Citation
Abstract
Beef prices in China have experienced increased volatility in recent years, yet existing research has failed to distinguish the state dependence of price fluctuations. This study constructs a two-state Markov switching vector autoregression (MS-VAR) model based on beef price return data from eastern, central, and western China from 2010 to 2024. The results identify two price regimes: normal (low volatility) and abnormal (high volatility). Under normal conditions, market volatility is small, with regional prices primarily driven by internal factors; under abnormal conditions, prices fluctuate dramatically, with significantly enhanced regional linkage effects. Model comparisons show that the MS-VAR model outperforms linear VAR and threshold VAR (TVAR) models in both fitting and forecasting performance. This study expands theoretical understanding of the state dependence of price behavior in agricultural economics and provides policy implications for establishing early warning mechanisms for beef market price fluctuations and cross-regional linkage regulation.
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Official URL or Download Paper: https://www.tandfonline.com/doi/full/10.1080/23322...
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Additional Metadata
| Item Type: | Article |
|---|---|
| Subject: | Finance |
| Subject: | Economics and Econometrics |
| Divisions: | Faculty of Humanities, Management and Science Institute of Ecosystem Science Borneo |
| DOI Number: | https://doi.org/10.1080/23322039.2025.2564210 |
| Publisher: | Cogent OA |
| Keywords: | China’s beef market; China’s beef production; Ms-var model; Regime transition effect; Volatility |
| Sustainable Development Goals (SDGs): | SDG 2: Zero Hunger, SDG 8: Decent Work and Economic Growth, SDG 12: Responsible Consumption and Production |
| Depositing User: | Ms. Siti Radziah Mohamed@mahmod |
| Date Deposited: | 23 Apr 2026 08:40 |
| Last Modified: | 23 Apr 2026 08:40 |
| Altmetrics: | http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.1080/23322039.2025.2564210 |
| URI: | http://psasir.upm.edu.my/id/eprint/123262 |
| Statistic Details: | View Download Statistic |
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