On Spatial Processes and Asymptotic Inference under Near-Epoch Dependence
Nazgul Jenish and Ingmar Prucha ,
( 170 )
Journal of Econometrics

The development of a general inferential theory for nonlinear models with cross-sectionally or spatially dependent data has been hampered by a lack of appropriate limit theorems. To facilitate a general asymptotic inference theory relevant to economic applications, this paper first extends the notion of near-epoch dependent (NED) processes used in the time series literature to random fields. The class of processes that is NED on, say, an α-mixing process, is shown to be closed under infinite transformations, and thus accommodates models with spatial dynamics.

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