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rego: Stata module for decomposing goodness of fit according to Owen and Shapley values

Author

Listed:
  • Frank Huettner

    (Universität Leipzig, Institut für Empirische Wirtschaftsforschung)

  • Marco Sunder

    (Universität Leipzig, Institut für Empirische Wirtschaftsforschung)

Abstract

Decomposition of the goodness of fit to (groups of) regressor variables can be a useful diagnostic tool to quickly assess “relative importance†. Owen and Shapley values, two closely related solutional concepts in cooperative game theory, provide unique solutions to the decomposition exercise on the basis of a sound set of assumptions. At this stage, the new command rego implements decomposition of R-squared in OLS regression, based on the covariance matrix of the data for fast computation in the Mata environment. It also allows for bootstrapping the outcomes. Inclusion of other measures of fit and classes of models is planned for future extensions.

Suggested Citation

  • Frank Huettner & Marco Sunder, 2012. "rego: Stata module for decomposing goodness of fit according to Owen and Shapley values," United Kingdom Stata Users' Group Meetings 2012 17, Stata Users Group.
    • Handle: RePEc:boc:usug12:17
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    10. Marina Cavalieri & Rossana Cristaudo & Livio Ferrante & Calogero Guccio, 2019. "Does the Project Design Matter for the Performance of Infrastructure Execution? An Assessment for Italy," Italian Economic Journal: A Continuation of Rivista Italiana degli Economisti and Giornale degli Economisti, Springer;Società Italiana degli Economisti (Italian Economic Association), vol. 5(1), pages 39-77, March.
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