Correlation testing in time series, spatial and cross-sectional data

Peter Robinson

LSE Research Online Documents on Economics from London School of Economics and Political Science, LSE Library

Abstract: We provide a general class of tests for correlation in time series, spatial, spatiotemporal and cross-sectional data. We motivate our focus by reviewing how computational and theoretical difficulties of point estimation mount as one moves from regularly-spaced time series data, through forms of irregular spacing, and to spatial data of various kinds. A broad class of computationally simple tests is justified. These specialize to Lagrange multiplier tests against parametric departures of various kinds. Their forms are illustrated in case of several models for describing correlation in various kinds of data. The initial focus assumes homoscedasticity, but we also robustify the tests to nonparametric heteroscedasticity.

JEL-codes: C21 C22 C29 (search for similar items in EconPapers)
Pages: 32 pages
Date: 2008-03
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Citations: View citations in EconPapers (36)

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