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

Peter Robinson ()
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Peter Robinson: Institute for Fiscal Studies and London School of Economics

No CWP01/07, CeMMAP working papers from Centre for Microdata Methods and Practice, Institute for Fiscal Studies

Abstract:

We provide a general class of tests for correlation in time series, spatial, spatio-temporal 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 justiied. These specialize 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.

Keywords: Correlation; heteroscedasticity; Lagrange multiplier tests. (search for similar items in EconPapers)
JEL-codes: C21 C22 C29 (search for similar items in EconPapers)
Pages: 25 pp.
Date: 2007-01-01
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Citations: View citations in EconPapers (3)

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