How do partly omitted control variables influence the averages used in meta-analysis in economics?
AbstractMeta regression analysis is used to extract the best average from a set of N primary studies of one economic parameter. Three averages of the N-set are discussed: The mean, the PET meta-average and the augmented meta-average. They are affected by control variables that are used in some of the primary studies. They are the POCs, partly omitted controls, of the meta-study. Some POCs are ceteris paribus controls chosen to make results from different data samples comparable. They should differ. Others are model variables. They may be true and should always be included, while others are false and should always be excluded, if only we knew. If POCs are systematically included for their effect on the estimate of the parameter, it gives publication bias. It is corrected by the meta-average. If a POC is randomly included, it gives a bias, which is corrected by the augmented meta-average. With many POCs very many augmentations are possible. The mean of all augmented meta-averages is also the mean of the N-set. If it has a publication bias so do the average augmented meta-averages.
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Bibliographic InfoPaper provided by School of Economics and Management, University of Aarhus in its series Economics Working Papers with number 2013-22.
Date of creation: 03 Oct 2013
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Meta-analysis; omitted variables; meta-average;
Find related papers by JEL classification:
- B4 - Schools of Economic Thought and Methodology - - Economic Methodology
- C9 - Mathematical and Quantitative Methods - - Design of Experiments
This paper has been announced in the following NEP Reports:
- NEP-ALL-2013-10-11 (All new papers)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
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Economics Working Papers
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