐Arceiz, A. (2020) · Land · doi:10.3390/land9110438 · Cited by 58 · see citing works
Mcgregor, T., Smith, B., & Wills, S. (2019) · Oxford review of economic policy · doi:10.1093/oxrep/grz015 · Cited by 37 · see citing works
The effect of natural disaster on economic growth: Evidence from a major earthquake in Haiti
Joseph, I.-L. (2022) · World Development · doi:10.1016/j.worlddev.2022.106053 · Cited by 55 · see citing works
Meng, Y., Xing, H., Yuan, Y., Wong, M. S., & Fan, K. (2020) · Computers Environment and Urban Systems · doi:10.1016/j.compenvurbsys.2020.101544 · Cited by 54 · see citing works
Women Legislators and Economic Performance
Baskaran, T., Bhalotra, S. R., Min, B., & Uppal, Y. (2018) · Journal of Economic Growth · doi:10.1007/s10887-023-09236-6 · Cited by 69 · see citing works
A Spatial-Socioeconomic Urban Development Status Curve from NPP-VIIRS Nighttime Light Data
Yang, C., Yu, B., Chen, Z., Song, W., Zhou, Y., Li, X., & Wu, J. (2019) · Remote Sensing · doi:10.3390/rs11202398 · Cited by 53 · see citing works
Bluhm, R., Fuchs, A., Strange, A. M., Dreher, A., Parks, B. C., & Tierney, M. J. (2020) · SSRN Electronic Journal · doi:10.2139/ssrn.3623679 · Cited by 53 · see citing works
Hall, O., Dompae, F., Wahab, I., & Dzanku, F. M. (2023) · Journal of International Development · doi:10.1002/jid.3751 · Cited by 51 · see citing works
Ambient Population and Larceny-Theft: A Spatial Analysis Using Mobile Phone Data
He, L., Páez, A., Jiao, J., An, P., Lu, C., Mao, W., & Long, D. (2020) · ISPRS International Journal of Geo-Information · doi:10.3390/ijgi9060342 · Cited by 50 · see citing works
Recognizing the equity implications of restoration priority maps
Schultz, B., Brockington, D., Coleman, E. A., Djenontin, I. N. S., Fischer, H. W., Fleischman, F. D., Kashwan, P., Marquardt, K., Pfeifer, M., Pritchard, R., et al. (2022) · Environmental Research Letters · doi:10.1088/1748-9326/ac9918 · Cited by 45 · see citing works
Andries, A., Morse, S., Murphy, R., Lynch, J. M., & Woolliams, E. R. (2019) · Sustainability · doi:10.3390/su11185062 · Cited by 41 · see citing works
Estimating Local Inequality from Nighttime Lights
Weidmann, N. B., & Theunissen, G. (2021) · Remote Sensing · doi:10.3390/rs13224624 · Cited by 40 · see citing works
Bluhm, R., Dreher, A., Fuchs, A., Parks, B. C., Strange, A. M., & Tierney, M. J. (2024) · Journal of Urban Economics · doi:10.1016/j.jue.2024.103730 · Cited by 36 · see citing works
A Country Pandemic Risk Exposure Measurement Model
Grima, S., Kizilkaya, M., Rupeika-Apoga, R., Romānova, I., Gonzi, R. D., & Jakovljević, M. (2020) · Risk Management and Healthcare Policy · doi:10.2147/rmhp.s270553 · Cited by 36 · see citing works
Abio, A., Owusu, P. N., Posti, J. P., Bärnighausen, T., Shaikh, M. A., Shankar, V., & Wilson, M. L. (2022) · Social Psychiatry and Psychiatric Epidemiology · doi:10.1007/s00127-022-02287-x · Cited by 36 · see citing works
Falchetta, G., & Noussan, M. (2019) · Energies · doi:10.3390/en12030456 · Cited by 35 · see citing works
Safer If Connected? Mobile Technology and Intimate Partner Violence
Pesando, L. M. (2022) · Demography · doi:10.1215/00703370-9774978 · Cited by 35 · see citing works
Bluhm, R., & McCord, G. C. (2022) · Remote Sensing · doi:10.3390/rs14051190 · Cited by 31 · see citing works
Crop prices and deforestation in the tropics
Berman, N., Couttenier, M., Leblois, A., & Soubeyran, R. (2023) · Journal of Environmental Economics and Management · doi:10.1016/j.jeem.2023.102819 · Cited by 30 · see citing works
