The Impact of Animal Disease Outbreaks on China’s Meat Imports

ABSTRACT

We assess the effect of three animal disease outbreaks on China’s meat imports from 1992 to 2017, namely foot-and-mouth disease (FMD) for swine, bovine spongiform encephalopathy (BSE) for cattle, and highly pathogenic avian influenza (HPAI) for poultry. Using system-GMM and FGLS estimators, we find that outbreaks of animal diseases in exporting countries reduce China’s import of the meat products. Additionally, we find positive trade diversion and substitution effects in both FMD and HPAI but negative effects in BSE. Although these results indicate that China can accommodate its meat consumption needs through international trade now, we are skeptical that it can continue to do so if animal husbandry practices do not improve in China. This calls for major meat exporters to improve production efficiency and reduce the prevalence of animal diseases. With increasing environmental pressure and high dependency on imported feed caused by the expanding livestock sector, we recommend a sustainable diet by encouraging less consumption of meat.

KEYWORDS:

• Meat imports
• animal diseases
• diversion effect
• substitution effect

JEL:

• F14
• Q18

Supplemental data

Supplemental data for this article can be accessed online at https://doi.org/10.1080/1540496X.2023.2223929

Disclosure Statement

No potential conflict of interest was reported by the author(s).

Notes

1. By the end of 2019, about 21% of the Chinese pig population was infected and culled according to official estimates. Others estimated that China lost more than 50% of pigs (Chiang and Sun 2019). To fill the gap between production and consumption and to stabilize pork prices, the Chinese government started an emergency import strategy by increasing pork and beef imports to 2.11 million tons and 1.66 million tons, respectively, in 2019.

2. The FGLS estimation is a three-stage procedure: (1) estimate the first-order correlation coefficient using Prais and Winsten (1954) estimator; (2) difference all variables using the estimated first-order correlation coefficient; (3) run an OLS regression using the differenced variables. Since the error terms of different meat functions may be correlated due to the substitution of different meat, we employ the Seemingly Uncorrelated Regression (SUR) in the third step to control such bias.

3. Based on the China Statistical Yearbook, beef and mutton accounted for only 9.51% of Chinese diet.

Additional information

Funding

This study was supported by Chinese Universities Scientific Fund (2023TC105).