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

被引:0
作者
Dhifaoui, Zouhaier [1 ,2 ]
机构
[1] Univ Sousse, Fac Med Sousse, Dept Family & Community Med, Mouhamed Karoui St, Sousse 4002, Tunisia
[2] Univ Paris 01, SAMM, 90 Rue Tolbiac, F-75634 Paris 13, France
关键词
Food security; Robust long-range cross-correlation coefficient; Bivariate Hurst exponent; Variable-lag transfer entropy; NAO index; International food prices; NORTH-ATLANTIC OSCILLATION; ESTIMATING INVARIANTS; UNIT ROOTS; VARIABILITY; YIELDS; NOISE; TEMPERATURE; VOLATILITY; OUTLIERS; MAIZE;
D O I
10.1140/epjds/s13688-024-00482-1
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
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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页数:23
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共 92 条
  • [1] Identifying Linear Models in Multi-Resolution Population Data Using Minimum Description Length Principle to Predict Household Income
    Amornbunchornvej, Chainarong
    Surasvadi, Navaporn
    Plangprasopchok, Anon
    Thajchayapong, Suttipong
    [J]. ACM TRANSACTIONS ON KNOWLEDGE DISCOVERY FROM DATA, 2021, 15 (02)
  • [2] Synchronous crop failures and climate-forced production variability
    Anderson, W. B.
    Seager, R.
    Baethgen, W.
    Cane, M.
    You, L.
    [J]. SCIENCE ADVANCES, 2019, 5 (07):
  • [3] [Anonymous], 2022, UN Report: Global hunger numbers rose to as many as 828 million in 2021
  • [4] Impacts of the COVID-19 pandemic on food prices: Evidence from storable and perishable commodities in India
    Bairagi, Subir
    Mishra, Ashok K.
    Mottaleb, Khondoker A.
    [J]. PLOS ONE, 2022, 17 (03):
  • [5] The impact of climate change on food crop productivity, food prices and food security in South Asia
    Bandara, Jayatilleke S.
    Cai, Yiyong
    [J]. ECONOMIC ANALYSIS AND POLICY, 2014, 44 (04) : 451 - 465
  • [6] Granger Causality and Transfer Entropy Are Equivalent for Gaussian Variables
    Barnett, Lionel
    Barrett, Adam B.
    Seth, Anil K.
    [J]. PHYSICAL REVIEW LETTERS, 2009, 103 (23)
  • [7] A review of technology and policy deep decarbonization pathway options for making energy-intensive industry production consistent with the Paris Agreement
    Bataille, Chris
    Ahman, Max
    Neuhoff, Karsten
    Nilsson, Lars J.
    Fischedick, Manfred
    Lechtenboehmer, Stefan
    Solano-Rodriquez, Baltazar
    Denis-Ryan, Amandine
    Stiebert, Seton
    Waisman, Henri
    Sartor, Oliver
    Rahbar, Shahrzad
    [J]. JOURNAL OF CLEANER PRODUCTION, 2018, 187 : 960 - 973
  • [8] Beckman J., 2021, Q Open, V1, DOI 10.1093/qopen/qoab005
  • [9] Implications of the Russia-Ukraine war for global food security
    Behnassi, Mohamed
    El Haiba, Mahjoub
    [J]. NATURE HUMAN BEHAVIOUR, 2022, 6 (06) : 754 - 755
  • [10] BERAN J., 1994, Monographs on Statistics and Applied Probability, V61