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?:abstract
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Despite the abundance of literature on agricultural price transmissions and unexpectedly disrupted value chains from infectious disease outbreaks such as bovine spongiform encephalopathy and COVID-19, the importance of research on price connectivity in the international beef markets has largely been ignored To assess agricultural price transmission issues, error correction-type models (ECMs) have been predominantly employed These models, however, suffer a deficiency in that the method is incapable of depicting time-variant linkages between prices This article examines the connections between global and local prices, as well as price volatility in the beef sector Our analysis uses a generalised autoregressive conditional heteroscedasticity (GARCH) model with the dynamic conditional correlation (DCC) specification that enables us to identify market connection intensity dynamics We pay assiduous attention to structural changes in the overall research processes to enhance the reliability of estimation For the first time in meat or grain price transmission research, our autoregressive models have been developed with structural break dummy variables for DCC The principal findings are that (1) local retail prices for Azerbaijan, Georgia, Japan, Kazakhstan, Kyrgyzstan, Tajikistan and the UK showed a structural change in mean or variance, all of which were identified after the global food crisis from 2007–2009, (2) international prices unidirectionally Granger-cause regional prices in Georgia, Tajikistan and the United States in both mean and volatility (accordingly, no country exhibited price or price-volatility transmission from regional to international markets), and (3) volatility liaisons between global and local beef markets are generally weak, but price volatility exhibited closer synchronisation around the 2008 global food crisis, which created structural changes during the period This finding implies that national governments should shield domestic from global markets by implementing trade restrictions such as quotas or taxes in a global emergency © 2020, The Author(s)
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