Coupling coordination relationships between air pollutant concentrations and emissions in China
Wu, Q., Hong, S., Yang, L., Mu, H., Huang, C., Niu, X., Zhong, Y., Yi, J., & He, C. (2023) · Atmospheric Pollution Research · doi:10.1016/j.apr.2023.101678 · Cited by 30 · see citing works
Estimating local agricultural gross domestic product (AgGDP) across the world
Ru, Y., Blankespoor, B. A., Wood‐Sichra, U., Thomas, T. S., You, L., & Kalvelagen, E. (2023) · Earth system science data · doi:10.5194/essd-15-1357-2023 · Cited by 32 · see citing works
Nighttime light extent and intensity explain the dynamics of human activity in coastal zones
Mokhtari, Z., Bergantino, A. S., Intini, M., Elia, M., Buongiorno, A., Giannico, V., Sanesi, G., & Lafortezza, R. (2025) · Scientific Reports · doi:10.1038/s41598-025-85917-z · Cited by 28 · see citing works
Oughton, E. J. (2022) · Telematics and Informatics · doi:10.1016/j.tele.2022.101908 · Cited by 29 · see citing works
Ceballos, F. C., Hazelhurst, S., Clark, D. W., Agongo, G., Asiki, G., Boua, P. R., Gómez-Olivé, F. X., Mashinya, F., Norris, S. A., Wilson, J. F., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-19595-y · Cited by 27 · see citing works
Baehr, C. J., BenYishay, A., & Parks, B. C. (2021) · Journal of the Association of Environmental and Resource Economists · doi:10.1086/712800 · Cited by 27 · see citing works
Mobile Money and Economic Activity: Evidence from Kenya★
Fabregas, R., & Yokossi, T. (2022) · World Bank Economic Review · doi:10.1093/wber/lhac007 · Cited by 21 · see citing works
Potential of Using Night-Time Light to Proxy Social Indicators for Sustainable Development
Andries, A., Morse, S., Murphy, R., Sadhukhan, J., Martínez-Hernández, E., Amezcua‐Allieri, M. A., & Aburto, J. (2023) · Remote Sensing · doi:10.3390/rs15051209 · Cited by 24 · see citing works
Watson, C. S., Elliott, J. R., Córdova, M., Menoscal, J., & Bonilla‐Bedoya, S. (2023) · International Journal of Remote Sensing · doi:10.1080/01431161.2023.2205983 · Cited by 24 · see citing works
Ge, E., Gao, J., Ren, Z., Liu, X., Luo, M., Zhong, J., Fei, F., Chen, B., Wang, X., Wei, X., et al. (2021) · The Science of The Total Environment · doi:10.1016/j.scitotenv.2021.145422 · Cited by 24 · see citing works
Wang, J., Zhang, J., Gong, L., Li, Q., & Zhou, D. (2018) · Natural hazards and earth system sciences · doi:10.5194/nhess-18-3253-2018 · Cited by 23 · see citing works
Women legislators and economic performance
Baskaran, T., Bhalotra, S. R., Min, B., & Uppal, Y. (2018) · Working Paper Series · doi:10.35188/unu-wider/2018/489-6 · Cited by 23 · see citing works
Daxecker, U., & Prins, B. (2021) · doi:10.1093/oso/9780190097394.001.0001 · Cited by 22 · see citing works
Mallick, J., & Alqadhi, S. D. (2024) · Urban Climate · doi:10.1016/j.uclim.2024.102259 · Cited by 22 · see citing works
Andersson, M., Hall, O., & Bustos, M. F. A. (2019) · ISPRS International Journal of Geo-Information · doi:10.3390/ijgi8110498 · Cited by 22 · see citing works
Spatial variation in lymphatic filariasis risk factors of hotspot zones in Ghana
Kwarteng, E. V. S., Andam‐Akorful, S. A., Kwarteng, A., Asare, D.-C. B. M., Quaye‐Ballard, J. A., Osei, F., & Duker, A. A. (2021) · BMC Public Health · doi:10.1186/s12889-021-10234-9 · Cited by 21 · see citing works
Zhang, Z., & Liu, Y. (2022) · Sustainability · doi:10.3390/su14159359 · Cited by 21 · see citing works
