DOUBLE LENGTH ARTIFICIAL REGRESSIONS FOR TESTING SPATIAL DEPENDENCE

DOI10.1081/ETC-100104078zbMath1018.62049OpenAlexW2065546246MaRDI QIDQ4406234

No author found.

Publication date: 25 June 2003

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

Full work available at URL: https://doi.org/10.1081/etc-100104078

zbMATH Keywords

spatial dependencedouble length regressionsLagrange multplier

Mathematics Subject Classification ID

Directional data; spatial statistics (62H11) Linear regression; mixed models (62J05)

Related Items (14)

Panel data models with spatially correlated error components ⋮ HAC estimation in a spatial framework ⋮ The origin of spatial interaction ⋮ Artificial regression test diagnostics for impact measures in spatial models ⋮ Adjustments of Rao's score test for distributional and local parametric misspecifications ⋮ Double-length regression tests for testing functional forms and spatial error dependence ⋮ A Generalized Cross-Entropy Approach for Modeling Spatially Correlated Counts ⋮ Estimation of simultaneous systems of spatially interrelated cross sectional equations. ⋮ Simple regression‐based tests for spatial dependence ⋮ Specification and estimation of spatial autoregressive models with autoregressive and heteroskedastic disturbances ⋮ On Two-Step Estimation of a Spatial Autoregressive Model with Autoregressive Disturbances and Endogenous Regressors ⋮ Artificial regression testing in the GARCH‐in‐mean model ⋮ Testing for spatial lag and spatial error dependence using double length artificial regressions ⋮ Model selection and model averaging for matrix exponential spatial models

Cites Work

• The influence of sample size on the degree of redundancy in spatial lag operators
• Model Specification Tests Based on Artificial Linear Regressions
• Estimation Methods for Models of Spatial Interaction
• Unnamed Item

This page was built for publication: DOUBLE LENGTH ARTIFICIAL REGRESSIONS FOR TESTING SPATIAL DEPENDENCE