Abstract
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.
Highlights
Price plays an important role in actualising efficient resource allocation in an economy
Almost nothing is understood about the liaisons between international and regional meat markets even though meat value chains have been disrupted by infectious disease outbreaks such as bovine spongiform encephalopathy (BSE) and COVID-19
The main results are that (1) local beef price returns for Azerbaijan, Georgia, Japan, Kazakhstan, Kyrgyzstan, Tajikistan, the UK and the United States have a structural change in mean or variance, all of which appear after 2010, (2) the global price Granger-causes indigenous prices in both mean and variance for Georgia, Tajikistan, and the United States, and no country showed price or price-volatility transmission from local to global prices, and (3) liaisons across world and regional markets regarding dynamic conditional correlation (DCC) are generally weak, but the intensity of market associations became more volatile around the 2008 global food crisis, which generated structural breaks during the period
Summary
Price plays an important role in actualising efficient resource allocation in an economy. Data description and preliminary analysis This research concentrates on nine net beef-importing countries (Azerbaijan, Georgia, Japan, Kazakhstan, Kyrgyzstan, Tajikistan, Tunisia, the UK and the United States of America) These nations were selected based on data availability and the criterion that self-sufficiency in beef does not exceed 100% according to data sourced from the Food and Agriculture Organization (FAO) corporate statistical database (FAOSTAT). Preliminary analysis indicates that these price returns are characterised by non-normal distributions, negative skewness, fat tails, stationarity and an endogenous structural break Based on these results, it is important to further examine the existence of multiple structural changes in the conditional mean and variance for each price return. Break, CCF and DCC methodology are used to investigate Granger causality and the dynamic interaction between international and domestic beef prices in beef-importing countries
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