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The economics 'credibility revolution' has promoted the identification of causal relationships using difference-in-differences (DID), instrumental variables (IV), randomized control trials (RCT) and regression discontinuity design (RDD) methods. The extent to which a reader should trust claims...
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We use a rigorous three-stage many-analysts design to assess how different researcher decisions—specifically data cleaning, research design, and the interpretation of a policy question—affect the variation in estimated treatment effects. A total of 146 research teams each completed the same...
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significant and theory-confirming estimates for publication. Meta-regression models were originally developed for the synthesis of … statistically significant and theory-confirming estimates. Each regression specification may possibly suffer from biases such as … authors of primary studies search for statistically significant and theory-confirming estimates, meta-regression models tend …
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-hacking or publication bias, in particular for articles using DID or IV as causal identification method. We show that a crucial … then find no evidence for p-hacking or publication bias in the DID and pooled data, but evidence remains for IV …
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Traditionally, social scientists perceived causality as regularity. As a consequence, qualitative comparative case study research was regarded as unsuitable for drawing causal inferences since a few cases cannot establish regularity. The dominant perception of causality has changed, however....
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