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Title: A High-Dimensional, Multivariate Copula Approach to Modeling Multivariate Agricultural Price Relationships and Tail Dependencies

Author: Chi, Xuan; Goodwin, Barry;

Date: 2012

Source: Agricultural and Applied Economics Association 2012 Annual Meeting, August 12-14, 2012, Seattle, Washington. Available at http://purl.umn.edu/124634.

Publication Series: Paper (invited, offered, keynote)

Description: Spatial and temporal relationships among agricultural prices have been an important topic of applied research for many years. Such research is used to investigate the performance of markets and to examine linkages up and down the marketing chain. This research has empirically evaluated price linkages by using correlation and regression models and, later, linear and nonlinear time-series models. The most recent research has recognized the fact that price linkages at different locations or levels of the market may be subject to the influences of adjustment and transactions costs. The results of such costs, which are typically unobservable, is to result in discontinuous and/or nonlinear relationships and patterns of adjustment. The most recent research in this area has recognized the fact that price linkages may be very different during extreme market conditions, such as booms and crashes. This tail behavior has become the focus of a new avenue of empirical research that expresses relationships in terms of tail dependence. Much of this recent research has noted that tail dependence often implies very different economic relationships than those that characterize relationships in normal states of the market. In addition, extreme in one direction (e.g., busts) may exhibit very different behavior than in another direction. As a consequence, prices linkages are often observed to have asymmetric tail dependencies.

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Chi, Xuan; Goodwin, Barry K. 2012. A High-Dimensional, Multivariate Copula Approach to Modeling Multivariate Agricultural Price Relationships and Tail Dependencies. Agricultural and Applied Economics Association 2012 Annual Meeting, August 12-14, 2012, Seattle, Washington. Available at http://purl.umn.edu/124634.

 


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