IDEAS home Printed from https://ideas.repec.org/a/bla/jecsur/v36y2022i1p214-234.html
   My bibliography  Save this article

Causal mediation analysis in economics: Objectives, assumptions, models

Author

Listed:
  • Viviana Celli

Abstract

Mediation analysis aims at identifying and evaluating the mechanisms through which treatment affects an outcome. The goal is to disentangle the total treatment effect into two components: the indirect effect that occurs due to one or more intermediate variables, known as mediators, and the direct effect that captures all other possible explanations for why a treatment works. This paper reviews the methodological advancements in the literature on causal mediation in economics, specifically quasi‐experimental designs. I define the parameters of interest, the main assumptions and the identification strategies under the counterfactual approach, and present the Instrumental Variables (IV), Difference‐in‐Differences (DID), and Synthetic Control (SC) methods.

Suggested Citation

  • Viviana Celli, 2022. "Causal mediation analysis in economics: Objectives, assumptions, models," Journal of Economic Surveys, Wiley Blackwell, vol. 36(1), pages 214-234, February.
    • Handle: RePEc:bla:jecsur:v:36:y:2022:i:1:p:214-234
    DOI: 10.1111/joes.12452
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/joes.12452
    Download Restriction: no
    File URL: https://libkey.io/10.1111/joes.12452?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Viviana Celli, 2020. "Identification of Causal Mechanisms through an RD Approach," Working Papers 15/20, Sapienza University of Rome, DISS.
    2. Constantine E. Frangakis & Donald B. Rubin, 2002. "Principal Stratification in Causal Inference," Biometrics, The International Biometric Society, vol. 58(1), pages 21-29, March.
    3. James J. Heckman & Rodrigo Pinto, 2015. "Econometric Mediation Analyses: Identifying the Sources of Treatment Effects from Experimentally Estimated Production Technologies with Unmeasured and Mismeasured Inputs," Econometric Reviews, Taylor & Francis Journals, vol. 34(1-2), pages 6-31, February.
    4. Adam N. Glynn, 2012. "The Product and Difference Fallacies for Indirect Effects," American Journal of Political Science, John Wiley & Sons, vol. 56(1), pages 257-269, January.
    5. Giorgio Brunello & Margherita Fort & Nicole Schneeweis & Rudolf Winter‐Ebmer, 2016. "The Causal Effect of Education on Health: What is the Role of Health Behaviors?," Health Economics, John Wiley & Sons, Ltd., vol. 25(3), pages 314-336, March.
    6. Sandra E. Black & Paul J. Devereux & Kjell G. Salvanes, 2005. "The More the Merrier? The Effect of Family Size and Birth Order on Children's Education," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 120(2), pages 669-700.
    7. Keele, Luke & Tingley, Dustin & Teppei Yamamoto, "undated". "Identifying Mechanisms behind Policy Interventions via Causal Mediation Analysis," Working Paper 135661, Harvard University OpenScholar.
    8. Powdthavee, Nattavudh & Lekfuangfu, Warn N. & Wooden, Mark, 2013. "The Marginal Income Effect of Education on Happiness: Estimating the Direct and Indirect Effects of Compulsory Schooling on Well-Being in Australia," IZA Discussion Papers 7365, Institute of Labor Economics (IZA).
    9. Imai, Kosuke & Keele, Luke & Tingley, Dustin & Yamamoto, Teppei, 2011. "Unpacking the Black Box of Causality: Learning about Causal Mechanisms from Experimental and Observational Studies," American Political Science Review, Cambridge University Press, vol. 105(4), pages 765-789, November.
    10. 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.
    11. Andrew Gelman & Guido Imbens, 2013. "Why ask Why? Forward Causal Inference and Reverse Causal Questions," NBER Working Papers 19614, National Bureau of Economic Research, Inc.
    12. Govert E. Bijwaard & Andrew M. Jones, 2019. "An IPW estimator for mediation effects in hazard models: with an application to schooling, cognitive ability and mortality," Empirical Economics, Springer, vol. 57(1), pages 129-175, July.
    13. Flores, Carlos A. & Flores-Lagunes, Alfonso, 2009. "Identification and Estimation of Causal Mechanisms and Net Effects of a Treatment under Unconfoundedness," IZA Discussion Papers 4237, Institute of Labor Economics (IZA).
