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Unpacking the Black Box of Causality: Learning about Causal Mechanisms from Experimental and Observational Studies

  • DOI:
  • Published online: 10 November 2011

Identifying causal mechanisms is a fundamental goal of social science. Researchers seek to study not only whether one variable affects another but also how such a causal relationship arises. Yet commonly used statistical methods for identifying causal mechanisms rely upon untestable assumptions and are often inappropriate even under those assumptions. Randomizing treatment and intermediate variables is also insufficient. Despite these difficulties, the study of causal mechanisms is too important to abandon. We make three contributions to improve research on causal mechanisms. First, we present a minimum set of assumptions required under standard designs of experimental and observational studies and develop a general algorithm for estimating causal mediation effects. Second, we provide a method for assessing the sensitivity of conclusions to potential violations of a key assumption. Third, we offer alternative research designs for identifying causal mechanisms under weaker assumptions. The proposed approach is illustrated using media framing experiments and incumbency advantage studies.

Corresponding author
Kosuke Imai is Associate Professor, Department of Politics, Princeton University, Corwin Hall 036, Princeton NJ 08544 (
Luke Keele is Assistant Professor, Department of Political Science, Pennsylvania State University, 211 Pond Lab, University Park, PA 16802 (
Dustin Tingley is Assistant Professor, Department of Government, Harvard University, 1737 Cambridge Street, CGIS Knafel Building 208, Cambridge MA 02138 (
Teppei Yamamoto is Assistant Professor, Department of Political Science, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139 (
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This list contains references from the content that can be linked to their source. For a full set of references and notes please see the PDF or HTML where available.

J. Albert 2008. “Mediation Analysis via Potential Outcomes Models.” Statistics in Medicine 27: 12821304.

J. D. Angrist , G. W. Imbens , and D. B. Rubin . 1996. “Identification of Causal Effects Using Instrumental Variables (with Discussion).” Journal of the American Statistical Association 91 (434): 444–55.

S. Ansolabehere , E. C. Snowberg , and J. M. Snyder . 2006. “Television and the Incumbency Advantage in U.S. Elections.” Legislative Studies Quarterly 31 (4): 469–90.

S. Ansolabehere , J. M. Snyder , and C. Stewart . 2000. “Old Voters, New Voters, and the Personal Vote: Using Redistricting to Measure the Incumbency Advantage.” American Journal of Political Science 44 (1): 1734.

R. M. Baron , and D. A. Kenny . 1986. “The Moderator–Mediator Variable Distinction in Social Psychological Research: Conceptual, Strategic, and Statistical Considerations.” Journal of Personality and Social Psychology 51 (6): 1173–82.

M. Bertrand , and S. Mullainathan . 2004. “Are Emily and Greg More Employable Than Lakisha and Jamal? A Field Experiment on Labor Market Discrimination.” American Economic Review 94 (4): 9911013.

T. Brader , N. A. Valentino , and E. Suhay . 2008. “What Triggers Public Opposition to Immigration? Anxiety, Group Cues, and Immigration.” American Journal of Political Science 52 (4): 959–78.

J. Bullock , D. Green , and S. Ha . 2010. “Yes, But What's the Mechanism? (Don't Expect an Easy Answer).” Journal of Personality and Social Psychology 98 (4): 550–58.

D. Chong , and J. Druckman . 2007. “Framing Theory.” Annual Review of Political Science 10: 103–26.

S. R. Cole , and C. E. Frangakis . 2009. “The Consistency Statement in Causal Inference: A Definition or Assumption?Epidemiology 20 (1): 35.

G. W. Cox , and J. N. Katz . 1996. “Why Did the Incumbency Advantage in U.S. House Elections Grow?American Journal of Political Science 40 (2): 478–97.

A. Deaton 2010a. “Instruments, Randomization, and Learning about Development.” Journal of Economic Literature 48 (2): 424–55.

A. Deaton 2010b. “Understanding the Mechanisms of Economic Development.” Journal of Economic Perspectives 24 (3): 316.

R. S. Erikson , and T. R. Palfrey . 1998. “Campaign Spending and Incumbency: An Alternative Simultaneous Equations Approach.” Journal of Politics 60 (2): 355–73.

S. K. Gadarian 2010. “The Politics of Threat: How Terrorism News Shapes Foreign Policy Attitudes.” Journal of Politics 72 (2): 469–83.

A. Gelman , and G. King . 1990. “Estimating Incumbency Advantage without Bias.” American Journal of Political Science 34 (4): 1142–64.

D. P. Green , S. E. Ha , and J. G. Bullock . 2010. “Enough Already about Black Box Experiments: Studying Mediation Is More Difficult Than Most Scholars Suppose.” Annals of the American Academy of Political and Social Sciences 628 (1): 200–08.

J. J. Gross , and R. W. Levenson . 1995. “Eliciting Emotions Using Films.” Cognition and Emotion 9 (1): 87108.

T. Haavelmo 1943. “The Statistical Implications of a System of Simultaneous Equations.” Econometrica 11: 112.

J. J. Heckman , and J. A. Smith . 1995. “Assessing the Case for Social Experiments.” Journal of Economic Perspectives 9 (2): 85110.

D. E. Ho , K. Imai , G. King , and E. A. Stuart . 2007. “Matching as Nonparametric Preprocessing for Reducing Model Dependence in Parametric Causal Inference.” Political Analysis 15 (3): 199236.

