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Causal inference with observational data: Regression Discontinuity and related methods in Stata


  • Austin Nichols

    () (Urban Institute)


This overview of implementing quasi-experimental methods of estimating causal impacts (panel methods, matching estimators, instrumental variables, and regression discontinuity) emphasizes practical considerations and Stata-specific approaches, with examples using real data and comparisons across methods. Particular attention is paid to the regression discontinuity method, which seems to less well-known in the larger community of Stata users, but is the most well-regarded of the quasi-experimental methods in those circumstances where it is appropriate.

Suggested Citation

  • Austin Nichols, 2007. "Causal inference with observational data: Regression Discontinuity and related methods in Stata," North American Stata Users' Group Meetings 2007 2, Stata Users Group.
  • Handle: RePEc:boc:asug07:2

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    Cited by:

    1. Aldieri, Luigi & Vinci, Concetto Paolo, 2010. "An investigation of the relation between the number of children and education in Italy," MPRA Paper 28534, University Library of Munich, Germany.
    2. Mark Partridge & Tim Sass, 2011. "The productivity of elected and appointed officials: the case of school superintendents," Public Choice, Springer, vol. 149(1), pages 133-149, October.
    3. Martin Binder & Felix Ward, 2011. "The Structure of Happiness: A Vector Autoregressive Approach," Papers on Economics and Evolution 2011-08, Philipps University Marburg, Department of Geography.

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