Comparing the great recession and COVID‐19 using Long Short‐Term Memory: A close look into agricultural commodity prices

IF 3.3 2区 经济学 Q2 AGRICULTURAL ECONOMICS & POLICY
Modhurima Dey Amin, Syed Badruddoza, Oscar Sarasty
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引用次数: 0

Abstract

We employ a neural network (NN) approach—Long Short‐Term Memory (LSTM)—to study agricultural commodity prices during the 2008 Great Recession and the COVID‐19 recession. Our analysis reveals more structural breaks and higher volatility in plant‐based commodities like corn and soybeans during recessions compared with animal‐based commodities. The price reactions varied among commodities, with corn responding first to both recessions, while milk price, which was found independent of other prices, recovered last from the financial recession and first from the disease‐induced recession. This insight into commodity behavior during recessions can aid in trend prediction and recession preparation for investors and researchers.
利用长短期记忆比较大衰退和 COVID-19仔细研究农产品价格
我们采用神经网络(NN)方法--长短期记忆(LSTM)--研究 2008 年大衰退和 COVID-19 衰退期间的农产品价格。我们的分析表明,与动物性商品相比,玉米和大豆等植物性商品在经济衰退期间的结构性断裂更多,波动性更高。不同商品的价格反应各不相同,玉米首先对两次经济衰退做出反应,而牛奶价格则独立于其他价格,最后从金融衰退中恢复,最先从疾病引发的衰退中恢复。对经济衰退期间商品行为的深入了解有助于投资者和研究人员进行趋势预测和衰退准备。
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来源期刊
Applied Economic Perspectives and Policy
Applied Economic Perspectives and Policy AGRICULTURAL ECONOMICS & POLICY-
CiteScore
10.70
自引率
6.90%
发文量
117
审稿时长
>12 weeks
期刊介绍: Applied Economic Perspectives and Policy provides a forum to address contemporary and emerging policy issues within an economic framework that informs the decision-making and policy-making community. AEPP welcomes submissions related to the economics of public policy themes associated with agriculture; animal, plant, and human health; energy; environment; food and consumer behavior; international development; natural hazards; natural resources; population and migration; and regional and rural development.
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