Different firm responses to the COVID-19 pandemic shocks: machine-learning evidence on the Vietnamese labor market

Abstract

Purpose

This paper aims to identify the disproportionate impacts of the COVID-19 pandemic on labor markets.

Design/methodology/approach

The authors conduct a large-scale survey on 16,000 firms from 82 industries in Ho Chi Minh City, Vietnam, and analyze the data set by using different machine-learning methods.

Findings

First, job loss and reduction in state-owned enterprises have been significantly larger than in other types of organizations. Second, employees of foreign direct investment enterprises suffer a significantly lower labor income than those of other groups. Third, the adverse effects of the COVID-19 pandemic on the labor market are heterogeneous across industries and geographies. Finally, firms with high revenue in 2019 are more likely to adopt preventive measures, including the reduction of labor forces. The authors also find a significant correlation between firms' revenue and labor reduction as traditional econometrics and machine-learning techniques suggest.

Originality/value

This study has two main policy implications. First, although government support through taxes has been provided, the authors highlight evidence that there may be some additional benefit from targeting firms that have characteristics associated with layoffs or other negative labor responses. Second, the authors provide information that shows which firm characteristics are associated with particular labor market responses such as layoffs, which may help target stimulus packages. Although the COVID-19 pandemic affects most industries and occupations, heterogeneous firm responses suggest that there could be several varieties of targeted policies-targeting firms that are likely to reduce labor forces or firms likely to face reduced revenue. In this paper, the authors outline several industries and firm characteristics which appear to more directly be reducing employee counts or having negative labor responses which may lead to more cost–effect stimulus.

Citation

Le, L.H.V., Huynh, T.L.D., Weber, B.S. and Nguyen, B.K.Q. (2023), "Different firm responses to the COVID-19 pandemic shocks: machine-learning evidence on the Vietnamese labor market", International Journal of Emerging Markets, Vol. 18 No. 9, pp. 2501-2522. https://doi.org/10.1108/IJOEM-02-2021-0292