Work From Home, Worry Less?

Abstract

Workers in occupations that cannot be performed remotely — the half of the global workforce in retail, hospitality, construction, healthcare delivery, and manufacturing — experienced sharper increases in self-reported anxiety during the first six months of the COVID-19 pandemic than workers in remote-capable jobs, even after conditioning on country-level case counts and policy stringency. The Open Science Framework COVID-19 survey, fielded across 177 countries from March 2020 onward, documents this gap at the individual level.

The behavioural-economics construct best placed to explain the residual is the **dual-process anxiety response to occupational uncertainty**: under high-uncertainty conditions, anxiety is generated less by realised income loss than by anticipated, hard-to-quantify catastrophic-outcome risk. Teleworkability — the structural property of a job that determines whether it can be performed from home — mechanically reduces the salience of one specific catastrophic-outcome category (workplace infection) and so should buffer anxiety differentially across occupations. The Dingel-Neiman occupational-teleworkability index provides a measurable exogenous job-property that varies across the respondent pool.

The existing analysis applies the classical identification stack: country fixed-effects + GMM dynamic-panel estimation, quantile regression (capturing distributional effects of the buffer), and Oaxaca-Blinder decomposition. Using 102,369 respondents (after listwise deletion from 113,083 raw) across 151 countries, merged with Johns Hopkins case counts and the Oxford Stringency Index, the estimates document a teleworkability effect on anxiety that survives the standard country-FE specification.

We propose extending the existing analysis with two ML layers: a Double-ML estimator that would partial out the 50+ country-level controls using LightGBM nuisance learners, producing standard errors valid under far weaker assumptions on the controls, and a Causal Forest CATE estimator that would recover the conditional teleworkability effect across sector × country-income-group strata. The proposed extensions would convert the population-average buffer estimate into occupational-targeting evidence for mental-health policy during future pandemic shocks.

Data & Methods