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Paper

Identification, Inference, and Sensitivity Analysis for Causal Mediation Effects Imai, Kosuke Keele, Luke Yamamoto, Teppei Uploaded 07-20-2009 Keywords causal inference causal mediation analysis direct and indirect eects linear structural equation models sequential ignorability unmeasured confounders Abstract Causal mediation analysis is routinely conducted by applied researchers in a variety of disciplines including epidemiology, political science, psychology, and sociology. The goal of such an analysis is to investigate alternative causal mechanisms by examining the roles of intermediate variables that lie in the causal path between the treatment and outcome variables. In this paper, we first prove that under a particular version of sequential ignorability assumption, the average causal mediation effect (ACME) is nonparametrically identified. We compare our identifying assumption with those proposed in the literature. Some practical implications of our identification result are also discussed. In particular, the popular estimator based on the linear structural equation model (LSEM) can be interpreted as an ACME estimator if the linearity and no-interaction assumptions are satisfied in addition to the proposed assumption. We show that this assumption can easily be relaxed within the framework of LSEM. Second, we consider a simple nonparametric estimator of the ACME in order to relax distributional and functional form assumptions. We also discuss a more general nonparametric approach. Third, we propose a new sensitivity analysis that can be easily implemented by applied researchers within the standard LSEM framework. Like the existing identifying assumptions, the proposed assumption may be too strong in many applied settings. Thus, sensitivity analysis is essential in order to examine the robustness of empirical findings to the possible existence of an unmeasured confounder. Finally, we apply the proposed methods to a randomized experiment from political psychology.

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Paper

Why Process Matters for Causal Inference Glynn, Adam Quinn, Kevin Uploaded 07-13-2009 Keywords causal effect process post-treatment mechanism mediation potential outcomes Abstract It is often assumed that the only way to assess the causal effects of an explanatory variable on an outcome variable is to compare the outcomes from units with differing values of the explanatory variable. In this paper, we provide a formal account of how within-unit causal process information (i.e., knowledge of the causal chain linking an explanatory variable to an outcome variable) can be used to make certain types of causal inferences without comparing outcomes from units with differing values of the explanatory variable. The methods discussed in this paper allow causal researchers to make full use of causal information that many had heretofore ignored. At the same time, because these methods are embedded in a Bayesian potential outcomes causal model, researchers are held to high standards of transparency and logical consistency. We illustrate these methods with an application to the effects of election day registration on African American turnout. This analysis shows that previous regression or matching estimates for these effects are likely overstated.

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Paper

Unpacking the Black Box: Learning about Causal Mechanisms from Experimental and Observational Studies Imai, Kosuke Keele, Luke Tingley, Dustin Yamamoto, Teppei Uploaded 07-01-2010 Keywords causal inference direct and indirect effects mediation moderation potential outcomes sensitivity analysis media cues incumbency effects Abstract Understanding causal mechanisms is a fundamental goal of social science research. Demonstrating whether one variable causes a change in another is often insufficient, and researchers seek to explain why such a causal relationship arises. Nevertheless, little is understood about how to identify causal mechanisms in empirical research. Many researchers either informally talk about possible causal mechanisms or attempt to quantify them without explicitly stating the required assumptions. Often, some assert that process tracing in detailed case studies is the only way to evaluate causal mechanisms. Others contend the search for causal mechanisms is so elusive that we should instead focus on causal effects alone. In this paper, we show how to learn about causal mechanisms from experimental and observational studies. Using the potential outcomes framework of causal inference, we formally define causal mechanisms, present general identification and estimation strategies, and provide a method to assess the sensitivity of one's conclusions to the possible violations of key identification assumptions. We also propose several alternative research designs for both experimental and observational studies that may help identify causal mechanisms under less stringent assumptions. The proposed methodology is illustrated using media framing experiments and observational studies of incumbency advantage.

