The Economics of the COVID-19 Pandemic in Poor Countries

Miguel, Edward; Mobarak, Ahmed Mushfiq

doi:10.1146/annurev-economics-051520-025412

Cited by 62 publications

(29 citation statements)

References 104 publications

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“…The coefficient for the Covid_Dummy variable (b 1 ) is negative and significant, implying a negative shock in output, post the pandemic. This result is consistent with the emerging body of literature on negative effects of the COVID-19 pandemic worldwide (Miguel and Mobarak, 2022 for a review of the emerging literature).…”

Section: Resultssupporting

confidence: 90%

“…These findings clearly indicate wider disparity in the coping mechanism of the poorer districts in absorbing the shock. The striking dissimilarity across regions within country corroborates with the findings discussed in Miguel and Mobarak (2022) and Basu (2021), and therefore warrants a targeted policy prescription through appropriate redistributive measures to mitigate this disparity. It must be noted, the change in convergence rate may well be temporary, as is estimated by Brussevich et al (2022).…”

Section: Resultssupporting

confidence: 82%

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Impact of COVID-19 on convergence in Indian districts

Chakrabarty

Mukherjee

2022

IGDR

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Purpose The purpose of this paper is to estimate the impact of the COVID-19 pandemic on the patterns of convergence/divergence among the districts in India. Specifically, this paper investigates if the impact is heterogeneous among different cohorts of districts (based on income distribution). The differential impact may lead to heterogeneous long-run growth paths, resulting in unbalanced development across regions within the country. A study of convergence can ascertain the possible trajectory of such development across regions. Investigation of this phenomenon is the primary aim of this study. Design/methodology/approach This paper uses the panel regression method for estimation. This paper uses high-frequency nighttime light intensity data as a proxy for aggregate output. Findings The authors observe a significant reduction in the convergence rate as a result of the pandemic. Across the cluster of districts, the drop in ß-convergence rate, compared to the pre-pandemic period, varied from approximately 33% for the poorer districts to close to zero for the richest group of districts. These findings suggest that the pandemic may lead to a wider disparity among different regions within the country. Originality/value This paper contributes to the literature in the following ways. First, to the best of the authors’ knowledge, this is the first paper to investigate the impact of COVID-19 on the convergence rate. A detailed look into the possible disparity in convergence among various regions is critical because a larger drop in convergence, especially among the poorer regions, may call for policy attention to attain long-term equitable development. The authors perform this exercise by dividing the districts into four quantile groups based on the distribution of night-light intensity. Second, while previous studies on convergence using nighttime light data have used a cross-sectional approach, this study is possibly the first attempt to use the panel regression method on this data. The application of this method can be useful in tackling district-level omitted variables bias. Finally, the heterogeneity analysis using different quantiles of the distribution of night-light intensity may help in designing targeted policies to mitigate the disparity across districts due to the shock.

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Section: Resultssupporting

confidence: 90%

Section: Resultssupporting

confidence: 82%

Impact of COVID-19 on convergence in Indian districts

Chakrabarty

Mukherjee

2022

IGDR

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“…Although economic indicators are not used in the PVUA evaluation system, the study findings showed that the differences in regional economic levels expressed various vulnerability risks posed by public health events, which might uncover a hidden fact. More specifically, it is likely that the sensitivity level and coping capacity regarding the vulnerability to public health events in urban agglomerations are deeply correlated economic level or socioeconomic level inevitably, which is consistent with previous studies (54,61,63,64). According to the research on Brazil denoted existing socioeconomic inequalities, rather than age, health status, and other risk factors for COVID-19, have affected the course of the epidemic (64).…”

Section: Temporal and Spatial Evolution Characteristics Of Vulnerabil...supporting

confidence: 84%

Evaluation of the vulnerability to public health events in the Guangdong-Hong Kong-Macao Greater Bay Area

Cui

Chen

Shen

et al. 2022

Front. Public Health

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With the continuous improvement in the integration of urban agglomeration, a multi-functional, socialized, and complex dynamic system, effective prevention and control of emergent public health events have become increasingly important. Based on the Public-Health Vulnerability-Assessment-System of Urban Agglomeration (PVUA), the temporal and spatial differentiation characteristics of vulnerability in the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) for the period of 2015-2019 are explored, and the vulnerable cities to public health events are identified in this area. The results can be summarized as follows: (1) The overall vulnerability to public health events in GBA decreases in the investigated period. (2) In the temporal dimension, accompanied by social and economic development, the sensitivity to public health events increases in GBA, and the coping capacity change from stable fluctuation to rapid improvement. (3) From the spatial dimension, the sensitivity level in GBA is low in the west, relatively high in the middle, and high in the southeast; the coping capacity is high in the southeast and low in the northwest; the collaborative governance capacity presents a spatial pattern of being low in the south and high in the north. (4) In the period of study, the vulnerability to public health events in Guangzhou and Jiangmen is stable at the lowest level, while that in Zhaoqing, Foshan, and Hong Kong SAR (Special Administrative Region) gradually reduces; the vulnerability in Shenzhen, Zhuhai, and Dongguan is fluctuating, and that in Huizhou, Zhongshan, and Macao SAR is continually maintained at a higher and the highest level.

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“…Understanding COVID-19 contagion among poor populations in low- and middle-income countries and people’s reactions to the pandemic and corresponding government policies is critical to design effective policies to address post-pandemic problems and future pandemics 1 – 8 . In rural remote regions where people have limited access to transportation, communication, health services, and testing for COVID-19, available data are scant which hampers much-needed understanding 9 , 10 .…”

Section: Introductionmentioning

confidence: 99%

COVID-19 contagion across remote communities in tropical forests

Takasaki

Abizaid

Coomes

2022

Sci Rep

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Understanding COVID-19 contagion among poor populations is hampered by a paucity of data, and especially so in remote rural communities with limited access to transportation, communication, and health services. We report on the first study on COVID-19 contagion across rural communities without road access. We conducted telephone surveys with over 400 riverine communities in the Peruvian Amazon in the early phase of the pandemic. During the first wave (April–June, 2020), COVID-19 spread from cities to most communities through public and private river transportation according to their remoteness. The initial spread was delayed by transportation restrictions but at the same time was driven in unintended ways by government social assistance. During the second wave (August, 2020), although people’s self-protective behaviors (promoted through communication access) helped to suppress the contagion, people responded to transportation restrictions and social assistance in distinct ways, leading to greater contagion among Indigenous communities than mestizo communities. As such, the spatial contagion during the early phase of the pandemic in tropical forests was shaped by river transportation and social behaviors. These novel findings have important implications for research and policies on pandemics in rural areas.

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The Economics of the COVID-19 Pandemic in Poor Countries

Cited by 62 publications

References 104 publications

Impact of COVID-19 on convergence in Indian districts

Impact of COVID-19 on convergence in Indian districts

Evaluation of the vulnerability to public health events in the Guangdong-Hong Kong-Macao Greater Bay Area

COVID-19 contagion across remote communities in tropical forests

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