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Confounding and control in a multivariate system. An issue in causal attribution

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Author Info

  • RUSSO, Federica

    ()
    (Dipartimento di Studi Umanistici, Università degli Studi di Ferrara, Italy)

  • MOUCHART, Michel

    ()
    (Université catholique de Louvain, ISBA and CORE, Belgium)

  • WUNSCH, Guillaume

    ()
    (Université catholique de Louvain, Demography, Belgium; Royal Academy of Sciences, Belgium)

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    Abstract

    It is widely agreed that, in establishing whether variable X causes variable Y, a third variable Z may confound the relation and thus hinder causal assessment. The solution developed within the ‘traditional’ framework is to control for any third variable, susceptible of confounding the relation between X and Y. This paper examines complex systems of variables, characterised by multiple causes and multiple effects. The paper advances the view that in such contexts confounding is a moot issue, under a suitable specification of the causal model. When networks of causal relations are considered, possible confounders are included in the appropriate causal paths from the causes to the outcome. The challenge for the model builder then amounts to developing a structural model that specifies the role of variables in each path, rather than just controlling for possible confounders.

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    File URL: http://uclouvain.be/cps/ucl/doc/core/documents/coredp2013_68web.pdf
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    Bibliographic Info

    Paper provided by Université catholique de Louvain, Center for Operations Research and Econometrics (CORE) in its series CORE Discussion Papers with number 2013068.

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    Date of creation: 31 Dec 2013
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    Handle: RePEc:cor:louvco:2013068

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    Related research

    Keywords: causality; confounding; control; structural modelling;

    This paper has been announced in the following NEP Reports:

    References

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    1. Michel Mouchart & Federica Russo & Guillaume Wunsch, 2010. "Inferrig Causal Relations by Modelling Structure," Statistica, Department of Statistics, University of Bologna, vol. 70(4), pages 411-432.
    2. Nigar Hashimzade & Jean Hindriks & Gareth D. Myles, 2006. "Solutions Manual to Accompany Intermediate Public Economics," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262582694, December.
    3. Roberto Impicciatore & Francesco Billari, 2010. "Secularization, union formation practices and marital stability: Evidence from Italy," Working Papers 026, "Carlo F. Dondena" Centre for Research on Social Dynamics (DONDENA), Università Commerciale Luigi Bocconi.
    4. WANG, Kent & WANG, Shin-Huei & PAN, Zheyao, 2013. "Can federal reserve policy deviation explain response patterns of financial markets over time?," CORE Discussion Papers 2013029, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    5. GABSZEWICZ, Jean & ZANAJ, Skerdilajda & ,, 2013. "(Un)stable vertical collusive agreements," CORE Discussion Papers 2013053, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    6. Manuel Förster & Ana Mauleon & Vincent J. Vannetelbosch, 2014. "Trust and Manipulation in Social Networks," Working Papers 2014.50, Fondazione Eni Enrico Mattei.
    7. Hindriks, Jean & Myles, Gareth D., 2013. "Intermediate Public Economics," MIT Press Books, The MIT Press, edition 2, volume 1, number 0262018691, December.
    8. Pearl Judea, 2013. "Linear Models: A Useful “Microscope” for Causal Analysis," Journal of Causal Inference, De Gruyter, vol. 1(1), pages 155-170, June.
    9. Guillaume Wunsch, 2007. "Confounding and control," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 16(4), pages 97-120, February.
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