Front Matter
  • 1 0000000404811396https://isni.org/isni/0000000404811396International Monetary Fund

Front Matter Page

Statistics Department

Contents

  • 1 Introduction

  • 2 The COVID-19 crises in Italy, Portugal, and Spain

  • 3 A unique dataset

  • 4 Heterogeneous effects on mobility across gender

    • 4.1 Regression discontinuity

    • 4.2 Local projections

  • 5 Heterogeneous effects on mobility across age groups

    • 5.1 Regression discontinuity

    • 5.2 Local projections

  • 6 Robustness

  • 7 Conclusions

  • References

  • A Lockdown stringency dynamics

  • List of Figures

    • 1 Mobility Levels from Apple, Google, and Vodafone

    • 2 Mobility and Lockdown Stringency

    • 3 Impact of Stay-at-Home Orders on Mobility, by Gender

    • 4 Impact of School Closures and Stay-at-Home Orders in Northern Italy

    • 5 Impact of a Full Lockdown on Mobility, by Gender

    • 6 Impact of a Doubling of COVID-19 Cases on Mobility, by Gender

    • 7 Impact of a Stay-at-Home Orders on Mobility, by Age

    • 8 Impact of a Full Lockdown on Mobility, by Age Group

    • 9 Impact of a Doubling of COVID-19 Cases on Mobility, by Age Group

    • 10 Impact of Lockdowns and COVID-19 Cases using Full Sample

    • 11 Impact of Lockdowns and COVID-19 Cases using Day-of-the-Week Fixed Effects

    • 12 Impact of Lockdowns and COVID-19 Cases Excluding Portugal

    • 13 Impact of Lockdowns and COVID-19 Cases Excluding Spain

    • A.1 Lockdown Stringency Dynamics

  • List of Tables

    • 1 RD Estimate of the Gender Gap by Age Group

    • 2 Gender Gap at the Trough of the Estimated Response

    • 3 Robustness of the RD Results by Gender

    • 4 Robustness of the RD Results by Gender across Provinces

    • 5 Robustness of the RD Results by Age

    • 6 Robustness of the RD results by Age across Provinces

Mobility under the COVID-19 Pandemic: Asymmetric Effects across Gender and Age
Author: Mr. Francesco Caselli, Mr. Francesco Grigoli, Mr. Damiano Sandri, and Mr. Antonio Spilimbergo