Finite sample power of Cliff–Ord-type tests for spatial disturbance correlation in linear regression |
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| Institution: | 1. Biosciences Research Division, Department of Environment and Primary Industries, Agribio, 5 Ring Road, Bundoora, VIC 3083, Australia;2. Dairy Futures Cooperative Research Centre, Bundoora, VIC 3083, Australia;3. Department of Animal Sciences, University of Wisconsin-Madison, WI 53706, USA;4. Department of Dairy Science, University of Wisconsin-Madison, WI 53706, USA;5. Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, WI 53706, USA;1. Faculty of Construction Management and Real Estate, International Research Center for Sustainable Built Environment, Chongqing University, Chongqing, China;2. School for Environment and Sustainability, University of Michigan, United States;3. Department of Real Estate and Construction, Faculty of Architecture, The University of Hong Kong, Pokfulam, Hong Kong;1. Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing 100084, China;2. Joint Center for Global Change Studies, Beijing 100875, China;1. School of Geographic Sciences, East China Normal University, Shanghai, 200241, China;2. Department of Tourism and Geography, Tongren University, Tongren, Guizhou Province, 554300, China;1. Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA;2. The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York City, NY, USA |
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| Abstract: | The paper considers tests against autocorrelation among the disturbances in linear regression models that can be expressed as ratios of quadratic forms. It shows that such tests are, in general, not unbiased and that power can even drop to zero for certain regressors and spatial weight matrices. Whether or not this can happen is however easily diagnosed for given regressors and for given spatial weights. |
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