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Paper

Conflict and Mediation Event Observations (CAMEO): A New Event Data Framework for the Analysis of Foreign Policy Interactions Schrodt, Philip A. Gerner, Deborah J. Abu-Jabr, Rajaa Yilmaz, Omur Uploaded 04-01-2002 Keywords event data mediation WEIS Middle East Balkans West Africa Abstract The Conflict and Mediation Events Observations (CAMEO) framework is a new event data coding scheme optimized for the study of third-party mediation in international disputes. We have developed and implemented this system using the TABARI automated coding program, and have generated data sets for the Balkans (1989-2002; N=69,620), Levant (1979-2002; N=146,283), and West Africa (1989-2002; N=17,468) from Reuters and Agence France Presse reports. We describe why we decided to develop a new coding system, rather than continuing to use the World Events Interaction Survey (WEIS) framework that we have used in earlier work. Our decision involved both known weaknesses in the WEIS system, and some additional problems that we have found occur when WEIS is coded using automated methods. We have addressed these problems in constructing CAMEO, as well as producing much more completed documentation than has been available for WEIS. In this paper, we make several statistical comparisons of CAMEO-coded and WEIS-coded data in the three geographical regions. When the data are aggregated to a general behavioral levelÑverbal cooperation, material cooperation, verbal conflict and material conflictÑmost of the data sets show a high correlation (r>0.90) in the number of WEIS and CAMEO events coded per month. However, as we expected, CAMEO consistently picks up a greater number of events involving material cooperation. CAMEO and WEIS show similar irregularities in the distribution of events by category. Finally, there is a very significant correlation (r>0.57) between the count of CAMEO events specifically dealing with mediation and negotiation, and a pattern-based measure of mediation we developed earlier from WEIS data. Appendices in the paper show the CAMEO coding framework and examples from the codebook.

5

Paper

Analyzing the dynamics of international mediation processes Schrodt, Philip A. Gerner, Deborah J. Uploaded 07-16-2001 Keywords event data cross-correlation mediation Cox proportional hazard pattern recognition Abstract This paper presents initial results from a project that will formally test a number of the hypotheses embedded in the theoretical and qualitative literatures on mediation, using automated coding of event data from news-wire sources. In contrast to most of the existing quantitative literature, which emphasizes the structural aspects of mediation, we will focus on the dynamics. The initial part of the paper focuses on two issues of design. First, we discuss the advantages of generating data using fully automated methods, which increases the transparency and replicability of the research. This transparency is extended to the development of more complex variables that cannot be captured as single events: these are defined as pattern of the underlying event data. We also suggest that these can be usefully studied using conventional inferential statistics rather than computational pattern recognition. Second, we justify the "statistical case study" approach which focuses on a small number of cases that are limited in geographical and temporal scope. While the risk of this approach is that one will find patterns of behavior that apply only in those circumstances, we point out that the more conventional large-N time-series cross-sectional studies also carry inferential risks. The statistical tests reported in this paper look at three different issues using data on the Israel-Lebanon and Israel-Palestinian conflicts in the Levant (1979-1999), and the Serbia-Croatia and Serbia-Bosnia conflicts in the Balkans (1991-1999). First, cross- correlation is used to look at the effects of mediation on the level of violence over time. Second, we test the "sticks-or-carrots" hypothesis on whether mediation is more effective in reducing violence if accompanied by cooperative or conflictual behavior by the mediator. Finally, we estimate Cox proportional hazard models to assess the factors that influence (1) whether mediation is accepted by the parties in a conflict, (2) whether formal agreements are reached, and (3) whether the agreements reduce the level of conflict. Future work in the project involves development of a new event coding scheme specifically designed for the study of mediation, and expansion of the list of cases to include other mediated conflicts in the Middle East and West Africa.

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Paper

Analyzing the Dynamics of International Mediation Processess in the Middle East and the former Yugoslavia Gerner, Deborah J. Schrodt, Philip A. Uploaded 06-28-2001 Keywords mediation event data cross-correlation conflict Middle East Abstract This paper discusses a new National Science Foundation-funded project that will examine the dynamics of third-party international mediation using statistical time-series analyses of political event data. Third-party mediation was attempted in over half of the conflicts in the post-WWII period and it is likely that the use of mediation has increased following the end of the Cold War. Surprisingly, there have been few systematic studies on mediation. Those that do exist have generally focused on relatively static contextual factors such as the the conflict's attributes and the prior relationship between the mediator and protagonists rather than on dynamic factors' both contextual and process that may contribute to the success or failure of mediation activities. In contrast, the extensive qualitative literature provides numerous hypotheses about dynamic aspects of mediation. This, however, primarily consists of case studies, often by mediation practitioners, that exhibit little cumulation and, when taken as a whole, are rife with contradictory assertions. The project will formally test a number of the hypotheses embedded in the theoretical and qualitative literatures on mediation, using automated coding of event data from news-wire sources and employing time-series and event- history methods. A system of specialized event codes that a sensitive to mediation activities will be developed, then events will be coded from news reports using the TABARI machine coding program. The research will look at the factors that influence (1) whether mediation is accepted by the parties in a conflict, (2) whether formal agreements are reached, and (3) whether the agreements actually reduce the level of conflict. The project will initially focus on conflicts in the Middle East, a region where the principal investigators have substantial field experience. After refining the statistical tests on the Middle East case, the analysis will be extended to event data on conflicts in the former Yugoslavia and West Africa. The paper presents the results of an empirical "plausibility probe" based on existing WEIS-coded event data for the Levant and the former Yugoslavia. It employs a simple measure of third-party mediation efforts as the independent variables and Goldstein-scaled cooperation as the dependent variable. In the Levant, we find a weak but consistent pattern of mediation correlating with past conflictual activity, and resulting in later increases in cooperation. In the former Yugoslavia, the analysis shows strikingly different results for the mediation efforts the UN, European states, and the US. All three respond to increased conflict, but the UN efforts correlate with greater conflict, the US efforts with greater cooperation, and the European efforts have no effect. These results are consistent with many of the qualitative assessments of these efforts, and suggest that the event data approach will produce credible results

