Robinson, Peter (2008) Correlation testing in time series, spatial and cross-sectional data. Journal of Econometrics, 147 (1). pp. 5-16. ISSN 0304-4076
Full text not available from this repository.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 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.
Item Type: | Article |
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Official URL: | http://www.elsevier.com/wps/find/journaldescriptio... |
Additional Information: | © 2008 Elsevier B.V. |
Divisions: | Economics |
Subjects: | H Social Sciences > HB Economic Theory Q Science > QA Mathematics |
JEL classification: | C - Mathematical and Quantitative Methods > C2 - Econometric Methods: Single Equation Models; Single Variables > C21 - Cross-Sectional Models; Spatial Models; Treatment Effect Models C - Mathematical and Quantitative Methods > C2 - Econometric Methods: Single Equation Models; Single Variables > C22 - Time-Series Models C - Mathematical and Quantitative Methods > C2 - Econometric Methods: Single Equation Models; Single Variables > C29 - Other |
Date Deposited: | 15 Apr 2011 15:45 |
Last Modified: | 13 Nov 2024 00:08 |
URI: | http://eprints.lse.ac.uk/id/eprint/35687 |
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