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Title: A copula approach to spatial econometrics with applications to finance Authors:  Hideatsu Tsukahara - Seijo University (Japan) [presenting]
Abstract: Traditional models in spatial econometrics utilize a spatial weight matrix as a means to express spatial dependence, but its choice is quite arbitrary. Besides, it imposes a linear structure between dependent variables; in its simplest form, a dependent variable at one spatial unit is a linear combination of dependent variables at other spatial units. When the underlying disturbance distribution is assumed to be Gaussian or elliptical in general, the model does not allow asymmetry in dependence structure and tail dependence for spatial interactions. These restrictions are too strict in some applications, for example, in finance. Therefore, we generalize existent models to allow for some nonlinear and tail dependence in disturbance distribution by applying the copula approach which somehow reflects the spatial dependence indicated by spatial weight matrix. After discussing some properties of the resulting model, we develop an estimation method assuming a (semi)parametric copula. Simulation results illustrate the applicability of the procedure. Some real applications to financial data will be given.