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Graphical diagnostics of endogeneity
Umeå University, Faculty of Social Sciences, Department of Statistics.
Uppsala University.
2008 (English)In: Modelling and Evaluating Treatment Effects in Econometrics / [ed] Tom Fomby, R. Carter Hill, Daniel L. Millimet, Jeffrey A. Smith, Edward J. Vytlacil, Emerald Group Publishing Limited, 2008, 147-166 p.Chapter in book (Other academic)
Abstract [en]

We show that in sorting cross-sectional data, the endogeneity of a variable may be successfully detected by graphically examining the cumulative sum of the recursive residuals. Moreover, the sign of the bias implied by the endogeneity may be deducible through such graphs. In general, instrumental variables are needed to implement the graphical test. However, when a continuous or ordered (e.g. years of schooling) variable is suspected to be endogenous, a graphical test for misspecification due to endogeneity (e.g. self-selection) can be obtained without instrumental variables.

Place, publisher, year, edition, pages
Emerald Group Publishing Limited, 2008. 147-166 p.
Series
Advances in Econometrics, ISSN 0731-9053 ; 21
National Category
Economics and Business Probability Theory and Statistics
Identifiers
URN: urn:nbn:se:umu:diva-9638DOI: 10.1016/S0731-9053(07)00006-0ISI: 000270826900007ISBN: 978-0-7623-1380-8 (print)ISBN: 978-1-84950-523-9 (print)OAI: oai:DiVA.org:umu-9638DiVA: diva2:149309
Available from: 2008-05-06 Created: 2008-05-06 Last updated: 2013-07-04Bibliographically approved

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CiteExportLink to record
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Cite
Citation style
  • apa
  • ieee
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  • vancouver
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Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf