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      Gridded global datasets for Gross Domestic Product and Human Development Index over 1990–2015

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          Abstract

          An increasing amount of high-resolution global spatial data are available, and used for various assessments. However, key economic and human development indicators are still mainly provided only at national level, and downscaled by users for gridded spatial analyses. Instead, it would be beneficial to adopt data for sub-national administrative units where available, supplemented by national data where necessary. To this end, we present gap-filled multiannual datasets in gridded form for Gross Domestic Product (GDP) and Human Development Index (HDI). To provide a consistent product over time and space, the sub-national data were only used indirectly, scaling the reported national value and thus, remaining representative of the official statistics. This resulted in annual gridded datasets for GDP per capita (PPP), total GDP (PPP), and HDI, for the whole world at 5 arc-min resolution for the 25-year period of 1990–2015. Additionally, total GDP (PPP) is provided with 30 arc-sec resolution for three time steps (1990, 2000, 2015).

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          Most cited references31

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          MIRCA2000-Global monthly irrigated and rainfed crop areas around the year 2000: A new high-resolution data set for agricultural and hydrological modeling

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            Anthropogenic transformation of the biomes, 1700 to 2000

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              Using luminosity data as a proxy for economic statistics

              A pervasive issue in social and environmental research has been how to improve the quality of socioeconomic data in developing countries. Given the shortcomings of standard sources, the present study examines luminosity (measures of nighttime lights visible from space) as a proxy for standard measures of output (gross domestic product). We compare output and luminosity at the country level and at the 1° latitude × 1° longitude grid-cell level for the period 1992-2008. We find that luminosity has informational value for countries with low-quality statistical systems, particularly for those countries with no recent population or economic censuses.
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                Author and article information

                Journal
                Sci Data
                Sci Data
                Scientific Data
                Nature Publishing Group
                2052-4463
                06 February 2018
                2018
                : 5
                : 180004
                Affiliations
                [1 ]Water & Development Research Group, Aalto University , Tietotie 1E, 02150 Espoo, Finland
                Author notes
                [a ] M.K. (email: matti.kummu@ 123456aalto.fi ).
                []

                M.K. designed and performed the data analysis; all authors designed error analysis and M.K. performed that; M.K. wrote the paper with contribution from J.H.A.G. and M.T.; M.T. took care of the data opening.

                Author information
                http://orcid.org/0000-0001-5096-0163
                http://orcid.org/0000-0001-6854-8708
                Article
                sdata20184
                10.1038/sdata.2018.4
                5800392
                29406518
                e18ae9ee-a3ba-4aef-baf7-9a1920adae43
                Copyright © 2018, The Author(s)

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/ applies to the metadata files made available in this article.

                History
                : 16 May 2017
                : 08 December 2017
                Categories
                Data Descriptor

                economics,developing world,environmental social sciences

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