极端天气事件和高哥伦比亚食品价格:非平稳极值方法1

IF 4.5 3区 经济学 Q1 AGRICULTURAL ECONOMICS & POLICY
Luis Fernando Melo-Velandia, Camilo Andrés Orozco-Vanegas, Daniel Parra-Amado
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引用次数: 2

摘要

鉴于气候变化的重要性及其在极端天气事件下的严重程度增加,我们分析了1985年至2020年期间哥伦比亚食品价格高企的主要驱动因素,重点分析了强厄尔尼诺Niño等极端天气冲击。我们估计了哥伦比亚食品价格的非平稳极值模型。我们的研究结果表明,与加工食品相比,易腐食品更容易受到极端天气条件的影响。事实上,极低的降水量只能解释易腐食品的高价格。与高降雨量(雨季)相比,低降雨量(旱季)的易腐食品价格高企的风险要大得多。这种风险逐渐导致易腐食品价格上涨。它是非线性的,也明显大于与美元-哥伦比亚比索汇率和燃料价格变化有关的风险。这些协变量也解释了易腐食品和加工食品的高价格。最后,我们发现与1988年和2016年最强El Niño相关的事件预计每50年重现一次。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Extreme weather events and high Colombian food prices: A non-stationary extreme value approach1

Given the importance of climate change and the increase of its severity under extreme weather events, we analyze the main drivers of high food prices in Colombia between 1985 and 2020 focusing on extreme weather shocks like a strong El Niño. We estimate a non-stationary extreme value model for Colombian food prices. Our findings suggest that perishable foods are more exposed to extreme weather conditions in comparison to processed foods. In fact, an extremely low precipitation level explains only high prices in perishable foods. The risk of high perishable food prices is significantly larger for low rainfall levels (dry seasons) compared to high precipitation levels (rainy seasons). This risk gradually results in higher perishable food prices. It is nonlinear and is also significantly larger than the risk related to changes in the US dollar-Colombian peso exchange rate and fuel prices. Those covariates also explain high prices for both perishable and processed foods. Finally, we find that the events associated with the strongest El Niño in 1988 and 2016 are expected to reoccur once every 50 years.

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来源期刊
Agricultural Economics
Agricultural Economics 管理科学-农业经济与政策
CiteScore
7.30
自引率
4.90%
发文量
62
审稿时长
3 months
期刊介绍: Agricultural Economics aims to disseminate the most important research results and policy analyses in our discipline, from all regions of the world. Topical coverage ranges from consumption and nutrition to land use and the environment, at every scale of analysis from households to markets and the macro-economy. Applicable methodologies include econometric estimation and statistical hypothesis testing, optimization and simulation models, descriptive reviews and policy analyses. We particularly encourage submission of empirical work that can be replicated and tested by others.
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