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Statistics and causal inference: A review

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  • Judea Pearl

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  • Judea Pearl, 2003. "Statistics and causal inference: A review," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 12(2), pages 281-345, December.
    • Handle: RePEc:spr:testjl:v:12:y:2003:i:2:p:281-345
    DOI: 10.1007/BF02595718
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    References listed on IDEAS

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    1. Manski, Charles F, 1990. "Nonparametric Bounds on Treatment Effects," American Economic Review, American Economic Association, vol. 80(2), pages 319-323, May.
    2. O. Ashenfelter & D. Card (ed.), 1999. "Handbook of Labor Economics," Handbook of Labor Economics, Elsevier, edition 1, volume 3, number 3.
    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. Imbens, Guido W & Angrist, Joshua D, 1994. "Identification and Estimation of Local Average Treatment Effects," Econometrica, Econometric Society, vol. 62(2), pages 467-475, March.
    5. Marianne Bertrand & Sendhil Mullainathan, 2004. "Are Emily and Greg More Employable Than Lakisha and Jamal? A Field Experiment on Labor Market Discrimination," American Economic Review, American Economic Association, vol. 94(4), pages 991-1013, September.
    6. James J. Heckman & Jeffrey A. Smith, 1998. "Evaluating the Welfare State," NBER Working Papers 6542, National Bureau of Economic Research, Inc.
    7. Altonji, Joseph G. & Blank, Rebecca M., 1999. "Race and gender in the labor market," Handbook of Labor Economics, in: O. Ashenfelter & D. Card (ed.), Handbook of Labor Economics, edition 1, volume 3, chapter 48, pages 3143-3259, Elsevier.
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    Cited by:

    1. Elena Stanghellini & Eduwin Pakpahan, 2015. "Identification of causal effects in linear models: beyond instrumental variables," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 24(3), pages 489-509, September.
    2. Federico Castelletti & Guido Consonni, 2020. "Discovering causal structures in Bayesian Gaussian directed acyclic graph models," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(4), pages 1727-1745, October.
    3. Víctor Casero-Alonso & Jesús López-Fidalgo, 2015. "Optimal designs subject to cost constraints in simultaneous equations models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 24(4), pages 701-713, December.
    4. Yongjun Chen & Xiaojian Li & Jin Wang & Mei Liu & Chaoxun Cai & Yuefeng Shi, 2023. "Research on the Application of Fuzzy Bayesian Network in Risk Assessment of Catenary Construction," Mathematics, MDPI, vol. 11(7), pages 1-19, April.
    5. 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.
    6. Federico Castelletti & Alessandro Mascaro, 2021. "Structural learning and estimation of joint causal effects among network-dependent variables," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 30(5), pages 1289-1314, December.
    7. Fazia Abdat & Sylvie Leclercq & Xavier Cuny & Claire Tissot, 2014. "Extracting recurrent scenarios from narrative texts using a Bayesian network: Application to serious occupational accidents with movement disturbance," Post-Print hal-01578382, HAL.
    8. Steven M. Shugan, 2007. "—Causality, Unintended Consequences and Deducing Shared Causes," Marketing Science, INFORMS, vol. 26(6), pages 731-741, 11-12.

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