Abstract
Utilizing the data from China Rural Revitalization Survey (CRRS), this study analyzes the impact of digital inequality on income distribution. The findings reveal that digital inequality has a significant negative effect on household income, with a more pronounced inhibitory effect on low-income households. Additionally, digital inequality widens income inequality within households, with a more significant negative effect on the middle-income group. The further analysis suggests that households do not passively respond to the impact of digital inequality but rather improve their livelihood diversity, particularly for higher-income groups. Based on these results, this study suggests that attention should be given to the issue of inequality in the process of digital technology transformation. It recommends creating development opportunities through digital technology, expanding income-generating opportunities for households, enhancing the sense of economic well-being among economically disadvantaged households, and building a future of digitalization that is fair, inclusive, and sustainable.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
Data Availability
Data applied in the study are available from China Rural Revitalization Survey (CRRS) dataset (http://rdi.cass.cn/ggl/202210/t20221024_5551642.shtml), accessed on 14 July 2023.
Notes
“Information Access” refers to the basic conditions required for rural residents to access the Internet, including digital infrastructure in the region, household digital devices, and software conditions such as broadband availability and internet speed.
“Information Literacy” refers to the ability to use digital technology, including the capacity to access and benefit from information.
According to data from the National Bureau of Statistics of China, as of December 2022, the Internet penetration rate (total Internet users/resident population) in rural areas of China reached 61.9%, with a total of 308 million rural netizens, accounting for 28.9% of the overall netizen population.
Center for Informatization Study of the Chinese Academy of Social Sciences (CASS), Report on Survey and Analysis of Rural Digital Literacy in China under the Background of Rural Revitalization Strategy, March 18 2021, http://iqte.cssn.cn/yjjg/fstyjzx/xxhyjzx/xsdt/202103/P020210311318247184884.pdf.
Total income includes wage income, agricultural income, industrial and commercial income, property income, and transfer income.
References
Acemoglu, D., & Autor, D. (2011). Skills, tasks and technologies: Implications for employment and earnings. Handbook of Labor Economics, 4B, 1043–1171.
Agyire-Tettey, F., Ackah, C. G., & Asuman, D. (2018). An unconditional quantile regression based decomposition of spatial Welfare Inequalities in Ghana. Journal of Development Studies, 54, 537–556. https://doi.org/10.1080/00220388.2017.1296571
Alobo Loison, S. (2015). Rural livelihood diversification in Sub-Saharan Africa: A literature review. The Journal of Development Studies, 51, 1125–1138. https://doi.org/10.1080/00220388.2015.1046445
Bao, T., Liang, B., & Riyanto, Y. E. (2021). Unpacking the negative welfare effect of social media: Evidence from a large scale nationally representative time-use survey in China. China Economic Review, 69, 101650. https://doi.org/10.1016/j.chieco.2021.101650
Benami, E., & Carter, M. R. (2021). Can digital technologies reshape rural microfinance? Implications for savings, credit, & insurance. Applied Economic Perspectives and Policy, 43, 1196–1220. https://doi.org/10.1002/aepp.13151
Brynjolfsson, E., & McAfee, A. (2011). Race against the machine: How the Digital Revolution is accelerating Innovation, driving Productivity, and irreversibly transforming employment and the economy. Brynjolfsson and McAfee.
Castellacci, F., & Tveito, V. (2018). Internet use and well-being: A survey and a theoretical framework. Research Policy, 47, 308–325. https://doi.org/10.1016/j.respol.2017.11.007
Demir, A., Pesqué-Cela, V., Altunbas, Y., & Murinde, V. (2022). Fintech, financial inclusion and income inequality: A quantile regression approach. The European Journal of Finance, 28, 86–107. https://doi.org/10.1080/1351847X.2020.1772335
DiMaggio, P., & Hargittai, E. (2001). From the “Digital Divide” to “Digital Inequality”: Studying internet use as penetration increases. Working Paper No. 47. Princeton University, School of Public and International Affairs, Center for Arts and Cultural Policy Studies.
Dimaggio, P., Hargittai, E., Celeste, C., & Shafer, S. (2004). Digital inequality: From unequal access to differentiated use. Social Inequality (pp. 355–400). Russell Sage Foundation.
