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.'
affiliation: 'Huynh, TLD (Corresponding Author), Univ Econ Ho Chi Minh City, Sch Banking,
  Ho Chi Minh City, Vietnam.

  Lam Hoang Viet Le, Univ Peoples Secur, Ho Chi Minh City, Vietnam.

  Toan Luu Duc Huynh, Univ Econ Ho Chi Minh City, Sch Banking, Ho Chi Minh City, Vietnam.

  Toan Luu Duc Huynh, WHU Otto Beisheim Sch Management, Chair Behav Finance, Vallendar,
  Germany.

  Weber, Bryan S., CUNY Coll Staten Isl, New York, NY USA.

  Bao Khac Quoc Nguyen, Univ Econ Ho Chi Minh City, Sch Finance, Ho Chi Minh City,
  Vietnam.'
author: Le, Lam Hoang Viet and Huynh, Toan Luu Duc and Weber, Bryan S. and Nguyen,
  Bao Khac Quoc
author-email: toanhld@ueh.edu.vn
author_list:
- family: Le
  given: Lam Hoang Viet
- family: Huynh
  given: Toan Luu Duc
- family: Weber
  given: Bryan S.
- family: Nguyen
  given: Bao Khac Quoc
da: '2023-09-28'
doi: 10.1108/IJOEM-02-2021-0292
earlyaccessdate: JUL 2021
eissn: 1746-8817
files: []
issn: 1746-8809
journal: INTERNATIONAL JOURNAL OF EMERGING MARKETS
keywords: 'COVID-19; Employment; Labor forces; Organizational behavior;

  Disparities; Vietnam; J22; J23; J21; J62; J63; J64; E24'
keywords-plus: CRISIS
language: English
month: 2021 JUL 27
number-of-cited-references: '56'
orcid-numbers: 'Weber, Bryan/0000-0003-1806-4451

  Nguyen, Khac Quoc Bao/0000-0001-7735-2096

  Huynh, Toan Luu Duc/0000-0002-1486-127X'
papis_id: 50f865b105a872f98498ad3d3bc305ae
ref: Le2021differentfirm
times-cited: '5'
title: 'Different firm responses to the COVID-19 pandemic shocks: machine-learning
  evidence on the Vietnamese labor market'
type: article
unique-id: WOS:000678046000001
usage-count-last-180-days: '1'
usage-count-since-2013: '21'
web-of-science-categories: Business; Economics; Management
year: '2021'