The Use and Misuse of Summary Statistics in Regression Analysis

Robert V. Bishop

Journal of Agricultural Economics Research, 1981, vol. 33, issue 01, 6

Abstract: This article discusses the effect of an autocorrelated error structure on the interpretation of traditional significance tests, especially the t-test and R2 measure It emphasizes first-order serial correlation, a common and often serious problem that researchers using time series data may encounter Even though many of the problems associated with an autocorrelated error structure are well known, many researchers ignore them and report results which range from being potentially misleading to grossly erroneous

Keywords: Research and Development/Tech Change/Emerging Technologies; Research Methods/Statistical Methods (search for similar items in EconPapers)
Date: 1981
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Persistent link: https://EconPapers.repec.org/RePEc:ags:uersja:148702

DOI: 10.22004/ag.econ.148702

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