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Local Climate Sensitivity: A Statistical Approach for a Spatially Heterogeneous Planet

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Climate sensitivity relates total radiative forcing from anthropogenic and other sources to global mean temperature, and it depends on both changes in net heat transports and changes in the spatial distribution of temperature anomalies. An energy balance model, an easily implemented statistical methodology, and a supplementary inferential procedure are proposed to estimate local climate sensitivity using the historical record and to assess the contribution to overall climate sensitivity. Results are roughly comparable with extant findings from simulations using more complicated models. In particular, areas over ocean tend to import energy, they are relatively more sensitive to forcings, but they warm more slowly than those over land. Increases in the variation of predicted local temperature anomalies are estimated to be proportional to increases in forcings, and economic implications are discussed.

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  • J. Isaac Miller, 2017. "Local Climate Sensitivity: A Statistical Approach for a Spatially Heterogeneous Planet," Working Papers 1702, Department of Economics, University of Missouri.
  • Handle: RePEc:umc:wpaper:1702
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    4. Park, Joon Y. & Shin, Kwanho & Whang, Yoon-Jae, 2010. "A semiparametric cointegrating regression: Investigating the effects of age distributions on consumption and saving," Journal of Econometrics, Elsevier, vol. 157(1), pages 165-178, July.
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    7. Felix Pretis, 2015. "Econometric Models of Climate Systems: The Equivalence of Two-Component Energy Balance Models and Cointegrated VARs," Economics Series Working Papers 750, University of Oxford, Department of Economics.
    8. Brock, William A. & Engström, Gustav & Grass, Dieter & Xepapadeas, Anastasios, 2013. "Energy balance climate models and general equilibrium optimal mitigation policies," Journal of Economic Dynamics and Control, Elsevier, vol. 37(12), pages 2371-2396.
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    Cited by:

    1. Kyungsik Nam, 2021. "Nonlinear Cointegrating Regression of the Earth’s Surface Mean Temperature Anomalies on Total Radiative Forcing," Econometrics, MDPI, vol. 9(1), pages 1-25, February.

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    More about this item

    Keywords

    local climate sensitivity; energy balance model; historical temperature anomaly distributions; partially linear semiparametric model;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming

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