Abstract
In Chap. 12, complexity analysis of spatial data is advocated as a preliminary to spatial econometric regime selection, estimation and testing. That approach assumes that the endogenous variable—only a one-equation model was considered—was measure error free. The present chapter is devoted to controlling for that element of the problem.
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Griffith, D.A., Paelinck, J.H. (2011). Filtering Complexity for Observational Errors and Spatial Bias. In: Non-standard Spatial Statistics and Spatial Econometrics. Advances in Geographic Information Science, vol 1. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16043-1_17
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DOI: https://doi.org/10.1007/978-3-642-16043-1_17
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