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<p>We argue that the fundamental issue of measuring treatment effects is to obtain good predictions of missing outcomes. However, there is no realized value to evaluate the quality of the predicted value generated by a particular method. The choice of prediction method has to rely on the compatibility of the observed data with the underlying assumptions of an approach and the predictive ability of the approach. In this paper, we selectively review some causal and non-causal approaches and discuss their limitations from this perspective.</p>

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A selective review of panel approaches to construct counterfactuals

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年4月24日

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  • Cheng Hsiao

摘要

We argue that the fundamental issue of measuring treatment effects is to obtain good predictions of missing outcomes. However, there is no realized value to evaluate the quality of the predicted value generated by a particular method. The choice of prediction method has to rely on the compatibility of the observed data with the underlying assumptions of an approach and the predictive ability of the approach. In this paper, we selectively review some causal and non-causal approaches and discuss their limitations from this perspective.