湿能量平衡模型中的极地放大效应:估算和检验的结构计量经济学方法

IF 9.9 3区 经济学 Q1 ECONOMICS Journal of Econometrics Pub Date : 2024-10-01 DOI:10.1016/j.jeconom.2024.105885
William A. Brock , J. Isaac Miller
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引用次数: 0

摘要

大气湿度和热量的极地传输在极地纬度每升高一度全球变暖的放大过程中起着重要作用,这种现象被称为极地放大(PA)。我们推导了一个时间序列计量经济学框架,该框架使用了一个方程系统,该方程系统具有误差修正机制,可限制各方程的估算,并采用了一种识别策略来恢复湿能量平衡模型(MEBM)的参数,该模型与近期气候科学文献中的模型类似。这一框架使气候计量经济学家能够估算和预测纬度带的温度上升,因为累积排放量持续增长,并考虑到克劳修斯-克拉皮隆方程提出的大气湿度增加的影响,这是气候变化空间非均匀性的驱动因素。非均匀性之所以重要,有两个原因:气候变化会带来不平等的经济后果,需要更好地理解;极地纬度温度的放大可能会引发不可逆转的气候临界点,而这些地区的气候临界点不成比例。
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Polar amplification in a moist energy balance model: A structural econometric approach to estimation and testing
Poleward transport of atmospheric moisture and heat play major roles in the magnification of warming in poleward latitudes per degree of global warming, a phenomenon known as polar amplification (PA). We derive a time series econometric framework using a system of equations that have error-correction mechanisms restricted across equations to estimate and an identification strategy to recover the parameters of a moist energy balance model (MEBM) similar to those in the recent climate science literature. This framework enables the climate econometrician to estimate and forecast temperature rise in latitude belts as cumulative emissions continue to grow as well as account for effects of increases in atmospheric moisture suggested by the Clausius–Clapeyron equation, a driver of spatial non-uniformity in climate change. Non-uniformity is important for two reasons: climate change has unequal economic consequences that need to be better understood and amplification of temperatures in polar latitudes may trigger irreversible climate tipping points, which are disproportionately located in those regions.
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来源期刊
Journal of Econometrics
Journal of Econometrics 社会科学-数学跨学科应用
CiteScore
8.60
自引率
1.60%
发文量
220
审稿时长
3-8 weeks
期刊介绍: The Journal of Econometrics serves as an outlet for important, high quality, new research in both theoretical and applied econometrics. The scope of the Journal includes papers dealing with identification, estimation, testing, decision, and prediction issues encountered in economic research. Classical Bayesian statistics, and machine learning methods, are decidedly within the range of the Journal''s interests. The Annals of Econometrics is a supplement to the Journal of Econometrics.
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