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Replication data for: Statistical analysis of endorsement experiments: Measuring support for militant groups in Pakistan

Harvard Dataverse (Africa Rice Center, Bioversity International, CCAFS, CIAT, IFPRI, IRRI and WorldFish)

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Title Replication data for: Statistical analysis of endorsement experiments: Measuring support for militant groups in Pakistan
 
Identifier https://doi.org/10.7910/DVN/DQ23DN
 
Creator Will Bullock
Kosuke Imai
Jacob Shapiro
 
Publisher Harvard Dataverse
 
Description Political scientists have long been interested in citizens' support level for socially sensitive actors such as ethnic minorities, militant groups, and authoritarian regimes. Attempts to use direct questioning in surveys, however, have largely yielded unreliable measures of these attitudes as they are contaminated by social desirability bias and high non-response rates. In this paper, we develop a statistical methodology to analyze endorsement experiments, which recently have been proposed as a possible solution to this measurement problem. The commonly used statistical methods are problematic because they cannot properly combine responses across multiple policy questions, the design feature of a typical endorsement experiment. We overcome this limitation by using item response theory to estimate support levels on the same scale as the ideal points of respondents. We also show how to extend our model to incorporate a hierarchical structure of data in order to recoup the loss of statistical eciency due to indirect questioning. We illustrate the proposed methodology by applying it to measure political support for Islamist milita
nt groups in Pakistan. Simulation studies suggest that the proposed Bayesian model yields estimates with reasonable levels of bias and statistical power. Finally, we oer several practical suggestions for improving the design and analysis of endorsement experiments.