Local Economic Growth and Infant Mortality
Kammerlander, A., & Schulze, G. G. (2021) · Journal of Health Economics · doi:10.1016/j.jhealeco.2022.102699 · Cited by 21 · see citing works
Τζιώκας, Ν., Zhang, C., Drolias, G. C., & Atkinson, P. M. (2023) · International Journal of Applied Earth Observation and Geoinformation · doi:10.1016/j.jag.2023.103395 · Cited by 20 · see citing works
Free secondary education policy and education attainment
Stenzel, A. G., Kwadwo, V. O., & Vincent, R. C. (2024) · International Journal of Educational Development · doi:10.1016/j.ijedudev.2024.103021 · Cited by 19 · see citing works
Predicting Livelihood Indicators from Community-Generated Street-Level Imagery
Lee, J., Grosz, D., Uzkent, B., Zeng, S., Burke, M., Lobell, D. B., & Ermon, S. (2021) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v35i1.16101 · Cited by 21 · see citing works
Water Scarcity and Local Economic Activity: Spatial Spillovers and the Role of Irrigation
Marbler, A. (2023) · Journal of Environmental Economics and Management · doi:10.1016/j.jeem.2024.102931 · Cited by 16 · see citing works
China's local-level monthly residential electricity power consumption monitoring
Du, M., Ruan, J., Zhang, L., Niu, M., Zhang, Z., Xia, L., Qian, S., & Chen, C. (2024) · Applied Energy · doi:10.1016/j.apenergy.2024.122658 · Cited by 16 · see citing works
Using satellite data and deep learning to estimate educational outcomes in data-sparse environments
Runfola, D. M., Stefanidis, A., & Baier, H. (2021) · Remote Sensing Letters · doi:10.1080/2150704x.2021.1987575 · Cited by 15 · see citing works
Assessing regional economy in North Korea using nighttime light
Kim, D. (2022) · Asia and the Global Economy · doi:10.1016/j.aglobe.2022.100046 · Cited by 15 · see citing works
The impact of educated leaders on economic development: Evidence from India
Jain, C., Kashyap, S., Lahoti, R., & Sahoo, S. (2023) · Journal of Comparative Economics · doi:10.1016/j.jce.2023.05.001 · Cited by 15 · see citing works
The impact of ESG advantages on the economic development of neighboring regions
Huang, C., Hao, S., & Ma, L. (2025) · Energy Economics · doi:10.1016/j.eneco.2025.108431 · Cited by 16 · see citing works
Carlin, R. E., Hellwig, T. T., Love, G. J., Martínez‐Gallardo, C., & Singer, M. (2021) · Comparative Political Studies · doi:10.1177/0010414021989758 · Cited by 15 · see citing works
Institutions and the resource curse: New insights from causal machine learning
Hodler, R., Lechner, M., & Raschky, P. A. (2023) · PLoS ONE · doi:10.1371/journal.pone.0284968 · Cited by 14 · see citing works
Self-citationChina–USA: multiple vector OF “tradE war”
Mikheev, V. V., & Lukonin, S. (2019) · World Economy and International Relations · doi:10.20542/0131-2227-2019-63-5-57-66 · Cited by 15 · see citing works
Panić, M., Drobnjakovic, М., Stanojević, G. B., Kanazir, V. K., & Дољак, Д. (2022) · Journal of the Geographical Institute Jovan Cvijic SASA · doi:10.2298/ijgi2201051p · Cited by 13 · see citing works
Backer, D., & Billing, T. (2023) · World Development · doi:10.1016/j.worlddev.2023.106484 · Cited by 13 · see citing works
What does the population in Niger think about a military government?
Tuki, D. (2024) · Democratization · doi:10.1080/13510347.2024.2341314 · Cited by 13 · see citing works
Mining in Africa: Are local communities paying the price of the global energy transition?
