Understanding Covid-19 Mobility Through Human Capital: A Unified Causal Framework

Fırat Bilgel () and Burhan Karahasan
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Fırat Bilgel: MEF University

Computational Economics, 2024, vol. 63, issue 2, No 12, 793-833

Abstract: Abstract This paper seeks to identify the causal impact of educational human capital on social distancing behavior at workplace in Turkey using district-level data for the period of April 2020 - February 2021. We adopt a unified causal framework, predicated on domain knowledge, theory-justified constraints anda data-driven causal structure discovery using causal graphs. We answer our causal query by employing machine learning prediction algorithms; instrumental variables in the presence of latent confounding and Heckman’s model in the presence of selection bias. Results show that educated regions are able to distance-work and educational human capital is a key factor in reducing workplace mobility, possibly through its impact on employment. This pattern leads to higher workplace mobility for less educated regions and translates into higher Covid-19 infection rates. The future of the pandemic lies in less educated segments of developing countries and calls for public health action to decrease its unequal and pervasive impact.

Keywords: Workplace mobility; Causal structure discovery; Do-calculus; Machine learning; Instrumental variables; Sample selection; J62; J68; C14; C36 (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s10614-023-10359-6

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