气候变化与国际粮食价格之间的联系:稳健的长程交叉相关性和滑动窗口法的变滞后转移熵证据

IF 3 2区 计算机科学 Q1 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS
Zouhaier Dhifaoui
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引用次数: 0

摘要

随着国家的进步,气候变化对粮食价格的影响越来越大。虽然气候变化对主要农产品产量的影响已得到广泛认可,但其对粮食价格的具体影响仍不确定。本研究深入探讨了北大西洋涛动指数(NAO)这一成熟的气候指标对全球粮食价格的影响。为此,采用了稳健双变量赫斯特指数(稳健 bHe)。该研究采用了一种跨越不同时间尺度的滑动窗口方法,绘制出该系数的彩色地图,呈现出一个随时间变化的版本。此外,还利用滑动窗口法的可变滞后转移熵来判别西北农林业大学指数与国际粮食价格之间的因果关系。研究结果表明,在短期和长期内,NAO 指数的大幅上升与各种国际粮食价格的显著上升相关。此外,可变滞后转移熵也证实了西北农林业大学指数在影响国际粮食价格方面的因果作用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Connection between climatic change and international food prices: evidence from robust long-range cross-correlation and variable-lag transfer entropy with sliding windows approach

Connection between climatic change and international food prices: evidence from robust long-range cross-correlation and variable-lag transfer entropy with sliding windows approach

As nations progress, the impact of climate change on food prices becomes increasingly substantial. While the influence of climate change on the yields of major agricultural products is widely recognized, its specific effect on food prices remains uncertain. This study delves into the impact of the North Atlantic Oscillation (NAO) index, a well-established climate indicator, on global food prices. To accomplish this, a robust bivariate Hurst exponent (robust bHe) is applied. The study employs a sliding windows approach across various time scales to produce a color map of this coefficient, presenting a time-varying version. Furthermore, variable-lag transfer entropy with a sliding windows approach is utilized to discern causal relationships between the NAO index and international food prices. The findings reveal that significant increases in the NAO index are correlated with noteworthy upswings in various international food prices over both short and long-term periods. Additionally, variable-lag transfer entropy confirms the causal role of the NAO index in influencing international food prices.

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来源期刊
EPJ Data Science
EPJ Data Science MATHEMATICS, INTERDISCIPLINARY APPLICATIONS -
CiteScore
6.10
自引率
5.60%
发文量
53
审稿时长
13 weeks
期刊介绍: EPJ Data Science covers a broad range of research areas and applications and particularly encourages contributions from techno-socio-economic systems, where it comprises those research lines that now regard the digital “tracks” of human beings as first-order objects for scientific investigation. Topics include, but are not limited to, human behavior, social interaction (including animal societies), economic and financial systems, management and business networks, socio-technical infrastructure, health and environmental systems, the science of science, as well as general risk and crisis scenario forecasting up to and including policy advice.
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