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Experimental designs for identifying causal mechanisms


  • Kosuke Imai
  • Dustin Tingley
  • Teppei Yamamoto


No abstract is available for this item.

Suggested Citation

  • Kosuke Imai & Dustin Tingley & Teppei Yamamoto, 2013. "Experimental designs for identifying causal mechanisms," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 176(1), pages 5-51, January.
  • Handle: RePEc:bla:jorssa:v:176:y:2013:i:1:p:5-51
    DOI: 10.1111/rssa.2012.176.issue-1

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    Cited by:

    1. Markus Frölich & Martin Huber, 2017. "Direct and indirect treatment effects–causal chains and mediation analysis with instrumental variables," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 79(5), pages 1645-1666, November.
    2. Acharya, Avidit & Blackwell, Matthew & Sen, Maya, 2016. "Explaining Causal Findings Without Bias: Detecting and Assessing Direct Effects," American Political Science Review, Cambridge University Press, vol. 110(3), pages 512-529, August.
    3. Kellie Ottoboni & Jason Poulos, 2019. "Estimating population average treatment effects from experiments with noncompliance," Papers 1901.02991,, revised Aug 2019.
    4. repec:eee:ecolec:v:165:y:2019:i:c:2 is not listed on IDEAS
    5. Michela Baccini & Alessandra Mattei & Fabrizia Mealli, 2015. "Bayesian inference for causal mechanisms with application to a randomized study for postoperative pain control," Econometrics Working Papers Archive 2015_06, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    6. Martin Huber, 2015. "Causal Pitfalls in the Decomposition of Wage Gaps," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(2), pages 179-191, April.
    7. Guanglei Hong & Jonah Deutsch & Heather D. Hill, 2013. "Ratio-of-Mediator-Probability Weighting for Causal Mediation Analysis in the Presence of Treatment-by-Mediator Interaction," Working Papers 2013-009, Human Capital and Economic Opportunity Working Group.
    8. Strobl, Renate & Wunsch, Conny, 2018. "Identification of causal mechanisms based on between-subject double randomization designs," CEPR Discussion Papers 13028, C.E.P.R. Discussion Papers.
    9. Baldwin Kate & Bhavnani Rikhil R., 2015. "Ancillary Studies of Experiments: Opportunities and Challenges," Journal of Globalization and Development, De Gruyter, vol. 6(1), pages 113-146, June.
    10. Eva Deuchert & Martin Huber & Mark Schelker, 2016. "Direct and Indirect Effects Based on Difference-in-Differences with an Application to Political Preferences Following the Vietnam Draft Lottery," CESifo Working Paper Series 6000, CESifo Group Munich.
    11. Huber, Martin, 2012. "Identifying causal mechanisms in experiments (primarily) based on inverse probability weighting," Economics Working Paper Series 1213, University of St. Gallen, School of Economics and Political Science, revised May 2013.
    12. Martin Huber, 2016. "Disentangling policy effects into causal channels," IZA World of Labor, Institute of Labor Economics (IZA), pages 259-259, May.
    13. Robert B. Lount & Oliver J. Sheldon & Floor Rink & Katherine W. Phillips, 2015. "Biased Perceptions of Racially Diverse Teams and Their Consequences for Resource Support," Organization Science, INFORMS, vol. 26(5), pages 1351-1364, October.
    14. repec:eee:jbrese:v:99:y:2019:i:c:p:306-318 is not listed on IDEAS
    15. repec:eee:jouret:v:91:y:2015:i:4:p:569-585 is not listed on IDEAS
    16. Ward, Jeffrey T. & Hartley, Richard D. & Tillyer, Rob, 2016. "Unpacking gender and racial/ethnic biases in the federal sentencing of drug offenders: A causal mediation approach," Journal of Criminal Justice, Elsevier, vol. 46(C), pages 196-206.
    17. Baldwin, Kate & Bhavnani, Rikhil R., 2013. "Ancillary Experiments: Opportunities and Challenges," WIDER Working Paper Series 024, World Institute for Development Economic Research (UNU-WIDER).

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