Can the Futures Price of Agricultural Products Predict the Scale of China's Agricultural Production?

Xianning Wang (), Xikai Huang, Longkun Tian and Huiyan Zhou
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Xianning Wang: School of Economics and Management, Chongqing Normal University, No. 37 of Middle Road of University Town, Shapingba District, 401331, Chongqing, China Big Data Marketing Research and Applications Center, No. 37 of Middle Road of University Town, Chongqing Normal University, Shapingba District, 401331, Chongqing, China
Xikai Huang: School of Economics and Management, Chongqing Normal University, No. 37 of Middle Road of University Town, Shapingba District, 401331, Chongqing, China Big Data Marketing Research and Applications Center, No. 37 of Middle Road of University Town, Chongqing Normal University, Shapingba District, 401331, Chongqing, China
Longkun Tian: School of Economics and Management, Chongqing Normal University, No. 37 of Middle Road of University Town, Shapingba District, 401331, Chongqing, China Big Data Marketing Research and Applications Center, No. 37 of Middle Road of University Town, Chongqing Normal University, Shapingba District, 401331, Chongqing, China
Huiyan Zhou: School of Economics and Management, Chongqing Normal University, No. 37 of Middle Road of University Town, Shapingba District, 401331, Chongqing, China Big Data Marketing Research and Applications Center, No. 37 of Middle Road of University Town, Chongqing Normal University, Shapingba District, 401331, Chongqing, China

Journal for Economic Forecasting, 2024, issue 4, 128-143

Abstract: The change in the production scale of agricultural products not only affects the income of agricultural producers and the management decisions of agriculture-related enterprises, but also affects national food security; therefore, the accurate prediction of the production scale of agricultural products cannot be ignored. Agricultural futures as a financial derivative have precedence; their price fluctuation is the result of the role of multiple parties, which, to a certain extent, can respond to and affect the production of agricultural products. Based on the high-frequency characteristics of agricultural futures prices and the growth cycle of agricultural products, this paper selects the high-frequency monthly futures price data of soybean and corn as the research object and compiles the growth cycle futures price data of agricultural products, selects the mixed-frequency data regression model to predict the scale of agricultural product production, and takes the benchmark prediction model as a reference to comprehensively compare the prediction effect.The conclusions of this paper are as follows: 1. the mixed-frequency data regression model for agricultural futures prices can predict the scale of agricultural production in China, and the direct prediction using mixed-frequency data can tap the potential information contained in the high-frequency data, thus improving the prediction accuracy; 2. there is a negative effect between monthly agricultural futures prices and the related agricultural production in the period of March to May near the harvest, especially in the recent month, which is the most obvious.

Keywords: agricultural production scale; agricultural futures prices; mixed-frequency data; mixed-frequency data regression models (search for similar items in EconPapers)
JEL-codes: C53 E37 (search for similar items in EconPapers)
Date: 2024
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