Separate estimation of spatial dependence parameters and variance parameters in a spatial model
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Date
2010-04-06T08:52:44Z
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Abstract
This paper suggests a two step estimation procedure for a spatial model with
different kinds of spatial dependence and heteroscedastic innovations. Since
maximum likelihood estimation is cumbersome due to the large number of parameters, we use a generalized method of moments approach to estimate the parameters of spatial correlation which does not need the large number of variance parameters to be known. For illustration purposes, we apply our
estimation procedure to daily stock returns of the Euro Stoxx 50 members. JEL subject classifications: C13, C51, G12
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Keywords
GMM estimation, Heteroscedasticity, Spatial dependence, Stock returns