    14. James J. Heckman, 2008. "Econometric Causality," International Statistical Review, International Statistical Institute, vol. 76(1), pages 1-27, April.
    15. Heckman, James & Pinto, Rodrigo, 2015. "Causal Analysis After Haavelmo," Econometric Theory, Cambridge University Press, vol. 31(1), pages 115-151, February.
    16. Hendry,David F. & Morgan,Mary S., 1997. "The Foundations of Econometric Analysis," Cambridge Books, Cambridge University Press, number 9780521588706.
    17. Martin Huber & Andreas Steinmayr, 2021. "A Framework for Separating Individual-Level Treatment Effects From Spillover Effects," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(2), pages 422-436, March.
    18. Luke Keele & Dustin Tingley & Teppei Yamamoto, 2015. "Identifying Mechanisms Behind Policy Interventions Via Causal Mediation Analysis," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 34(4), pages 937-963, September.
    19. Gardner, Jonathan & Oswald, Andrew J., 2007. "Money and mental wellbeing: A longitudinal study of medium-sized lottery wins," Journal of Health Economics, Elsevier, vol. 26(1), pages 49-60, January.
    20. 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.
    21. Ted Brader & Nicholas A. Valentino & Elizabeth Suhay, 2008. "What Triggers Public Opposition to Immigration? Anxiety, Group Cues, and Immigration Threat," American Journal of Political Science, John Wiley & Sons, vol. 52(4), pages 959-978, October.
    22. Rosenzweig, Mark R & Wolpin, Kenneth I, 1980. "Testing the Quantity-Quality Fertility Model: The Use of Twins as a Natural Experiment," Econometrica, Econometric Society, vol. 48(1), pages 227-240, January.
    23. 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.
    24. James Heckman & Rodrigo Pinto & Peter Savelyev, 2013. "Understanding the Mechanisms through Which an Influential Early Childhood Program Boosted Adult Outcomes," American Economic Review, American Economic Association, vol. 103(6), pages 2052-2086, October.
    25. Joshua Angrist & Victor Lavy & Analia Schlosser, 2010. "Multiple Experiments for the Causal Link between the Quantity and Quality of Children," Journal of Labor Economics, University of Chicago Press, vol. 28(4), pages 773-824, October.
    26. Guido W. Imbens & Jeffrey M. Wooldridge, 2009. "Recent Developments in the Econometrics of Program Evaluation," Journal of Economic Literature, American Economic Association, vol. 47(1), pages 5-86, March.
    27. Martin Huber & Michael Lechner & Giovanni Mellace, 2017. "Why Do Tougher Caseworkers Increase Employment? The Role of Program Assignment as a Causal Mechanism," The Review of Economics and Statistics, MIT Press, vol. 99(1), pages 180-183, March.
    28. M. Angelucci & V. Di Maro, 2016. "Programme evaluation and spillover effects," Journal of Development Effectiveness, Taylor & Francis Journals, vol. 8(1), pages 22-43, March.
    29. Guido W. Imbens, 2004. "Nonparametric Estimation of Average Treatment Effects Under Exogeneity: A Review," The Review of Economics and Statistics, MIT Press, vol. 86(1), pages 4-29, February.
    30. Mikael Lindahl, 2005. "Estimating the Effect of Income on Health and Mortality Using Lottery Prizes as an Exogenous Source of Variation in Income," Journal of Human Resources, University of Wisconsin Press, vol. 40(1).
    31. Philip Oreopoulos, 2006. "Estimating Average and Local Average Treatment Effects of Education when Compulsory Schooling Laws Really Matter," American Economic Review, American Economic Association, vol. 96(1), pages 152-175, March.
    32. Sara Geneletti, 2007. "Identifying direct and indirect effects in a non‐counterfactual framework," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 69(2), pages 199-215, April.
    33. Jeffrey M. Albert & Suchitra Nelson, 2011. "Generalized Causal Mediation Analysis," Biometrics, The International Biometric Society, vol. 67(3), pages 1028-1038, September.
    34. Eva Deuchert & Martin Huber & Mark Schelker, 2019. "Direct and Indirect Effects Based on Difference-in-Differences With an Application to Political Preferences Following the Vietnam Draft Lottery," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 37(4), pages 710-720, October.
