COVID-19 restrictions and workplace mobility: Synthetic control analysis using Google data

Caro, Juan Carlos and Gutierrez-Lythgoe, Antonio and Molina, Jose Alberto (2025): COVID-19 restrictions and workplace mobility: Synthetic control analysis using Google data.

Abstract

The health mandated restrictions during the COVID-19 pandemic induced permanent changes in the economy and society worldwide. Transformation is mainly noticeable in economic sectors where daily tasks permit some degree of telework (e.g. call centers), and those which replaced in-person business (e.g. delivery services). COVID-19 restrictions in Europe implied a 160% increase in working from home (WFH), with a small decrease after mandated restrictions were removed. This paper employs synthetic control methods with Google data to analyze the casual impact of removing these restrictions on the workplace mobility in cities across four European countries (Spain, Italy, France and Sweden). Findings show a significant average fall of 6.3% in workplace mobility post-restriction relaxation. This result highlight associations with key factors such as COVID-19 cases, city population, sex-ratio, stringency index, and residential mobility, pointing towards a potential increase in remote work adoption. These findings underscore the intricate dynamics of workplace measures and their broader implications for evolving remote work trends.

• Item Type: MPRA Paper
• Language: English
• Keywords: Workplace mobility; Generalized synthetic control methods; Remote work; Google data
• Subjects: C - Mathematical and Quantitative Methods > C2 - Single Equation Models ; Single Variables > C21 - Cross-Sectional Models ; Spatial Models ; Treatment Effect Models ; Quantile Regressions; J - Labor and Demographic Economics > J2 - Demand and Supply of Labor > J22 - Time Allocation and Labor Supply

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