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Statistics and causal inference: A review

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  • Judea Pearl

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    File URL: http://hdl.handle.net/10.1007/BF02595718
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    Bibliographic Info

    Article provided by Springer in its journal Test.

    Volume (Year): 12 (2003)
    Issue (Month): 2 (December)
    Pages: 281-345

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    Handle: RePEc:spr:testjl:v:12:y:2003:i:2:p:281-345

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    Related research

    Keywords: Structural equation models; confounding; noncompliance; graphical methods; counterfactuals; 68T30;

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    References

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    1. repec:att:wimass:8909 is not listed on IDEAS
    2. Imbens, Guido W & Angrist, Joshua D, 1994. "Identification and Estimation of Local Average Treatment Effects," Econometrica, Econometric Society, vol. 62(2), pages 467-75, March.
    3. Barsky R. & Bound J. & Charles K.K. & Lupton J.P., 2002. "Accounting for the Black-White Wealth Gap: A Nonparametric Approach," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 663-673, September.
    4. Marianne Bertrand & Sendhil Mullainathan, 2003. "Are Emily and Greg More Employable than Lakisha and Jamal? A Field Experiment on Labor Market Discrimination," NBER Working Papers 9873, National Bureau of Economic Research, Inc.
    5. James J. Heckman & Jeffrey A. Smith, 1998. "Evaluating the Welfare State," NBER Working Papers 6542, National Bureau of Economic Research, Inc.
    6. Manski, Charles F, 1990. "Nonparametric Bounds on Treatment Effects," American Economic Review, American Economic Association, vol. 80(2), pages 319-23, May.
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    Cited by:
    1. Ballinger, Clint, 2011. "Why inferential statistics are inappropriate for development studies and how the same data can be better used," MPRA Paper 29780, University Library of Munich, Germany.
    2. Elena Stanghellini & Eduwin Pakpahan, 2013. "Identification of casual effects in linear models: beyond Instrumental Variables," Quaderni del Dipartimento di Economia, Finanza e Statistica 117/2013, Università di Perugia, Dipartimento Economia, Finanza e Statistica.

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