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Research Article

ICT adoption and income diversification among rural households in China

, ORCID Icon, ORCID Icon &
Pages 3614-3628 | Published online: 16 Jan 2020
 

ABSTRACT

Although the determinants of income diversification have been widely examined in the literature, little is known about whether and how information and communication technology (ICT) adoption affects household income diversification. To fill in this gap, this paper examines the impact of ICT adoption on income diversification among rural households in China, utilizing open-access data collected through the China Labour-force Dynamics Survey project. We employ a two-stage treatment effects model to address the potential selection bias issue associated with ICT adoption. The empirical results show that ICT adoption exerts a positive and statistically significant impact on income diversification. Further analyses reveal that ICT adoption is more beneficial to low-income rural households and those residing in eastern and central parts of China when it plays a role in diversifying rural income. Our findings suggest that improving rural education and infrastructure such as roads and broadband facilities can help enhance ICT adoption among rural households, which subsequently increases income diversification.

JEL CLASSIFICATION:

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1 For a better understanding, in Section 4.2.3 we also discussed the impact of ICT adoption on income diversification of urban households.

2 Please refer to http://css.sysu.edu.cn for more information about the CLDS data.

3 The Shannon-Weaver index is calculated by the formula SWI=inPilnPi, where SWI represents the Shannon-Weaver index variable, n and Pi are defined as previously. The Shannon-Weaver index (SWI) takes into account the diversity of income sources. It is calculated for every household and increases continuously with higher diversity (Schwarze and Zeller Citation2005).

Additional information

Funding

The authors would like to acknowledge the funding support from the National Natural Science Foundation of China Project [Grant No. 71903062] and Lincoln University commerce faculty seed fund project [INT5063].

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