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This study provides new mechanisms for identifying and estimating explosive bubbles in mixed-root panel autoregressions …$-means clustering algorithm can correctly recover latent group membership in data of this type and the proposed post-clustering panel … with a latent group structure. A post-clustering approach is employed that combines a recursive $k$-means clustering …
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Inference for estimates of treatment effects with clustered data requires great care when treatment is assigned at the group level. This is true for both pure treatment models and difference-in-differences regressions. Even when the number of clusters is quite large, cluster-robust standard...
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In many fields of economics, and also in other disciplines, it is hard to justify the assumption that the random error terms in regression models are uncorrelated. It seems more plausible to assume that they are correlated within clusters, such as geographical areas or time periods, but...
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-means objective to regression settings. As the regularization parameter m approaches 1, the fuzzy clustering objective converges to …
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