Testing for Spatial Autocorrelation: The Regressors that Make the Power Disappear

DOI10.1080/07474938.2011.553571zbMath1491.62063OpenAlexW1992914617MaRDI QIDQ5080146

Federico Martellosio

Publication date: 31 May 2022

Published in: Econometric Reviews (Search for Journal in Brave)

Full work available at URL: http://centaur.reading.ac.uk/17917/1/Martellosio-MS2008088%282%29.pdf

zbMATH Keywords

powerpoint optimal testsspatial lag modelspatial error modelCliff-Ord testspatial unit root

Mathematics Subject Classification ID

Applications of statistics to economics (62P20) Inference from spatial processes (62M30) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Linear regression; mixed models (62J05) Hypothesis testing in multivariate analysis (62H15)

Related Items (max. 100)

HOW TO AVOID THE ZERO-POWER TRAP IN TESTING FOR CORRELATION ⋮ ON THE POWER OF INVARIANT TESTS FOR HYPOTHESES ON A COVARIANCE MATRIX ⋮ Higher-order least squares inference for spatial autoregressions

Cites Work

• Unnamed Item
• Unnamed Item
• Specification and estimation of spatial autoregressive models with autoregressive and heteroskedastic disturbances
• Finite sample power of Clifford-type tests for spatial disturbance correlation in linear regres\-sion
• A test for spatial autocorrelation in seemingly unrelated regressions
• Regression with strongly correlated data
• Spatial lag test with equal weights
• Robust tests for spherical symmetry and their application to least squares regression
• NONTESTABILITY OF EQUAL WEIGHTS SPATIAL DEPENDENCE
• SERIAL CORRELATION IN REGRESSION ANALYSIS. I
• RANDOM EFFECTS AND SPATIAL AUTOCORRELATION WITH EQUAL WEIGHTS
• Matrix Analysis
• Linear Models with Exchangeably Distributed Errors
• Note on a Condition for Equality of Sample Variances in a Linear Model
• The Power of the Durbin-Watson Test
• Efficiency of least squares estimators in the presence of spatial autocorrelation
• Algebraic Graph Theory
• Regression Models with Spatially Correlated Errors
• POWER PROPERTIES OF INVARIANT TESTS FOR SPATIAL AUTOCORRELATION IN LINEAR REGRESSION
• Testing Statistical Hypotheses
• Normal Multivariate Analysis and the Orthogonal Group
• On the asymptotic distribution of the Moran \(I\) test stastistic with applications

This page was built for publication: Testing for Spatial Autocorrelation: The Regressors that Make the Power Disappear