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<p>Social distancing policies have been widely used to curb the spread of infectious diseases such as COVID-19, but assessing their effectiveness is challenging. This study shows that widely-used methods to estimate the effects of such policies, like Two-way Fixed Effects and Difference-in-Differences, are highly sensitive to accounting, or failing to account, for the simultaneous adoption of policies and the presence of spillovers across geographies stemming from human movement. By estimating a series of nonparametric models on fine-grained mobility, epidemiological, and policy data from Mexico during the COVID-19 pandemic, this research shows that failing to consider confounders, interactions, and spillovers can change the magnitude and the sign of estimated policy effects, hampering the design of optimal public policies.</p>

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The impact of confounders, spillovers and interactions on social distancing policy effects estimates

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年10月2日

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  • José Ramón Enríquez,
  • Horacio Larreguy,
  • Alberto Simpser

摘要

Social distancing policies have been widely used to curb the spread of infectious diseases such as COVID-19, but assessing their effectiveness is challenging. This study shows that widely-used methods to estimate the effects of such policies, like Two-way Fixed Effects and Difference-in-Differences, are highly sensitive to accounting, or failing to account, for the simultaneous adoption of policies and the presence of spillovers across geographies stemming from human movement. By estimating a series of nonparametric models on fine-grained mobility, epidemiological, and policy data from Mexico during the COVID-19 pandemic, this research shows that failing to consider confounders, interactions, and spillovers can change the magnitude and the sign of estimated policy effects, hampering the design of optimal public policies.