Price dependence in the principal EU olive oil markets
Abstract
The objective of this paper is to assess the degree and the structure of price dependence in the principal EU olive oil markets (Spain, Italy and Greece). To this end, it utilizes monthly olive oil price data and the statistical tool of copulas. The empirical results suggest that prices are likely to boom together but not to crash together; this is especially true for the prices of the two most important players, Italy (importer) and Spain (exporter). The finding of asymmetric price co-movements implies that the three principal spatial olive oil markets in the EU cannot be thought of as one great pool.
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References
Asche F, Bremnes H, Wessels C, 1999. Product aggregation, market integration, and relationships between prices. Am J Agr Econ 81: 568-81.
http://dx.doi.org/10.2307/1244016
Borchert E, Reineke S, 2007. Eating, drinking, smoking. Comparative price levels in 37 European countries for 2006, statistics in focus. Econ Financ 90: 1-7.
Brechmann E, Schepsmeier U, 2013. Modeling dependence with C- and D-vine copulas: the R-package CDVine. J Stat Software 52 (3): 1-27.
Chen X, Fan Y, 2006. Estimation of copula-based semiparametric time series Models. J Econometrics 130: 307-335.
http://dx.doi.org/10.1016/j.jeconom.2005.03.004
Choros B, Ibragimov R, Permiakova E, 2010. Copula estimation. In: Copula theory and its applications (Jaworski P, Durante F, Härdle W, Rychlik T, eds.). Springer, Dordrecht (Netherlands), pp: 77-92.
http://dx.doi.org/10.1007/978-3-642-12465-5_3
Czado C, Schepsmeier U, Min A, 2012. Maximum likelihood estimation of mixed C-vines with application to exchange rates. Stat Model 12: 229-255.
http://dx.doi.org/10.1177/1471082X1101200302
Durante F, Sempi C, 2010. Copula theory: an introduction. In: Copula theory and its applications (Jaworski P, Durante F, Härdle W, Rychlik T, eds.). Springer, Dordrecht (Netherlands), pp: 3-31.
http://dx.doi.org/10.1007/978-3-642-12465-5_1
Efron B, 1979. Bootstrap methods: another look at the jackknife. Ann Stat 7: 1-26.
http://dx.doi.org/10.1214/aos/1176344552
Embrechts P, McNeil A, Straumann D, 2002. Correlation and dependence in risk management: properties and pittfalls. In: Risk management: value at risk and beyond. (Dempster MA, ed.) Cambridge Univ. Press, Cambridge (UK), pp: 176-223.
http://dx.doi.org/10.1017/CBO9780511615337.008
Emmanouilides C, Fousekis P, 2012. Testing for the LOP under non linearity: an application to four major EU markets. Agr Econ 43: 715-723.
http://dx.doi.org/10.1111/j.1574-0862.2012.00614.x
EC, 2001. European economy. Supplement A: Economic Trends, No 7, July.
EC, 2004. The internal market scoreboard. No 13, July 2004.
EC, 2008. Market monitoring: state of play and envisaged follow-up. Commission Staff Working Document No. 3074.
EC, 2012a. Economic and financial affairs. Market integration and internal market issues.
EC, 2012b. Economic analysis of the olive sector. DG for Agriculture and Rural Development, Brussels. July.
EC, 2012c. Statistics for olive oil. European Commission. DG for Agriculture and Rural Development, Brussels. November.
EC, 2013. Olive oil prices and trade data. DG for Agriculture and Rural Development, Brussels. Available in http://ec.europa.eu/agriculture/olive-oil/prices/index_en.htm [20 December 2013].
Fousekis P, 2007. Multiple markets within the EU? Empirical evidence from pork and poultry prices in 14 EU member states. Econ Bull 3(65): 1-12.
Genest C, Favre AC, 2007. Everything you always wanted to know about copula but you were afraid to ask. J Hydrol Eng 12: 347-368.
http://dx.doi.org/10.1061/(ASCE)1084-0699(2007)12:4(347)
Genest C, Ghoudi K, Rivest LP, 1995. A semi-parametric estimation procedure of dependence parameters in multivariate families of distribution. Biometrica 82: 543-552.
http://dx.doi.org/10.1093/biomet/82.3.543
Genest C, Remillard B, Beaudoin D, 2009. Goodness of fit tests for copulas: a review and a power study. Insurance: Mathematics and Economics 44: 192-213.
http://dx.doi.org/10.1016/j.insmatheco.2007.10.005
Goodwin BK, Holt M, Onel G, Prestemon P, 2011. Copula-based nonlinear models of spatial price linkages. Paper presented at the AAEA Meetings, Pittsburg, July 24-26.
Granger CWJ, 1969. Investigating causal relations by econometric models and cross-spectral methods. Econometrica 37 (3): 424-438.
http://dx.doi.org/10.2307/1912791
Joe H, 1997. Multivariate models and dependence concepts. Chapman & Hall, London (UK).
http://dx.doi.org/10.1201/b13150
Kim G, Silvapulle M, Silvapulle P, 2007. Comparison of semiparametric and parametric methods for estimating copulas. Communications in Statistics-Simulation and Computation 51: 2836–2850.
Meucci A, 2011. A short, comprehensive, practical guide to copulas. Risk Professional October: 22-27.
Nelsen RB, 2006. An introduction to copulas. Springer-Verlag, NY (USA).
Patton A, 2012. A review of copula models for economic time series. J Multivariate Anal 110: 4-18.
http://dx.doi.org/10.1016/j.jmva.2012.02.021
Reboredo J, 2011. How do crude oil price co-move? A copula approach. Energ Econ 33: 948-955.
http://dx.doi.org/10.1016/j.eneco.2011.04.006
Requenta A, Mediero L, Garrote L, 2013. Bivariate return period based on copulas for hydrologic dam design: comparison of theoretical and empirical approach. Hydrology and Earth Systems Science Discussions 10: 557–596.
http://dx.doi.org/10.5194/hessd-10-557-2013
Schepmeier U, Brechmann E, 2012. Statistical inference with C- and D-vine copulas.Version 1.1. Repository CRAN, Wien, 7 March 2012.
Serra T, Gil J, 2012. Biodiesel as a motor fuel stabilization mechanism. CREDA working paper, Castelldefels (Barcelona).
Serra T, Gil J, Goodwin B, 2006. Local polynomial fitting and spatial price relationships: Price transmission in EU pork markets. Eur Rev Agr Econ 33: 415-436.
http://dx.doi.org/10.1093/erae/jbl013
Sexton R, Kling C, Carman H, 1991. Market integration, efficiency of arbitrage and imperfect competition. Am J Agr Econ 73: 568-580.
http://dx.doi.org/10.2307/1242810
Sklar A, 1959. Fonctions de repartition a "n" dimensions et leurs marges. Publications de l'Institut Statistique de l'Université de Paris 8: 229-213.
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