Affiliation:
1. Department of Economics BSMRSTU Gopalganj Bangladesh
Abstract
AbstractThis study investigates the determinants of firms' job‐cut decisions during the COVID‐19 pandemic, considering both firm‐level and country‐level factors. Data from 31 countries (a mix of developed and emerging) collected between May 2020 and May 2021 are analyzed using a multilevel Zero‐Inflated Negative Binomial (ZINB) model. The results reveal that firms that were operational, larger in size, received financial incentives, and arranged remote work for their workforce laid off a smaller proportion of workers. Conversely, firms that experienced significant sales reductions, input supply disruptions, and introduced delivery or carry‐out services laid off a larger proportion of workers. Moreover, among financial incentive‐recipient firms, smaller ones and those that introduced remote work and delivery or carry‐out services had smaller layoffs. At the country level, the human capital index (HCI) significantly influenced job‐cut decisions, with higher HCI scores associated with smaller layoffs. Classifying countries into “developed” and “emerging” yielded similar results, except for temporary closure having no significant impact on job cuts in developed countries and remote work showing no impact on job cuts in emerging countries. The robustness of the results was confirmed by a multilevel zero‐inflated Tobit model, which consistently reproduced the outcomes.