Lapeyronie, H., & Szedlacsek, E. (2024) · The Extractive Industries and Society · doi:10.1016/j.exis.2024.101565 · Cited by 13 · see citing works
Predicting cell phone adoption metrics using machine learning and satellite imagery
Oughton, E. J., & Mathur, J. (2021) · Telematics and Informatics · doi:10.1016/j.tele.2021.101622 · Cited by 13 · see citing works
Detection of the Seasonally Activated Rural Areas
Drobnjakovic, М., Panić, M., Stanojević, G. B., Дољак, Д., & Kanazir, V. K. (2022) · Sustainability · doi:10.3390/su14031604 · Cited by 13 · see citing works
Using Neural Networks to Predict Micro-Spatial Economic Growth
Khachiyan, A., Thomas, A. H., Zhou, H., Hanson, G., Cloninger, A., Rosing, T., & Khandelwal, A. K. (2021) · National Bureau of Economic Research · doi:10.3386/w29569 · Cited by 13 · see citing works
The economic efficiency of aid targeting
BenYishay, A., DiLorenzo, M. D., & Dolan, C. B. (2022) · World Development · doi:10.1016/j.worlddev.2022.106062 · Cited by 12 · see citing works
A water pricing model for urban areas based on water accessibility
Xu, L., Tu, Z., Yang, J. B., Zhang, C., Chen, X., Gu, Y., & Yu, G. (2022) · Journal of Environmental Management · doi:10.1016/j.jenvman.2022.116880 · Cited by 12 · see citing works
Biswas, A., Tucker, J., & Bauhoff, S. (2023) · BMJ Global Health · doi:10.1136/bmjgh-2023-012836 · Cited by 12 · see citing works
Rapid Socioeconomic Growth in Southeast Asia: Evidence From Nighttime Light Observations
Cui, Y., Zhao, R., Mi, Z., Wang, L., Yuan, Y., Duan, X., & Shi, K. (2024) · IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing · doi:10.1109/jstars.2024.3365177 · Cited by 12 · see citing works
Land systems’ asymmetries across transnational ecoregions in South America
Rodríguez, M. P., Gasparri, I., Zarbá, L., Aráoz, E., & Grau, H. R. (2021) · Sustainability Science · doi:10.1007/s11625-021-00967-2 · Cited by 12 · see citing works
Political instability and households’ investment behavior: Evidence from Burkina Faso
Büttner, N., Grimm, M., & Soubeiga, S. (2021) · Journal of comparative economics (Print) · doi:10.1016/j.jce.2021.11.003 · Cited by 7 · see citing works
Burdett, E. M., Muriel, R., Morandini, V., Kolnegari, M., & Ferrer, M. (2022) · Diversity · doi:10.3390/d14110984 · Cited by 12 · see citing works
Mihaylova, I. (2023) · World Development · doi:10.1016/j.worlddev.2022.106176 · Cited by 11 · see citing works
Fazia, C., Nahiduzzaman, K. M., Al-Ramadan, B. M., Aldosary, A. S., & Moraci, F. (2024) · Land · doi:10.3390/land13030323 · Cited by 11 · see citing works
Murshed, S., Griffin, A. L., Islam, M. A., Oliver, T. S. N., Wang, X. H., & Paull, D. J. (2024) · International Journal of Disaster Risk Reduction · doi:10.1016/j.ijdrr.2024.104832 · Cited by 11 · see citing works
Shedding light on development: Leveraging the new nightlights data to measure economic progress
Jhamb, P., Ferreira, S., Stephens, P. R., Sundaram, M., & Wilson, J. (2025) · PLoS ONE · doi:10.1371/journal.pone.0318482 · Cited by 11 · see citing works
Economic development, weather shocks and child marriage in South Asia: A machine learning approach
Dietrich, S., Meysonnat, A., Rosales, F., Cebotari, V., & Gassmann, F. (2022) · PLoS ONE · doi:10.1371/journal.pone.0271373 · Cited by 11 · see citing works
Varughese, A. R., & Bairagya, I. (2021) · Structural Change and Economic Dynamics · doi:10.1016/j.strueco.2021.09.015 · Cited by 11 · see citing works
Harris, J. A., & Posner, D. (2022) · World Development · doi:10.1016/j.worlddev.2022.105845 · Cited by 11 · see citing works
Living in darkness: rural poverty in Venezuela
Maldonado, L. (2023) · Journal of Applied Economics · doi:10.1080/15140326.2023.2168464 · Cited by 11 · see citing works
Oda, T., Román, M. O., Wang, Z., Stokes, E. C., Sun, Q., Shrestha, R., Feng, S., Lauvaux, T., Bun, R., Maksyutov, S. S., et al. (2021) · doi:10.1002/9781119625865.ch16 · Cited by 11 · see citing works
Htet, N. L., Kongprawechnon, W., Thajchayapong, S., & Isshiki, T. (2021) · International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON) · doi:10.1109/ecti-con51831.2021.9454768 · Cited by 10 · see citing works
Spatial interdependence and spillovers of fiscal grants in Benin: Static and dynamic diffusions
Vincent, R. C., & Kwadwo, V. O. (2022) · World Development · doi:10.1016/j.worlddev.2022.106006 · Cited by 10 · see citing works
Did Covid-19 lockdown positively affect the urban environment and UN- Sustainable Development Goals?
