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2020
- handle: 10670/1.8m05s6
- halshs: halshs-02726466
- doi: 10.2139/ssrn.3615328
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info:eu-repo/semantics/altIdentifier/doi/10.2139/ssrn.3615328
info:eu-repo/semantics/OpenAccess
Mots-clés
Climate change Nomadic migration Conflicts Historical China Threshold Regression Non linearity Copula Cau Climate change C - Mathematical and Quantitative Methods/C.C2 - Single Equation Models • Single Variables/C.C2.C22 - Time-Series Models • Dynamic Quantile Regressions • Dynamic Treatment Effect Models • Diffusion Processes C - Mathematical and Quantitative Methods/C.C5 - Econometric Modeling/C.C5.C53 - Forecasting and Prediction Methods • Simulation Methods E - Macroeconomics and Monetary Economics/E.E3 - Prices, Business Fluctuations, and Cycles/E.E3.E32 - Business Fluctuations • Cycles F - International Economics/F.F0 - General/F.F0.F00 - General Q - Agricultural and Natural Resource Economics • Environmental and Ecological Economics/Q.Q0 - General/Q.Q0.Q00 - General -fin] -fin]/Computational Finance [q-fin.CP] -fin]/Pricing of Securities [q-fin.PR] -fin]/Statistical Finance [q-fin.ST]Sujets proches
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Stéphane Goutte et al., « Climate and nomadic migration in a nonlinear world : evidence of the Historical China », HAL-SHS : économie et finance, ID : 10.2139/ssrn.3615328
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Résumé
This paper deals with climate change and nomadic migration relationships at a long term and wide geographical scale using a statistical approach in the vein of Bai and Kung (2011). More precisely, it presents a reassessment of these relationships in a nonlinear world using threshold regressions, time varying-copula and nonlinear causality tests. The large amount of historical records in China enables us to re-interpret the link between climate and historical social dynamics (Hsiang et al., 2013) through different regimes of temperatures and precipitations.