How well do gridded population estimates proxy for actual population changes? Evidence from four gridded data products and three censuses for China

Xiaoxuan Zhang () and John Gibson
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Xiaoxuan Zhang: University of Waikato

Working Papers in Economics from University of Waikato

Abstract: High-resolution gridded population estimates are increasingly used to support public health, disaster, and socio-economic research. These gridded data allow phenomena to be studied at a finer spatial scale than the usual survey or administrative data (spatialization) and with higher frequency than typical decadal census data allow (temporal interpolation). However, little is known about how accurately these gridded data follow actual changes in population. Therefore, we use China's census data for 2000, 2010, and 2020 to test predictive accuracy of four popular gridded population data products, conducting our tests at three spatial levels (county/district, prefectural city, and province). The gridded population data are accurate cross-sectional predictors at all three spatial levels, with less than five percent of variation unexplained. They far less accurately predict temporal changes in population, especially for disaggregated spatial units (counties and districts) where just one fifth of the variation in population changes is predicted by the gridded data. Predictive performance of gridded data for population changes has fallen substantially in the last decade. We illustrate how these inaccurate predictions could distort analyses that examine trends in spatial inequality. Overall, our results suggest that caution is required in using these gridded data products as proxies for the actual changes in local population.

Keywords: gridded population datal; cross-sectional; time-series; Census; China (search for similar items in EconPapers)
JEL-codes: R12 (search for similar items in EconPapers)
Pages: 25 pages
Date: 2024-09-17
New Economics Papers: this item is included in nep-cna, nep-geo and nep-ure
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