Empirical Detection and Quantification of Price Transmission in Endogenously Unstable Markets: The Case of the Global–Domestic Coffee Supply Chain in Papua New Guinea

Price transmission through global–domestic agricultural supply chains is a fundamental indicator of domestic market efficiency and producer welfare. Conventional price-transmission econometrics test for a theory-based spatial-arbitrage restriction that long-run equilibrium prices in spatially distinct markets differ by no more than transaction costs. The conventional approach is illequipped to test for price transmission when endogenously unstable markets do not equilibrate due to systematic arbitrage-frustrating frictions including financial and institutional transaction costs and biophysical constraints. We propose a novel empirical framework using price data to test for market stability and price transmission along international-domestic supply chains incorporating nonlinear time series analysis and recently emerging causal-detection methods from empirical nonlinear dynamics. We apply the framework to map-out and quantify price transmission through the global exporter–processor–producer coffee supply chain in Papua, New Guinea. We find empirical evidence of upstream price transmission from the global market to domestic exporters and processors, but not through to producers.