Nigam, R., Tripathi, G., Priya, T., Luis, A. J., Vaz, E., Kumar, S., Shakya, A., Damásio, B., & Kotha, M. (2022) · PLoS ONE · doi:10.1371/journal.pone.0274621 · Cited by 10 · see citing works
Wu, W., Chen, D., Ruan, X., Wu, G., Deng, X., Lawrence, W. R., Lin, X., Li, Z., Wang, Y., Lin, Z., et al. (2024) · Journal of Advanced Research · doi:10.1016/j.jare.2024.05.025 · Cited by 10 · see citing works
The Fertility Transition in Sub-Saharan Africa: The Role of Structural Change
Büttner, N., Grimm, M., Günther, I., Harttgen, K., & Klasen, S. (2024) · Demography · doi:10.1215/00703370-11587285 · Cited by 10 · see citing works
Määttä, I., & Leßmann, C. (2019) · Remote Sensing · doi:10.3390/rs11192194 · Cited by 10 · see citing works
The Process of Revolutionary Protest: Development and Democracy in the Tunisian Revolution
Barrie, C. (2023) · Perspectives on Politics · doi:10.1017/s1537592723002062 · Cited by 10 · see citing works
Artisanal mining in Africa. Green for Gold?
Girard, V., Molina-Millán, T., & Vic, G. (2025) · The Economic Journal · doi:10.1093/ej/ueaf058 · Cited by 9 · see citing works
A model to identify causality for geographic patterns
Zhang, Z., & Wang, J. (2025) · International Journal of Geographical Information Systems · doi:10.1080/13658816.2025.2581207 · Cited by 9 · see citing works
Using Neural Networks to Predict Microspatial Economic Growth
Khachiyan, A., Thomas, A. H., Zhou, H., Hanson, G., Cloninger, A., Rosing, T., & Khandelwal, A. K. (2022) · American Economic Review Insights · doi:10.1257/aeri.20210422 · Cited by 9 · see citing works
Sun, Y., Xie, J., Wang, Y., Chan, T. O., & Sun, Z. (2023) · Geo-spatial Information Science · doi:10.1080/10095020.2023.2273826 · Cited by 9 · see citing works
Toharudin, T., Caraka, R. E., Kaban, P. A., Supardi, K., Kurniawan, R., Kim, Y., Mufti, S. A., Gio, P. U., Sakti, A. D., Chen, R.-C., et al. (2024) · IEEE Access · doi:10.1109/access.2024.3355963 · Cited by 9 · see citing works
Nighttime lights and wealth in very small areas:
Määttä, I., Ferreira, T., & Leßmann, C. (2021) · Review of Regional Research · doi:10.1007/s10037-021-00159-6 · Cited by 9 · see citing works
- Authors
- Bruederle, A., & Hodler, R.
- Affiliations
- University of St.Gallen (CH)
- Corresponding author
- Hodler, Roland
- Venue
- PLOS ONE
- Publisher
- Public Library of Science (PLoS)
- Published
- 2018-09-05
- Volume
- 13
- Issue
- 9
- Pages
- e0202231
- ISSN
- 1932-6203 (ISSN-L)
- PMC
- PMC6124706
- OpenAlex
- W2742305379
- Cited by
- 259
- References
- 36
- Citations by year
- 2026: 19 · 2025: 31 · 2024: 37 · 2023: 36 · 2022: 40 · 2021: 58 · 2020: 15 · 2019: 16 · 2018: 6 · 2017: 1
- FWCI
- 13.90
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- PLoS ONE (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Alexandria (UniSG) (University of St.Gallen) (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Figshare (submittedVersion, cc-by)
- Funders
- Universität St. Gallen (Basic Research Grant)
- Topics
- Physical Sciences › Environmental Science › Global and Planetary Change › Impact of Light on Environment and Health
- Social Sciences › Transportation › Human Mobility and Location-Based Analysis
- Social Sciences › Demography › Culture, Economy, and Development Studies
- Keywords
- nighttime lights, human development, proxy indicators, household wealth, subnational regions, developing countries, African countries, satellite remote sensing, local economic development
- MeSH terms
- Africa, Algorithms, Developing Countries, Geography, Humans, Lighting, Surveys and Questionnaires, Socioeconomic Factors, Time Factors, Models, Economic
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review