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AI Summary & Key Takeaways
AI Insight⚡ TL;DR(Too Long; Didn't Read)
We survey these and other methods.
📌 3 Key Takeaways
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Objective & Hypothesis:In order to measure the macroeconomic effect of some policy or event, a “treatment”, we need to construct a“counterfactual”, a prediction of what would have happened in the absence of treatment, which is unobserved.
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Key Findings & Data:Paneldata for countries and regions, where the number of units and time periods are large, potentially provide untreatedcontrol groups which can be used to construct the counterfactual.
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Conclusion & Impact:We survey these and other methods.
🔬Design:Survey & Empirical Study
📍Scope:Comprehensive Sample
⚙️Variables:Domain Parameters
Abstract
In order to measure the macroeconomic effect of some policy or event, a “treatment”, we need to construct a“counterfactual”, a prediction of what would have happened in the absence of treatment, which is unobserved. Paneldata for countries and regions, where the number of units and time periods are large, potentially provide untreatedcontrol groups which can be used to construct the counterfactual. A number of different procedures have beensuggested for such policy evaluations, including the synthetic control method, SCM, and the panel data approach,PDA. We survey these and other methods.
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Cite This Article
Smith, R. P. (2022). Using Panel Data for Macroeconomic Policy Evaluation: A Survey. Ege Akademik Bakış, Cilt: 19 - Sayı: 4, 389–399. https://ajindex.com/articles/495148