    35. Marianne Simonsen & Lars Skipper, 2006. "The costs of motherhood: an analysis using matching estimators," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(7), pages 919-934, November.
    36. Ruth Miquel, 2002. "Identification of Dynamic Treatment Effects by Instrumental Variables," University of St. Gallen Department of Economics working paper series 2002 2002-11, Department of Economics, University of St. Gallen.
    37. Thomas R. Ten Have & Marshall M. Joffe & Kevin G. Lynch & Gregory K. Brown & Stephen A. Maisto & Aaron T. Beck, 2007. "Causal Mediation Analyses with Rank Preserving Models," Biometrics, The International Biometric Society, vol. 63(3), pages 926-934, September.
    38. VanderWeele, Tyler J., 2008. "Simple relations between principal stratification and direct and indirect effects," Statistics & Probability Letters, Elsevier, vol. 78(17), pages 2957-2962, December.
    39. Abadie, Alberto & Diamond, Alexis & Hainmueller, Jens, 2010. "Synthetic Control Methods for Comparative Case Studies: Estimating the Effect of California’s Tobacco Control Program," Journal of the American Statistical Association, American Statistical Association, vol. 105(490), pages 493-505.
    40. 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.
    41. James J. Heckman, 2008. "Causalidad econométrica," Monetaria, CEMLA, vol. 0(3), pages 291-338, julio-sep.
    42. Giovanni Mellace & Alessandra Pasquini, 2019. "Identify More, Observe Less: Mediation Analysis Synthetic Control," CEIS Research Paper 474, Tor Vergata University, CEIS, revised 20 Nov 2019.
    43. Huber, Martin, 2019. "A review of causal mediation analysis for assessing direct and indirect treatment effects," FSES Working Papers 500, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
    44. Lars Skipper & Marianne Simonsen, 2006. "The costs of motherhood: an analysis using matching estimators," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(7), pages 919-934.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Mazzocchi, Mario & Capacci, Sara & Biondi, Beatrice, 2022. "Causal inference on the impact of nutrition policies using observational data," Bio-based and Applied Economics Journal, Italian Association of Agricultural and Applied Economics (AIEAA), vol. 11(1), April.
    2. Abel, Martin & Brown, Willa, 2022. "Prosocial behavior in the time of COVID-19: The effect of private and public role models," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 101(C).
    3. Katarzyna A. Bilicka & Irem Guceri & Evangelos Koumanakos, 2022. "Dividend Taxation and Firm Performance with Heterogeneous Payout Responses," NBER Working Papers 30808, National Bureau of Economic Research, Inc.
    4. Manuel Salas-Velasco, 2022. "Causal Effects of Financial Education Intervention Aimed at University Students on Financial Knowledge and Financial Self-Efficacy," JRFM, MDPI, vol. 15(7), pages 1-16, June.
    5. Jiawei Fu, 2024. "Extract Mechanisms from Heterogeneous Effects: Identification Strategy for Mediation Analysis," Papers 2403.04131, arXiv.org, revised Apr 2024.
    6. Guo, Xu & Li, Runze & Liu, Jingyuan & Zeng, Mudong, 2023. "Statistical inference for linear mediation models with high-dimensional mediators and application to studying stock reaction to COVID-19 pandemic," Journal of Econometrics, Elsevier, vol. 235(1), pages 166-179.
    7. Haisen Wang & Gangqiang Yang & Ziyang Yue, 2023. "Breaking through ingrained beliefs: revisiting the impact of the digital economy on carbon emissions," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-13, December.
    8. Juliana Sanchez-Ariza, 2022. "Conflict, parenting, and early childhood mental health in conflict-affected settings: Evidence from Colombia," Documentos CEDE 20639, Universidad de los Andes, Facultad de Economía, CEDE.
    9. Brent J. Davis & Tarek Jaber‐Lopez, 2023. "Do voluntary commitment mechanisms improve welfare? The effect of mandatory and voluntary oaths in a social dilemma," Bulletin of Economic Research, Wiley Blackwell, vol. 75(2), pages 525-540, April.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Viviana Celli, 2019. "Causal Mediation Analysis in Economics: objectives, assumptions, models," Working Papers 12/19, Sapienza University of Rome, DISS.
