A Synthetic Business Cycle Approach to Counterfactual Analysis with Nonstationary Macroeconomic Data----系统科学研究所

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A Synthetic Business Cycle Approach to Counterfactual Analysis with Nonstationary Macroeconomic Data

主讲人：奚晋助理研究员
时间：2025年10月15日上午11:00—11:30 地点：数学院南楼N204

【报告摘要】This paper investigates the use of synthetic control methods for causal inference in macroeconomic settings when dealing with possibly nonstationary data. While the synthetic control approach has gained popularity for estimating counterfactual outcomes, we caution researchers against assuming a common nonstationary trend factor across units for macroeconomic outcomes, as doing so may result in misleading causal estimation—a pitfall we refer to as the spurious synthetic control problem. To address this issue, we propose a synthetic business cycle framework that explicitly separates trend and cyclical components. By leveraging the treated unit's historical data to forecast its trend and using control units only for cyclical fluctuations, our strategy eliminates spurious correlations and improves the robustness of counterfactual prediction in macroeconomic applications. As empirical illustrations, we examine the cases of German reunification and the handover of Hong Kong, demonstrating the advantages of the proposed approach.

【报告人简介】中国科学院数学与系统科学研究院预测科学研究中心助理研究员。毕业于加州大学圣地亚哥分校，主要研究方向为计量经济学，相关成果发表在Journal of Business & Economic Statistics，Social Choice and Welfare。

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