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Erschienen in: Population and Environment 4/2023

01.12.2023 | Original Paper

Temperature effects on rural household outmigration: Evidence from China

verfasst von: Yefei Sun

Erschienen in: Population and Environment | Ausgabe 4/2023

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Abstract

Changes in temperature extremes under climate change are expected to affect outmigration in rural areas through an agricultural mechanism. This study examines the effect of rising temperatures on rural outmigration in Jiangxi Province, China, a cold region where agricultural livelihoods predominate. The study contributes novel results by using large-scale household smart meter data to identify rural household outmigration. These data are combined with temperature data from meteorological stations to reveal a nonlinear effect of temperature on rural outmigration through an agricultural livelihood mechanism. The study projects the influence of rising temperatures on rural outmigration based on two representative concentration pathways (RCPs): RCP4.5 and RCP8.5. The results of the study show that extremely low temperatures significantly increase rural outmigration in Jiangxi Province, China, a rice-growing region. Moreover, projections show that warmer temperatures will improve rice yields and diminish outmigration. According to the medium-term (2041–2060) and long-term (2061–2080) prediction results, rural household outmigration will decrease by 0.55–1.40% and 1.23–2.96%, respectively. These findings contribute to research showing that rising global temperatures affect rural areas in cold regions by improving crop yields and diminishing outmigration.

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Fußnoten
1
One US dollar is approximately equivalent to 7 yuan.
 
2
These 21 temperature prediction models were developed by research institutes in different countries around the world. The 21 temperature models are as follows: the ACCESS1-0 model, bcc-csm1-1 model, BNU-ESM model, CanESM2 model, CCSM4 model, CESM1-BGC model, CNRM-CM5 model, CSIRO-Mk3-6–0 model, GFDL-CM3 model, GFDL-ESM2G model, GFDL-ESM2M model, inmcm4 model, IPSL-CM5A-LR model, IPSL-CM5A-MR model, MIROC5 model, MIROC-ESM model, MIROC-ESM-CHEM model, MPI-ESM-LR model, MPI-ESM-MR model, MRI-CGCM3 model, and NorESM1-M model.
 
3
Since the number of days per month is between 28 and 31 days, we normalize the temperature bins to ensure that the sum of the temperature bins equals 30. These results are reported in the “Robustness check” section.
 
4
According to the seemingly unrelated regression, the p value is 0.0020; thus, the group regression results are comparable.
 
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Metadaten
Titel
Temperature effects on rural household outmigration: Evidence from China
verfasst von
Yefei Sun
Publikationsdatum
01.12.2023
Verlag
Springer Netherlands
Erschienen in
Population and Environment / Ausgabe 4/2023
Print ISSN: 0199-0039
Elektronische ISSN: 1573-7810
DOI
https://doi.org/10.1007/s11111-023-00441-4

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