    2. Martin Huber & Mark Schelker & Anthony Strittmatter, 2022. "Direct and Indirect Effects based on Changes-in-Changes," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(1), pages 432-443, January.
    3. 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.
    4. repec:hhs:ifauwp:2025_012 is not listed on IDEAS
    5. Helmut Farbmacher & Martin Huber & Lukáš Lafférs & Henrika Langen & Martin Spindler, 2022. "Causal mediation analysis with double machine learning [Mediation analysis via potential outcomes models]," The Econometrics Journal, Royal Economic Society, vol. 25(2), pages 277-300.
    6. Martin Huber & Michael Lechner & Giovanni Mellace, 2017. "Why Do Tougher Caseworkers Increase Employment? The Role of Program Assignment as a Causal Mechanism," The Review of Economics and Statistics, MIT Press, vol. 99(1), pages 180-183, March.
    7. Martin Huber & Yu‐Chin Hsu & Ying‐Ying Lee & Layal Lettry, 2020. "Direct and indirect effects of continuous treatments based on generalized propensity score weighting," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(7), pages 814-840, November.
    8. Huber, Martin & Steinmayr, Andreas, 2017. "A framework for separating individual treatment effects from spillover, interaction, and general equilibrium effects," FSES Working Papers 481, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
    9. Wunsch, Conny & Strobl, Renate, 2018. "Identification of causal mechanisms based on between-subject double randomization designs," CEPR Discussion Papers 13028, C.E.P.R. Discussion Papers.
    10. James J. Heckman & Rodrigo Pinto, 2022. "Causality and Econometrics," NBER Working Papers 29787, National Bureau of Economic Research, Inc.
    11. Martin Huber & Anna Solovyeva, 2020. "Direct and Indirect Effects under Sample Selection and Outcome Attrition," Econometrics, MDPI, vol. 8(4), pages 1-25, December.
    12. 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.
    13. Martin Huber & Michael Lechner & Giovanni Mellace, 2016. "The Finite Sample Performance of Estimators for Mediation Analysis Under Sequential Conditional Independence," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(1), pages 139-160, January.
    14. Eva Deuchert & Martin Huber & Mark Schelker, 2019. "Direct and Indirect Effects Based on Difference-in-Differences With an Application to Political Preferences Following the Vietnam Draft Lottery," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 37(4), pages 710-720, October.
    15. Martin Huber & Anna Solovyeva, 2020. "On the Sensitivity of Wage Gap Decompositions," Journal of Labor Research, Springer, vol. 41(1), pages 1-33, June.
    16. Martin Huber & Lukáš Lafférs, 2022. "Bounds on direct and indirect effects under treatment/mediator endogeneity and outcome attrition," Econometric Reviews, Taylor & Francis Journals, vol. 41(10), pages 1141-1163, November.
    17. James J. Heckman & Rodrigo Pinto, 2023. "Econometric Causality: The Central Role of Thought Experiments," NBER Working Papers 31945, National Bureau of Economic Research, Inc.
    18. Hsu Yu-Chin & Huber Martin & Lai Tsung-Chih, 2019. "Nonparametric estimation of natural direct and indirect effects based on inverse probability weighting," Journal of Econometric Methods, De Gruyter, vol. 8(1), pages 1-20, January.
    19. Christian Dippel & Robert Gold & Stephan Heblich & Rodrigo Pinto, 2017. "Instrumental Variables and Causal Mechanisms: Unpacking the Effect of Trade on Workers and Voters," CESifo Working Paper Series 6816, CESifo.
    20. Huber Martin & Wüthrich Kaspar, 2019. "Local Average and Quantile Treatment Effects Under Endogeneity: A Review," Journal of Econometric Methods, De Gruyter, vol. 8(1), pages 1-27, January.
    21. Kilburn, Kelly & Handa, Sudhanshu & Angeles, Gustavo & Mvula, Peter & Tsoka, Maxton, 2017. "Short-term impacts of an unconditional cash transfer program on child schooling: Experimental evidence from Malawi," Economics of Education Review, Elsevier, vol. 59(C), pages 63-80.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bla:jecsur:v:36:y:2022:i:1:p:214-234. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: http://www.blackwellpublishing.com/journal.asp?ref=0950-0804 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.