1990 | OriginalPaper | Buchkapitel
*Correlated Errors
verfasst von : Ashish Sen, Muni Srivastava
Erschienen in: Regression Analysis
Verlag: Springer New York
Enthalten in: Professional Book Archive
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Continuing with our examination of violations of Gauss-Markov conditions, in this chapter we examine the case where7.1 $$E(\in \in ') = {\sigma ^2}\Omega$$ could be non-diagonal; i.e., some E(∈j∈j)’s may be non-zero even when i ≠ j. Cases of this kind do occur with some frequency. For example, observations of the same phenomena (e.g., per capita income) taken over time are often correlated (serial correlation), observations (e.g., of median rent) from points or zones in space that are close together are often more alike than observations taken from points further apart (spatial correlation), and observations from the same production run or using the same laboratory equipment often have more semblance than those from distinct runs.