Internal Migration, Urbanization and Poverty in Asia: Dynamics and Interrelationships

This paper calculates poverty and inequality elasticities using the latest-available World Bank primary survey household consumption expenditure data for the rapidly growing urban sectors of India, Indonesia, and China. Our approach compares the conventional use of the overly simple headcount measure to the poverty gap squared (PG 2 ) measures of poverty and focuses the effectiveness of reducing inequality on the disutility of the poor using a microeconomic utility-based point elasticity measure of poverty loss. The calculations show that reducing urban inequality is more effective in reducing (1) urban poverty than promoting growth and (2) poverty distress more than that in the rural sector. The optimal policy prescription is to reduce urban inequality by targeting the urban very poor using the PG 2 measure.Further research is required to identify and quantify the determinants of the point elasticity magnitudes and the possible directions of causation.

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The Effects of COVID-19 on the Socio-Economic Conditions of Marginal People: A Case Study in the Selected Districts of Bangladesh

Rahman

Alam

2022

Sustainability

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In this paper, we have examined the effects of COVID-19 on the socio-economic condition of the three-wheeled electric vehicle drivers in some selected areas of Bangladesh from the cross-sectional data (September–November 2020). The results of linear regression indicate that under COVID-19 conditions, age (p = 0.022) and hardship (p = 0.000) positively, and education (p = 0.036), driving duration (p = 0.023), COVID consciousness (p = 0.086) and easy bike vehicle (p = 0.000) negatively affects income of the respondents. The deaths of COVID in the district (p = 0.003), income (p = 0.000), age (p = 0.037), easy bike vehicle (p = 0.018), debt (p = 0.059) and sufferings of diseases (p = 0.044) positively, and property holdings (p = 0.028), residence in urban areas (p = 0.004) and COVID consciousness (p = 0.082) negatively affect the family expenditure. The results from binary logistics regressions show that diseases sufferings (adjusted p = <0.001; unadjusted p = <0.001), corona fear (unadjusted p = 0.005; adjusted p = <0.001) have positive, and income (unadjusted p = <0.001; adjusted p = <0.001), cooking fuel (unadjusted p = 0.003; adjusted p = 0.091) and easy bike vehicle (unadjusted p = <0.001; adjusted p = 0.288) have negative association with hardship or misery due to COVID-19; death of COVID-19 in the district (unadjusted p = 0.008; adjusted p = 0.037), hardship or misery (adjusted p = 0.005; adjusted p = 0.001), and urban dwelling area (unadjusted p = 0.002; adjusted p = 0.004) have positive, and access to pure drinking water (unadjusted p = 0.005; adjusted p = 0.011) has negative link with corona fear; and, family savings (unadjusted p = 0.001; adjusted p = 0.013), satisfaction in the current job (unadjusted p = <0.001; adjusted p = <0.001), and government medical service (unadjusted p = 0.065; adjusted p = 0.012) have positive affiliation, and household size (unadjusted p = 0.007; adjusted p = 0.020) has negative affiliation with the continuation desire of the current job of respondents. All the obtained results are consistent and have significant policy implications.

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Internal Migration, Urbanization and Poverty in Asia: Dynamics and Interrelationships

Cited by 3 publications

References 84 publications

City Size Effect on Migration and Poverty: Study of Million-Plus Cities in India

City Size Effect on Migration and Poverty: Study of Million-Plus Cities in India

Urban poverty, growth, and inequality: A needed paradigm shift?

The Effects of COVID-19 on the Socio-Economic Conditions of Marginal People: A Case Study in the Selected Districts of Bangladesh

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