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https://hdl.handle.net/20.500.11779/1973
Title: | Understanding Covid-19 Mobility Through Human Capital: a Unified Causal Framework | Authors: | Bilgel, Fırat Karahasan, Burhan Can |
Keywords: | C36 Directed Acyclic Graphs Machine learning Causal structure discovery J68 Instrumental variables C14 Sample selection Do-calculus Workplace mobility J62 |
Publisher: | Springer | Source: | Bilgel, F., & Karahasan, B. C. (2023). Understanding Covid-19 Mobility Through Human Capital: A Unified Causal Framework. Computational Economics, 1-41. | 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. | URI: | https://hdl.handle.net/20.500.11779/1973 https://doi.org/10.1007/s10614-023-10359-6 |
ISSN: | 0927-7099 1572-9974 |
Appears in Collections: | Ekonomi Bölümü Koleksiyonu PubMed İndeksli Yayınlar Koleksiyonu / PubMed Indexed Publications Collection Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection |
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File | Description | Size | Format | |
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s10614-023-10359-6.pdf | Full Text- Article | 2.93 MB | Adobe PDF | View/Open |
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