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Paper

Detecting United States Mediation Styles in the Middle East, 1979-1998 Schrodt, Philip A. Uploaded 03-04-1999 Keywords event data mediation Middle East time series hidden Markov models Abstract This research is part of the "Multiple Paths to Knowledge Project" sponsored by the James A. Baker III Institute for Public Policy, Rice University, and the Program in Foreign Policy Decision Making, Texas A&M University. The paper deals with the problem of determining whether the mediation styles used by four U.S. Secretaries of State -- George Schultz, James Baker, Warren Christopher and Madeline Albright -- are sufficiently distinct that they can be detected in event data. The mediation domain is the Israel-Palestinian conflict from April 1979 to December 1998, the event data are coded from the Reuters news service reports using the WEIS event coding scheme, and the classification technique is hidden Markov models. The models are estimated for each of the four Secretaries based on 16 randomly chosen 32-events sequences of USA>ISR and USA>PAL events during the term of the Secretary. Each month in the data set is then assigned to one of the four Secretarial styles based on the best-fitting model. The models differentiate the mediation styles quite distinctly and this method of detecting styles yields quite different results when applied to ISR-PAL data or random data. The "Baker" and "Albright" styles are most distinctive; the "Schultz" style is least; both results are consistent with many qualitative characterizations of these periods. A series of t-tests is then done on Goldstein-scaled scores to determine whether the mediation styles translate into statistically distinct interactions in the ISR>USA, ISR>PAL, PAL>USA and PAL>ISR dyads. While there are a number of statistically-significant differences when the full sample is used, these may be due simply to the overall changes Israel-Palestinian relations over the course of the time series. When tests are done on months that are out-of-term -- in other words, where the style of one Secretary is being employed during the term of another -- few statistically-significant differences are found, though there is someindication of a lag of a month or so between the change in style and the behavioral response. It appears that the effects of the differing styles are not captured by changes in aggregated data, possibly because these scales force behavior into a single conflict-cooperation dimension. Consistent with other papers in the "Multiple Paths to Knowledge" project, the paper contains commentary on how the research project was actually done, as well as the conventional presentation of results. The file includes the papers in Postscript and PDF formats, the event data (Levant, April 1979 to December 1998) used in the analysis, the C source code for estimating the hidden Markov models. This paper was presented at the International Studies Association meetings, Washington, 16-21 February 1999

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Poster

Economic Voting: Causal Mediation of Retrospective Evaluations Becher, Michael Donnelly, Michael Uploaded 08-15-2010 Keywords Economic Voting Causal Mediation Mediation Incumbency Retrospective Evaluations Ideology Abstract In this paper, we show that an increase in economic growth has a positive effect on the share of voters who support the party of the chief executive and that it does this through retrospective evaluations of the economy. In order to do this, we expand on the results of Duch and Stevenson (2005, 2008). Using causal mediation analysis, we show that an increase in economic growth leads to an increase in the number of survey respondents whose retrospective evaluations of the economy are positive. This, in turn, leads to an increase in the number of voters who support the party of the chief executive. A similar result holds using annual unemployment change as the treatment. In both cases, the effect is weaker when the chief executive is a member of a coalition. The evidence for existence of mediation effects is robust to the inclusion or exclusion of a number of control variables, including an interaction between individual ideology and government ideology.