Stavrakoudis, Athanassios and Panagiotou, Dimitrios (2016): Price dependence between coffee qualities: a copula model to evaluate asymmetric responses.
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Abstract
The objective of this paper is to assess the degree and the structure of price dependence between different coffee qualities of the Arabica and Robusta varieties. This is pursued using the statistical tool of copulas and monthly price data for the period 1990:1{2014:12. Our results reveal evidence of asymmetric price dependence between the pairs Brazilian-Robusta, Brazilian-Others and Robusta-Others, since price booms and price crashes are transmitted with different probabilities between these pairs of coffee qualities. For the pairs Brazilian-Colombian, Colombian-Robusta and Colombian-Others there is no evidence of asymmetric price dependence. The empirical findings of this article indicate that the probability that fairtrade coffee producers will see a price crash in the Robusta variety being transmitted to the coffee qualities of the Arabica variety is either zero or much lower than the probability of the transmission of a price boom.
Item Type: | MPRA Paper |
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Original Title: | Price dependence between coffee qualities: a copula model to evaluate asymmetric responses |
English Title: | Price dependence between coffee qualities: a copula model to evaluate asymmetric responses |
Language: | English |
Keywords: | coffee qualities; price dependence; copula; fairtrade |
Subjects: | C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C14 - Semiparametric and Nonparametric Methods: General F - International Economics > F1 - Trade > F15 - Economic Integration Q - Agricultural and Natural Resource Economics ; Environmental and Ecological Economics > Q1 - Agriculture > Q13 - Agricultural Markets and Marketing ; Cooperatives ; Agribusiness |
Item ID: | 75994 |
Depositing User: | Dr Athanassios Stavrakoudis |
Date Deposited: | 05 Jan 2017 04:53 |
Last Modified: | 30 Sep 2019 02:42 |
References: | Acar, E. F., C. Genest, and J. NesLehova (2012). Beyond simpli�ed pair-copula constructions. Journal of Multivariate Analysis 110, 74-90. Akiyama, T. and P. N. Varangis (1990). The impact of the international coffee agreement on producing countries. The World Bank Economic Review 4, 157-173. Bacon, C. M., V. E. Mendez, S. R. Gliessman, D. Goodman, and J. A. Fox (Eds.) (2008). Fair Trade, Sustainable Livelihoods and Ecosystems in Mexico and Central America . MIT Press. Bakucs, Z., J. Fa lkowski, and I. Ferto (2014). Does Market Structure Influence Price Transmission in the Agro-food Sector? A Meta-analysis Perspective. Journal of Agricultural Economics 65, 1-25. Berg, D. (2009). Copula goodness-of-fit testing: an overview and power comparison. The European Journal of Finance 15, 675-701. Brechmann, E. C. and U. Schepsmeier (2013). Modeling Dependence with C- and D-Vine Copulas: The R Package CDVine. Journal of Statistical Software 52, 1-27. Byrd, R. H., P. Lu, J. Nocedal, and C. Zhu (1995). A limited memory algorithm for bound constrained optimization. SIAM Journal on Scienti�c Computing 16, 1190-1208. Chen, X. and Y. Fan (2006). Estimation of copula-based semiparametric time series models. Journal of Econometrics 130, 307-335. Choros, B., R. Ibragimov, and E. Permiakova (2010). Copula estimation. In Copula theory and its applications, pp. 77-91. Springer. Czado, C., U. Schepsmeier, and A. Min (2012). Maximum likelihood estimation of mixed c-vines with application to exchange rates. Statistical Modelling 12 (3), 229-255. Diβmann, J., E. Brechmann, C. Czado, and D. Kurowicka (2013). Selecting and estimating regular vine copulae and application to financial returns. Computational Statistics & Data Analysis 59, 52-69. Donnet, M. L., D. D. Weatherspoon, and J. P. Hoehn (2008). Price determinants in top-quality e-auctioned specialty coffees. Agricultural Economics 38, 103-118. Emmanouilides, C. J. and P. Fousekis (2015). Vertical price dependence structures: copula-based evidence from the beef supply chain in the USA. European Review of Agricultural Economics 42, 77-97. Frey, G. and M. Manera (2007). Econometric models of asymmetric price transmission. Journal of Economic Surveys 21, 349-415. Gaiβer, S., M. Ruppert, and F. Schmid (2010). A multivariate version of Hoeffding's phi-square. Journal of Multivariate Analysis 101, 2571-2586. Genest, C. and W. Huang (2012). A regularized goodness-of-fit test for copulas. Journal de la Societe Francaise de Statistique & revue de statistique appliquee 154, 64-77. Genest, C., B. Remillard, and D. Beaudoin (2009). Goodness-of-fit tests for copulas: A review and a power study. Insurance: Mathematics and Economics 44, 199-213. Ghalanos, A. (2014). rugarch: Univariate GARCH models. R package version 1.3-4. Ghoshray, A. (2009). On Price Dynamics for Different Qualities of