Model invariance when estimating random parameters with categorical variables

Michael Burton

No 273051, Working Papers from University of Western Australia, School of Agricultural and Resource Economics

Abstract: This paper shows that econometric models that include categorical variables are not invariant to choice of ‘base’ category when random parameters are estimated, unless they are allowed to be correlated. We show that the invariance can lead to significant increases in Type I errors, and distortions in the implied behaviour of respondents. We hypothesise that these biases may influence the economic policy implications of published models that contain this error, but it’s impossible to be sure without re-estimating the model correctly.

Keywords: Research; Methods/; Statistical; Methods (search for similar items in EconPapers)
Pages: 11
Date: 2018-05-12
New Economics Papers: this item is included in nep-ecm
References: Add references at CitEc
Citations: View citations in EconPapers (5)

Downloads: (external link)
https://ageconsearch.umn.edu/record/273051/files/WP1804.pdf (application/pdf)
https://ageconsearch.umn.edu/record/273051/files/WP1804.pdf?subformat=pdfa (application/pdf)

Related works:
Working Paper: Model invariance when estimating random parameters with categorical variables (2019)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ags:uwauwp:273051

DOI: 10.22004/ag.econ.273051

Access Statistics for this paper

More papers in Working Papers from University of Western Australia, School of Agricultural and Resource Economics Contact information at EDIRC.
Bibliographic data for series maintained by AgEcon Search ().