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The Philippine Agricultural Scientist

Yu Wang, Agricultural Information Institute, Chinese Academy of Agricultural Sciences/ Research Center of Agricultural Monitoring and Early Warning Engineering Technologies of Beijing/ Key Open Laboratory of Intelligent Agricultural Early Warning Technologies and Systems, Chinese Academy of Agricultural Sciences/ Key Laboratory of Agricultural Monitoring and Early Warning Technology, Ministry of Agriculture and Rural Affairs, P.R. China, Beijing 100081
Shiwei Xu, Agricultural Information Institute, Chinese Academy of Agricultural Sciences/ Research Center of Agricultural Monitoring and Early Warning Engineering Technologies of Beijing/ Key Open Laboratory of Intelligent Agricultural Early Warning Technologies and Systems, Chinese Academy of Agricultural Sciences/ Key Laboratory of Agricultural Monitoring and Early Warning Technology, Ministry of Agriculture and Rural Affairs, P.R. China, Beijing 100081
Ganqiong Li, Agricultural Information Institute, Chinese Academy of Agricultural Sciences/ Research Center of Agricultural Monitoring and Early Warning Engineering Technologies of Beijing/ Key Open Laboratory of Intelligent Agricultural Early Warning Technologies and Systems, Chinese Academy of Agricultural Sciences/ Key Laboratory of Agricultural Monitoring and Early Warning Technology, Ministry of Agriculture and Rural Affairs, P.R. China, Beijing 100081Follow
Yongen Zhang, Agricultural Information Institute, Chinese Academy of Agricultural Sciences/ Research Center of Agricultural Monitoring and Early Warning Engineering Technologies of Beijing/ Key Open Laboratory of Intelligent Agricultural Early Warning Technologies and Systems, Chinese Academy of Agricultural Sciences/ Key Laboratory of Agricultural Monitoring and Early Warning Technology, Ministry of Agriculture and Rural Affairs, P.R. China, Beijing 100081
Xiaoyun Zhang, Institute of Agricultural Economics & Information, Xinjiang Academy of Agricultural Sciences, Xinjiang, 100089
Shengwei Wang, Agricultural Information Institute, Chinese Academy of Agricultural Sciences/ Research Center of Agricultural Monitoring and Early Warning Engineering Technologies of Beijing/ Key Open Laboratory of Intelligent Agricultural Early Warning Technologies and Systems, Chinese Academy of Agricultural Sciences/ Key Laboratory of Agricultural Monitoring and Early Warning Technology, Ministry of Agriculture and Rural Affairs, P.R. China, Beijing 100081
Wen Yu, Agricultural Information Institute, Chinese Academy of Agricultural Sciences/ Research Center of Agricultural Monitoring and Early Warning Engineering Technologies of Beijing/ Key Open Laboratory of Intelligent Agricultural Early Warning Technologies and Systems, Chinese Academy of Agricultural Sciences/ Key Laboratory of Agricultural Monitoring and Early Warning Technology, Ministry of Agriculture and Rural Affairs, P.R. China, Beijing 100081Follow
Han Zhou, Agricultural Information Institute, Chinese Academy of Agricultural Sciences/ Research Center of Agricultural Monitoring and Early Warning Engineering Technologies of Beijing/ Key Open Laboratory of Intelligent Agricultural Early Warning Technologies and Systems, Chinese Academy of Agricultural Sciences/ Key Laboratory of Agricultural Monitoring and Early Warning Technology, Ministry of Agriculture and Rural Affairs, P.R. China, Beijing 100081

Publication Date

9-1-2024

Abstract

This study aimed to identify warning thresholds that can guide sellers in achieving reasonable profits while reducing buyer payment costs. Monthly price data from January 2009 to June 2023 and the two-regime threshold regression model were used for an empirical analysis of the asymmetric effects of the changes in household consumption under different pork price fluctuation levels to verify that the changes in household consumption have significant pork price fluctuation thresholds and threshold effects. It was found that as the fluctuation of pork prices approached the threshold, the temporary price-intervention policy (e.g., reference price) effect of adjusting prices diminished. An empirical analysis was conducted from the perspective of asymmetric effects of the upstream (feed and piglets), midstream (live pigs), and downstream (pork) of price transmission. The impacts of the products in the upstream and midstream of the industry chain on pork prices declined gradually, and among the products, the impact of the prices of feeds for fattening pigs on pork prices was found to be the weakest. Thus, the price intervention policy (e.g., reference price) based on the pork price threshold suggests that strengthening the supervision of the price fluctuations of midstream products (e.g., controlling the profit margin) when the pork price fluctuation is near the threshold (8.24%) would have more significant effects on all sides.

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