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Smart access and smart protection for welfare gain in Europe during COVID‐19: An empirical investigation using real‐time data

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  • Humaira Kamal Pasha

Abstract

The COVID‐19 (Coronoavirus Disease 2019) pandemic has had many disastrous effects on welfare globally, particularly in European countries. In recent research, a new debate has arisen as a result of the shift of day‐to‐day activities to virtual platforms, which has augmented concerns related to smart (data) access and smart (data) protection. This study examines the economic, social, and psychological indicators of welfare gain within the context of the COVID‐19 pandemic and examines their impact on smart access and smart protection using the data of Survey of Health, Ageing and Retirement in Europe and real‐time Google Trends from June to August 2020. The findings indicate a negative relationship between smart access and economic crisis caused by COVID‐19, while households with sufficient resources support smart protection. Psychological effects including nervousness and anxiety are highly related to smart access. Likewise, being helpful in a time of uncertainty, societal contact, and social measures (hygiene and face mask) significantly and positively impact smart protection. The findings suggest that countries should combine their welfare agencies with health and economic institutes, and initiate projects related to cybersecurity.

Suggested Citation

  • Humaira Kamal Pasha, 2024. "Smart access and smart protection for welfare gain in Europe during COVID‐19: An empirical investigation using real‐time data," Bulletin of Economic Research, Wiley Blackwell, vol. 76(1), pages 41-66, January.
    • Handle: RePEc:bla:buecrs:v:76:y:2024:i:1:p:41-66
    DOI: 10.1111/boer.12414
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    1. Supriya Garikipati & Uma Kambhampati, 2021. "Leading the Fight Against the Pandemic: Does Gender Really Matter?," Feminist Economics, Taylor & Francis Journals, vol. 27(1-2), pages 401-418, April.
    2. Chen, Xudong & Huang, Bihong & Lin, Chin-Te, 2019. "Environmental awareness and environmental Kuznets curve," Economic Modelling, Elsevier, vol. 77(C), pages 2-11.
    3. A. Colin Cameron & Jonah B. Gelbach & Douglas L. Miller, 2011. "Robust Inference With Multiway Clustering," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 29(2), pages 238-249, April.
    4. Celidoni, Martina & Dal Bianco, Chiara & Weber, Guglielmo, 2017. "Retirement and cognitive decline. A longitudinal analysis using SHARE data," Journal of Health Economics, Elsevier, vol. 56(C), pages 113-125.
    5. Alessia Naccarato & Andrea Pierini & Stefano Falorsi, 2015. "Using Google Trend Data To Predict The Italian Unemployment Rate," Departmental Working Papers of Economics - University 'Roma Tre' 0203, Department of Economics - University Roma Tre.
    6. Massimiliano Bratti, 2003. "Labour force participation and marital fertility of Italian women: The role of education," Journal of Population Economics, Springer;European Society for Population Economics, vol. 16(3), pages 525-554, August.
    7. Kun-Huang Huarng & Tiffany Hui-Kuang Yu & Maria Rodriguez-Garcia, 2020. "Qualitative analysis of housing demand using Google trends data," Economic Research-Ekonomska Istraživanja, Taylor & Francis Journals, vol. 33(1), pages 2007-2017, January.
    8. Johan Swinnen & Rob Vos, 2021. "COVID‐19 and impacts on global food systems and household welfare: Introduction to a special issue," Agricultural Economics, International Association of Agricultural Economists, vol. 52(3), pages 365-374, May.
    9. Christian Montag & Harald Baumeister & Christopher Kannen & Rayna Sariyska & Eva-Maria Meßner & Matthias Brand, 2019. "Concept, Possibilities and Pilot-Testing of a New Smartphone Application for the Social and Life Sciences to Study Human Behavior Including Validation Data from Personality Psychology," J, MDPI, vol. 2(2), pages 1-14, March.
    10. Wei-Po Chou & Peng-Wei Wang & Shiou-Lan Chen & Yu-Ping Chang & Chia-Fen Wu & Wei-Hsin Lu & Cheng-Fang Yen, 2020. "Voluntary Reduction of Social Interaction during the COVID-19 Pandemic in Taiwan: Related Factors and Association with Perceived Social Support," IJERPH, MDPI, vol. 17(21), pages 1-12, October.
    11. Kirk, Colleen P. & Rifkin, Laura S., 2020. "I'll trade you diamonds for toilet paper: Consumer reacting, coping and adapting behaviors in the COVID-19 pandemic," Journal of Business Research, Elsevier, vol. 117(C), pages 124-131.
    12. Hetschko, Clemens & Schöb, Ronnie & Wolf, Tobias, 2020. "Income support, employment transitions and well-being," Labour Economics, Elsevier, vol. 66(C).
    13. Roxana Guti'errez-Romero, 2020. "Conflict in Africa during COVID-19: social distancing, food vulnerability and welfare response," Papers 2006.10696, arXiv.org.
    14. Jeffrey M. Wooldridge, 2003. "Cluster-Sample Methods in Applied Econometrics," American Economic Review, American Economic Association, vol. 93(2), pages 133-138, May.
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