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Abstract
An extensive empirical literature has addressed a wide array of issues pertaining to
price linkages over space and across time. Empirical models of price linkages have been
used to measure market power and to characterize the operation of markets that are
separated by space, time, and product form. The long history of these empirical models
extends from simple tests of price correlation, to conventional regression tests, to modern
time series models that account for nonstationarity, nonlinearities, and threshold
behavior in market linkages. This paper proposes an entirely different and potentially
novel approach to analyzing these same types of time series data in a nonlinear fashion.
Copula-based models that consider the joint distribution of prices separated by
space are developed and applied to weekly prices for important lumber products at
geographically distinct markets. In particular, we consider prices taken from weekly
editions of the Random Lengths publication for homogeneous OSB products.