Arbeitspapier

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

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.

Sprache
Englisch

Erschienen in
Series: cemmap working paper ; No. CWP01/07

Klassifikation
Wirtschaft
Single Equation Models; Single Variables: Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions
Single Equation Models; Single Variables: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
Single Equation Models; Single Variables: Other
Thema
Correlation , heteroscedasticity , Lagrange multiplier tests
Zeitreihenanalyse
Korrelation
Heteroskedastizität

Ereignis
Geistige Schöpfung
(wer)
Robinson, Peter
Ereignis
Veröffentlichung
(wer)
Centre for Microdata Methods and Practice (cemmap)
(wo)
London
(wann)
2007

DOI
doi:10.1920/wp.cem.2007.0107
Handle
Letzte Aktualisierung
12.07.2024, 13:21 MESZ

Objekttyp

  • Arbeitspapier

Beteiligte

  • Robinson, Peter
  • Centre for Microdata Methods and Practice (cemmap)

Entstanden

  • 2007

Ähnliche Objekte (12)