The Use and Misuse of Summary Statistics in Regression Analysis

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


Issue Date:
1981-01
Publication Type:
Journal Article
Record Identifier:
http://ageconsearch.umn.edu/record/148702
PURL Identifier:
http://purl.umn.edu/148702
Published in:
Agricultural Economics Research, Volume 33, Number 1
Page range:
13-18
Total Pages:
6




 Record created 2017-04-01, last modified 2018-01-22

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