P. W. Holland 1986. “Statistics and Causal Inference.” Journal of the American Statistical Association 81: 945–60.

P. W. Holland 1988. “Causal Inference, Path Analysis, and Recursive Structural Equations Models.” Sociological Methodology 18: 449–84.

Y. Horiuchi , K. Imai , and N. Taniguchi . 2007. “Designing and Analyzing Randomized Experiments: Application to a Japanese Election Survey Experiment.” American Journal of Political Science 51 (3): 669–87.

K. Imai , L. Keele , and D. Tingley . 2010. “A General Approach to Causal Mediation Analysis.” Psychological Methods 15 (4): 309–34.

K. Imai , L. Keele , D. Tingley and T. Yamamoto . 2010. “Causal Mediation Analysis Using R”. In Advances in Social Science Research Using R, ed. H. D. Vinod , Lecture Notes in Statistics. Springer-verlag: New York, 129–54.

K. Imai , L. Keele , and T. Yamamoto . 2010. “Identification, Inference, and Sensitivity Analysis for Causal Mediation Effects.” Statistical Science 25 (1): 5171.

K. Imai , G. King , and E. A. Stuart . 2008. “Misunderstandings among Experimentalists and Observationalists about Causal Inference.” Journal of the Royal Statistical Society, Series A (Statistics in Society) 171 (2): 481502.

K. Imai , and T. Yamamoto . 2010. “Causal Inference with Differential Measurement Error: Nonparametric Identification and Sensitivity Analysis.” American Journal of Political Science 54 (2): 543–60.

L. Isbell , and V. Ottati . 2002. “The Emotional Voter.” In The Social Psychology of Politics, ed. V. Ottati , New York: Kluwer, 5574.

B. Jo 2008. “Causal Inference in Randomized Experiments with Mediational Processes.” Psychological Methods 13 (4): 314–36.

J. T. Jost , J. L. Napier , H. Thorisdottir , S. D. Gosling , T. P. Palfai , and B. Ostafin . 2007. “Are Needs to Manage Uncertainty and Threat Associated With Political Conservatism or Ideological Extremity?Personality and Social Psychology Bulletin 33 (7): 9891007.

G. King , M. Tomz , and J. Wittenberg . 2000. “Making the Most of Statistical Analyses: Improving Interpretation and Presentation.” American Journal of Political Science 44: 341–55.

S. D. Levitt and C. D. Wolfram . 1997. “Decomposing the Sources of Incumbency Advantage in the U.S. House.” Legislative Studies Quarterly 22 (1): 4560.

D. MacKinnon , C. Lockwood , C. Brown , W. Wang , and J. Hoffman . 2007. “The Intermediate Endpoint Effect in Logistic and Probit Regression.” Clinical Trials 4: 499513.

J. M. Miller , and J. A. Krosnick . 2000. “News Media Impact on the Ingredients of Presidential Evaluations: Politically Knowledgeable Citizens Are Guided by a Trusted Source.” American Journal of Political Science 44 (2): 301–15.

T. E. Nelson , and D. R. Kinder . 1996. “Issue Frames and Group-centrism in American Public Opinion.” The Journal of Politics 58 (4): 1055–78.

A. Olsson , J. P. Ebert , M. R. Banaji , and E. A. Phelps . 2005. “The Role of Social Groups in the Persistence of Learned Fear.” Science 309 (5735): 785–87.

D. R. Oxley , K. B. Smith , J. R. Alford , M. V. Hibbing , J. L. Miller , M. Scalora , P. K. Hatemi , and J. R. Hibbing . 2008. “Political Attitudes Vary with Physiological Traits.” Science 321 (5896): 1667–70.

M. L. Petersen , S. E. Sinisi , and M. J. van der Laan . 2006. “Estimation of Direct Causal Effects.” Epidemiology 17 (3): 276–84.

M. Prior 2006. “The Incumbent in the Living Room: The Rise of Television and the Incumbency Advantage in U.S. House Elections.” Journal of Politics 68 (3): 657–73.

J. M. Robins , and S. Greenland . 1992. “Identifiability and Exchangeability for Direct and Indirect Effects.” Epidemiology 3 (2): 143–55.

D. B. Rubin 1974. “Estimating Causal Effects of Treatments in Randomized and Non-randomized Studies.” Journal of Educational Psychology 66: 688701.

A. Sjölander 2009. “Bounds on Natural Direct Effects in the Presence of Confounded Intermediate Variables.” Statistics in Medicine 28 (4): 558–71.

M. E. Sobel 1982. “Asymptotic Confidence Intervals for Indirect Effects in Structural Equation Models.” Sociological Methodology 13: 290321.

M. E. Sobel 2008. “Identification of Causal Parameters in Randomized Studies with Mediating Variables.” Journal of Educational and Behavioral Statistics 33 (2): 230–51.

S. Spencer , M. Zanna , and G. Fong . 2005. “Establishing a Causal Chain: Why Experiments Are Often More Effective Than Mediational Analyses in Examining Psychological Processes.” Journal of Personality and Social Psychology 89 (6): 845–51.

L. Z. Tiedens and S. Linton . 2001. “Judgment under Emotional Certainty and Uncertainty: The Effects of Specific Emotions on Information Processing.” Journal of Personality and Social Psychology 81 (6): 973–88.

T. J. VanderWeele 2009. “Marginal Structural Models for the Estimation of Direct and Indirect Effects.” Epidemiology 20 (1): 1826.

T. J. VanderWeele and J. M. Robins . 2009. “Minimal Sufficient Causation and Directed Acyclic Graphs.” Annals of Statistics 37 (3): 1437–65.

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American Political Science Review
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