The Impacts of COVID-19 on Indonesian Poverty and Unemployment

Khairulbahri, Muhamad

doi:10.20944/preprints202008.0288.v1

Cited by 1 publication

(1 citation statement)

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“…This is comparable to findings from other household-level studies by [18] in Uganda and [32] in Canada. No evidence suggests that female-headed households suffered more than male-headed households did, as evidenced in most studies (see [2,3,42,43]). In terms of specific gender concentration in industries, there was no indication that females were more concentrated in sectors that had been badly hit compared to males.…”

Section: Discussionmentioning

confidence: 99%

The Immediate Impacts of COVID-19 on Low-Income Households: Evidence from Malaysia

et al. 2023

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This study unravelled the economic impacts of the coronavirus disease 2019 (COVID-19) on low-income households. The asymmetric economic impacts of the pandemic that are biased towards the poor, young, and women have been well established. However, micro evidence on the poor is limited, thus demanding detailed understanding to design an effective targeted assistance. In this study, data were gathered from face-to-face interviews using a sampling frame provided by the Department of Statistics Malaysia (DOSM). Online data collection was dismissed to ensure all low-income households had the same chance to participate, as some might have no online access. Logistic regressions were estimated to identify the characteristics of households that suffered job loss and income reduction. The findings revealed that one in ten households experienced job loss during the pandemic, while one third survived with lower income. The extent of income reduction was rather severe, as the pandemic had reduced income generation by more than half among the affected households. The regression outcomes showed that the higher-income households among the low-income households had higher chances of experiencing income reduction. A similar scenario was noted for less-educated households. Notably, the adverse impacts were not biased toward female-headed households, as is widely perceived. There was no evidence that economic sectors explained job losses, but households involved in the agriculture, domestic, and transportation sectors had higher chances of suffering from income reduction. These results suggest that monetary government assistance should not rely on general indicators, such as female-headed households and below-poverty-line income (PLI). Instead, a more effective measure is to look at other characteristics, such as employment type, education level, and job sectors.

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