Labour market outcomes and migration: evidence from China

Huang, Xiao; Sheng, Pengfei; Shui, Ailun

doi:10.1080/13504851.2019.1705236

Cited by 3 publications

(3 citation statements)

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“…The study of Huang et al (2020) is quite close to our study and is conducted in the Chinese context. They collected data from the 2016 China Migrants Dynamic Survey to investigate the income gap between small entrepreneurs, own‐account workers, and employees among rural‐to‐urban migrants.…”

Section: Literature Reviewsupporting

confidence: 84%

“…However, this technological advancement has widened income gaps (Ma, 2022; Njangang, 2022; Zuo & Hong, 2021), creating a huge social divide and instability (Balcilar, Gupta, Ma, & Makena, 2021; Golin, 2022; Su, Zhou, Ye, & Li, 2021). Studies have also shown that an income gap exists between self‐employed individuals and employees of both developed and developing countries (Huang, Sheng, & Shui, 2020; ILO, 2015, 2018; Ma & Li, 2022). Thus, with changes in employment statuses and the rapid expansion of Internet usage, it becomes imperative to investigate how Internet usage affects the income gap between different employment groups in China as research on this issue is limited.…”

Section: Introductionmentioning

confidence: 99%

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Internet usage and the income gap between self‐employed individuals and employees: Evidence from China

2022

Review Development Economics

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Using longitudinal data from the China Family Panel Studies, we investigate the impact of Internet usage on the income gap between self‐employed individuals and employees in China, considering the sample selection bias and individual heterogeneity issues. We divided employment statuses into three types―small entrepreneur, own‐account worker, and employee. The findings reveal the following: First, the returns from Internet usage differ by employment type, which is lower for self‐employed individuals than that for employees. Second, the difference in Internet usage contributes to widening the income gap, whereas the difference in the returns from Internet usage to income contributes to narrowing it. Finally, Internet usage exerts a greater impact on the income gap between employees and small entrepreneurs than that between employees and own‐account workers. These empirical results suggest that the division of Internet access may exacerbate the segmentation of the formal and informal sectors in China.

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Section: Literature Reviewsupporting

confidence: 84%

Section: Introductionmentioning

confidence: 99%

Internet usage and the income gap between self‐employed individuals and employees: Evidence from China

2022

Review Development Economics

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“…From the perspective of consumption structure, due to the low-income level of migrant workers, the household consumption structure has been dominated by subsistence consumption, household subsidies, and improvement of living conditions (33,34). Moreover, due to the unique household registration system of China, even if migrant workers have worked in the city for many years, they cannot enjoy the same treatment as urban residents (35,36), and they may even suffer employment discrimination (32,37,38). Compared with the great contribution of migrant workers to urban economic development, the public services and welfare provided by the urban sector to them are very limited.…”

Section: Introductionmentioning

confidence: 99%

Work Resumption Rate and Migrant Workers' Income During the COVID-19 Pandemic

Chu

Chai

et al. 2021

Front. Public Health

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The COVID-19 public health crisis has quickly led to an economic crisis, impacting many people and businesses in the world. This study examines how the pandemic affects workforces and workers' income. We quantify the impact of staggered resumption of work, after the coronavirus lockdowns, on the migrant workers' income. Using data on population movements of 366 Chinese cities at the daily level from the Baidu Maps-Migration Big Data Platform and historical data on the average monthly income of migrant workers, we find that the average work resumption rate (WRR) during the period of the Chinese Lantern Festival was 25.25%, which was only 30.67% of that in the same matched lunar calendar period in 2019. We then apply Gray Model First Order One Variable [GM (1, 1)] to predict the monthly income of migrant workers during the period of the COVID-19 pandemic. We show that, if without the influence of the COVID-19 pandemic, the average monthly income of migrant workers in 2020 will be expected to increase by 12% compared with 2019. We further conduct scenario analysis and show that the average monthly income of migrant workers in 2020 under the conservative scenario (COS), medium scenario (MES), and worse scenario (WOS) will be predicted to decrease by 2, 21, and 44%, respectively. Through testing, our prediction error is <5%. Our findings will help policymakers to decide when and how they implement a plan to ease the coronavirus lockdown and related financial support policies.

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