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Work From Anywhere. Restarting Covid-19 Economies Using Human Capital Boosters

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  • ANDREEA TEODORA IACOB

    (drd. ECONOMICS I, ASE, BUCHAREST)

Abstract

Throughout our journey in life, the economy is a constant companion, reminding us that it cannot be controlled but rather understood and, to some extent, predicted. This notion often applies to cyclical crises. But can the same be said for non-cyclical crises? Has history revealed patterns or provided us with predictive tools? Can we, as economists and economic agents who rely on economic principles in our daily lives, act proactively rather than merely reactively in the face of such crises? Answering these questions requires a review of the most notable studies and theories on the subject. It also involves the author's personal perspective on the critical role of swift and accurate corrective policies, given that predictive policies, as discussed in the relevant section, may not be as effective in this type of crisis. The core of the study will present a proposed strategy for economic recovery, serving as a research topic using various methodological approaches. The analysis will focus on the past, present, and future implications of the COVID-19 pandemic. The study will take into account both the international and European contexts.

Suggested Citation

  • Andreea Teodora Iacob, 2024. "Work From Anywhere. Restarting Covid-19 Economies Using Human Capital Boosters," Annals - Economy Series, Constantin Brancusi University, Faculty of Economics, vol. 4, pages 164-168, August.
  • Handle: RePEc:cbu:jrnlec:y:2024:v:4:p:164-168
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    References listed on IDEAS

    as
    1. Mincer, Jacob, 1984. "Human capital and economic growth," Economics of Education Review, Elsevier, vol. 3(3), pages 195-205, June.
    2. Gary S. Becker, 1994. "Human Capital Revisited," NBER Chapters, in: Human Capital: A Theoretical and Empirical Analysis with Special Reference to Education, Third Edition, pages 15-28, National Bureau of Economic Research, Inc.
    3. Annamaria Di Bartolo, 1999. "Modern Human Capital Analysis: Estimation of US, Canada and Italy Earning Functions," LIS Working papers 212, LIS Cross-National Data Center in Luxembourg.
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