Threshold Effects of Infectious Disease Outbreaks on Livestock Prices: Cases of African Swine Fever and Avian Influenza in South Korea

Hyungchul Rah,Kwan-Hee Yoo,Aziz Nasridinov,Hyeon-Woong Kim,Seokhwa Choi,Wan-Sup Cho

doi:10.3390/app11115114

Hyungchul Rah, Kwan-Hee Yoo + Show 4 more

Open Access

https://doi.org/10.3390/app11115114

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Abstract

In this paper we demonstrate the threshold effects of infectious diseases on livestock prices. Daily retail prices of pork and chicken were used as structured data; news and SNS mentions of African Swine Fever (ASF) and Avian Influenza (AI) were used as unstructured data. Models were tested for the threshold effects of disease-related news and SNS frequencies, specifically those related to ASF and AI, on the retail prices of pork and chicken, respectively. The effects were found to exist, and the values of ASF-related news on pork prices were estimated to be −9 and 8, indicating that the threshold autoregressive (TAR) model can be divided into three regimes. The coefficients of the ASF-related SNS frequencies on pork prices were 1.1666, 0.2663 and −0.1035 for regimes 1, 2 and 3, respectively, suggesting that pork prices increased by 1.1666 Korean won in regime 1 when ASF-related SNS frequencies increased. To promote pork consumption by SNS posts, the required SNS frequencies were estimated to have impacts as great as one standard deviation in the pork price. These values were 247.057, 1309.158 and 2817.266 for regimes 1, 2 and 3, respectively. The impact response periods for pork prices were estimated to last 48, 6, and 8 days for regimes 1, 2 and 3, respectively. When the prediction accuracies of the TAR and autoregressive (AR) models with regard to pork prices were compared for the root mean square error, the prediction accuracy of the TAR model was found to be slightly better than that of the AR. When the threshold effect of AI-related news on chicken prices was tested, a linear relationship appeared without a threshold effect. These findings suggest that when infectious diseases such as ASF occur for the first time, the impact on livestock prices is significant, as indicated by the threshold effect and the long impact response period. Our findings also suggest that the impact on livestock prices is not remarkable when infectious diseases occur multiple times, as in the case of AI. To date, this study is the first to suggest the use of SNS to promote meat consumption.

Highlights

During the outbreak of African Swine Fever (ASF) in South Korea in 2019, the media predicted that the pork supply would decrease and that pork prices would rise by the end of September of that year
We aimed to demonstrate that the threshold effects of the threshold autoregressive (TAR) model
Error may be used for better livestock epidemics such as (RMSE)

Summary

Introduction

During the outbreak of African Swine Fever (ASF) in South Korea in 2019, the media predicted that the pork supply would decrease and that pork prices would rise by the end of September of that year. At the end of October, after the ASF outbreak was controlled, pork prices collapsed due to a sharp fall in consumption [1] This situation is thought to have stemmed from the reduced will of consumers to purchase pork, as news about the ASF outbreak was reported and the information was delivered to consumers through various types of media, including SNS. Avian Influenza (AI) occur, they can have a negative effect on demand and cause volatile changes to livestock prices because the supply of livestock products will be reduced because of the pre-emptive slaughter of animals at risk and the fall in consumer demand [2,3]. News about livestock diseases was considered to be an advertisement against livestock consumption [2,5,6]

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