Abstract
Transmission of price shocks among related markets is a necessary condition for economic efficiency. Earlier empirical studies have investigated price spillovers in green coffee markets across physical space, quality space, and/or time through highly restrictive models. The present work examines price transmission “at the extremes” using penalized quantile regressions, an econometric tool that allows one to analyze complex market networks. The analysis relies on daily green coffee prices from two geographically separated markets (USA and EU), four coffee varieties, and two futures markets. The empirical results suggest: (a) price risk spillovers are stronger when quality differentiation is low and when green coffee varieties are traded within the same spatial market; (b) higher quality varieties are net-transmitters of price risk to lower quality ones while futures markets are net-receivers of price risk from spot markets; and (c) asymmetric price spillovers are more likely to occur for coffee beans traded in different spatial markets.
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