Coffee. Review of Market Integration 1, 103-108. Hofert, M., I. Kojadinovic, M. Maechler, and J. Yan (2014). copula: Multivariate Dependence with Copulas. R package version 0.999-12. ICO (2015). International co�ee organization. http://www.ico.org. Accessed 16 February 2015. Joe, H. (2014). Dependence Modeling with Copulas. CRC Press. Jordanger, L. A. and D. Tjostheim (2014). Model selection of copulas: AIC versus a cross validation copula information criterion. Statistics & Probability Letters 92, 249-255. Kilian, B., C. Jones, L. Pratt, and A. Villalobos (2006). Is sustainable agriculture a viable strategy to improve farm income in Central America? A case study on coffee. Journal of Business Research 59, 322-330. Kojadinovic, I., J. Yan, M. Holmes, et al. (2011). Fast large-sample goodness-of-fit tests for copulas. Statistica Sinica 21, 841-871. Manner, H. (2007). Estimation and model selection of copulas with an application to exchange rates. Technical report. http://arnop.unimaas.nl/show.cgi?fid=9426. Manner, H. and O. Reznikova (2012). A Survey on Time-Varying Copulas: Specification, Simulations, and Application. Econometric Reviews 31, 654-687. Mehtaa, A. and J.-P. Chavasb (2008). Responding to the coffee crisis: What can we learn from price dynamics? Journal of Development Economics 85, 282-311. Meucci, A. (2011). A Short, Comprehensive, Practical Guide to Copulas. http://ssrn.com/abstract=1847864. Meyer, J. and S. Cramon-Taubadel (2004). Asymmetric price transmission: a survey. Journal of Agricultural Economics 55, 581-611. Nash, J. C. (2014). On Best Practice Optimization Methods in R. Journal of Statistical Software 60, 1-14. Nash, J. C. and R. Varadhan (2011). Unifying Optimization Algorithms to Aid Software System Users: optimx for R. Journal of Statistical Software 43, 1-14. Nelsen, R. B. (2007). An introduction to copulas. Springer. Paige, J. M. (1997). COFFEE AND POWER. Harvard University Press. Panagiotou, D. and A. Stavrakoudis (2015). Price asymmetry between different pork cuts in the USA: a copula approach. Agricultural and Food Economics 3 (1) Patton, A. J. (2012). A review of copula models for economic time series. Journal of Multivariate Analysis 110, 4-18. Ponte, S. (2002). The Latte Revolution? Regulation, Markets and Consumption in the Global Coffee Chain. World Development 30, 1099-1122. R Core Team (2014). R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing. Rapsomanikis, G., D. Hallam, and P. Conforti (2006). Market integration and price transmission in selected food and cash crop markets of developing countries: review and applications. In A. S. and D. Hallam (Eds.), Agricultural Commodity Markets and Trade, pp. 187-217. Edwar Elgar Publishing Limited. Reboredo, J. C. (2011). How do crude oil prices co-move?: A copula approach. Energy Economics 33, 948-955 Reboredo, J. C. (2012). Do food and oil prices co-move? Energy Policy 49, 456-467. Reinecke, J., S. Manning, and O. Von Hagen (2012). The emergence of a standards market: Multiplicity of sustainability standards in the global coffee industry. Organization Studies 33 (5-6), 791-814. Reznikova, O. (2012). On the estimation of dynamic conditional correlation models. Computational Statistics & Data Analysis 56, 3533-3545. Russell, B., S. Mohan, and A. Banerjee (2012). Coffee Market Liberalisation and the Implications for Producers in Brazil, Guatemala and India. The World Bank Economic Review 26, 514-538. Sklar, A. (1959). Fonctions de repartition A n dimensions et leurs marges. Publicatons de L'Institut Statistique de L'Universite de Paris 8, 229-231. Sukcharoen, K., T. Zohrabyan, D. Leatham, and X. Wu (2014). Interdependence of oil prices and stock market indices: A copula approach. Energy Economics 44, 331-339. Swinnen, J. F. M. and A. Vandeplas (2014). Price Transmission and Market Power in Modern Agricultural Value Chains. http://dx.doi.org/10.2139/ssrn.2400431. Talbot, J. M. (2004). Grounds for Agreement: The Political Economy of the Coffee Commodity Chain. ROWMAN & LITTLEFIELD PUBLISHERS. Trivedi, P. K. and D. M. Zimmer (2005). Copula Modeling: An Introduction for Practitioners. Foundations and Trends in Econometrics 1, 1-111. Ubilava, D. (2012). El Ni~no, La Nina, and world coffee price dynamics. Agricultural Economics 43, 17-26. Vavra, P. and B. K. Goodwin (2005). Analysis of Price Transmission Along the Food Chain. http://dx.doi.org/10.1787/752335872456. Wilson, A. P. and N. L. Wilson (2014). The economics of quality in the specialty coffee industry: insights from the Cup of Excellence auction programs. Agricultural Economics 45, 91-105. Yan, J. (2007). Enjoy the Joy of Copulas: With a Package copula. Journal of Statistical Software 21, 1{21. Zhang, J. and D. Gueganc (2008). Pricing bivariate option under GARCH processes with time varying copula. Insurance: Mathematics and Economics 42, 1095-1103. |
URI: | https://mpra.ub.uni-muenchen.de/id/eprint/75994 |