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

Ray Huffaker,Charles Dambui,Garry Griffith,Maurizio Canavari

doi:10.3390/su13169172

Ray Huffaker, Charles Dambui + Show 2 more

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https://doi.org/10.3390/su13169172

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Abstract

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 ill-equipped 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.

Highlights

Price transmission concerns the extent to which price changes from one market pass through to spatially distinct markets, and is a fundamental indicator of market integration along global–domestic supply chains, domestic market efficiency, and economic welfare of exporters, processors, and producers [1]
We propose a novel empirical framework that adopts emerging methods from empirical nonlinear dynamics capable of reconstructing market dynamics from price data in economic application [16,17], and in doing so, tests whether market dynamics concealed in volatile observed prices are most likely generated by stable linear-stochastic market dynamics or endogenously unstable nonlinear-deterministic dynamics—both legitimate theory-based alternatives [14,18,19,20,21]
We extend the world price (WP) series and isolated nonlinear trend cycle two years beyond the period-of-record of the domestic prices to demonstrate that the trend cycle has a length of about 18 years (2002–2020)

Summary

Introduction

Price transmission concerns the extent to which price changes from one market pass through to spatially distinct markets, and is a fundamental indicator of market integration along global–domestic supply chains, domestic market efficiency, and economic welfare of exporters, processors, and producers [1]. Arrow et al (2004) took this to mean that “intertemporal social welfare must not decrease over time” [3]. In this context, policymakers rely on “before-and-after” measures of price transmission to empirically determine whether global trade policies have had an adverse welfare impact on domestic markets [1]. For price transmission to be a reliable welfare measure, there is critical need for theory and empirical practice to correspond to real-world global–domestic supply-chain price dynamics

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