Dimova, R., & Adebowale, O. (2018). Does access to formal finance matter for welfare and inequality? Micro Level evidence from Nigeria. The Journal of Development Studies, 54, 1534–1550. https://doi.org/10.1080/00220388.2017.1371293
Ellis, F. (1998). Household strategies and rural livelihood diversification. The Journal of Development Studies, 35, 1–38. https://doi.org/10.1080/00220389808422553
Ellis, F. (2000). The determinants of rural livelihood diversification in developing countries. Journal of Agricultural Economics, 51, 289–302. https://doi.org/10.1111/j.1477-9552.2000.tb01229.x
Firpo, S., Fortin, N., & Lemieux, T. (2009). Unconditional quantile regressions. Econometrica, 77, 953–973. https://doi.org/10.3982/ECTA6822
Fossen, F. M., & Sorgner, A. (2022). New digital technologies and heterogeneous wage and employment dynamics in the United States: Evidence from individual-level data. Technological Forecasting and Social Change, 175, 121381. https://doi.org/10.1016/j.techfore.2021.121381
Gautam, Y., & Andersen, P. (2016). Rural livelihood diversification and household well-being: Insights from Humla, Nepal. Journal of Rural Studies, 44, 239–249. https://doi.org/10.1016/j.jrurstud.2016.02.001
Giuntella, O., Lu, Y., & Wang, T. (2022). How do workers and households adjust to Robots? Evidence from China. Working Paper Series. https://doi.org/10.3386/w30707
Hailu, B. K., Abrha, B. K., & Weldegiorgis, K. A. (Eds.). (2014). Adoption and impact of agricultural technologies on farm income: Evidence from Southern Tigray, Northern Ethiopia. International Journal of Food and Agricultural Economics (IJFAEC), Vol 2. https://doi.org/10.22004/ag.econ.190816
Hargittai, E. (2002). Second-level digital divide: Differences in people’s online skills. First Monday. https://doi.org/10.5210/fm.v7i4.942
He, J., & Li, Q. (2020). Can online social interaction improve the digital finance participation of rural households? China Agricultural Economic Review, 12, 295–313. https://doi.org/10.1108/CAER-11-2019-0213
Kakwani, N. (1984). The relative deprivation curve and its applications: Reply. Journal of Business & Economic Statistics, 2, 400–405.
Kemigisha, E., Angelsen, A., Babweteera, F., & Mugisha, J. (2022). Survival- versus opportunity-driven environmental reliance: Evidence from Uganda. Forest Policy and Economics, 135, 102639. https://doi.org/10.1016/j.forpol.2021.102639
Khan, N., Ray, R. L., Zhang, S., Osabuohien, E., & Ihtisham, M. (2022). Influence of mobile phone and internet technology on income of rural farmers: Evidence from Khyber Pakhtunkhwa Province, Pakistan. Technology in Society, 68, 101866. https://doi.org/10.1016/j.techsoc.2022.101866
Li, G., Cui, X., Pan, L., & Wang, Y. (2023). Land transfer and rural household consumption diversity: Promoting or inhibiting? Land, 12, 203. https://doi.org/10.3390/land12010203
Ma, W., Grafton, R. Q., & Renwick, A. (2020). Smartphone use and income growth in rural China: Empirical results and policy implications. Electronic Commerce Research, 20, 713–736. https://doi.org/10.1007/s10660-018-9323-x
Ma, W., Vatsa, P., Zheng, H., & Rahut, D. B. (2022). Nonfarm employment and consumption diversification in rural China. Economic Analysis and Policy, 76, 582–598. https://doi.org/10.1016/j.eap.2022.09.010
Mingo, I., & Bracciale, R. (2018). The Matthew effect in the Italian digital context: The progressive marginalisation of the poor. Social Indicators Research, 135, 629–659. https://doi.org/10.1007/s11205-016-1511-2
Nakasone, E., Torero, M., & Minten, B. (2014). The power of information: The ICT revolution in agricultural development. Annual Review of Resource Economics, 6, 533–550. https://doi.org/10.1146/annurev-resource-100913-012714
Nambisan, S. (2017). Digital entrepreneurship: Toward a digital technology perspective of entrepreneurship. Entrepreneurship Theory and Practice, 41, 1029–1055. https://doi.org/10.1111/etap.12254
Nambisan, S., Wright, M., & Feldman, M. (2019). The digital transformation of innovation and entrepreneurship: Progress, challenges and key themes. Research Policy the Digital Transformation of Innovation and Entrepreneurship, 48, 103773. https://doi.org/10.1016/j.respol.2019.03.018
Ng, P. M. L., Lit, K. K., & Cheung, C. T. Y. (2022). Remote work as a new normal? The technology-organization-environment (TOE) context. Technology in Society, 70, 102022. https://doi.org/10.1016/j.techsoc.2022.102022
Oster, E. (2019). Unobservable selection and coefficient stability: Theory and evidence. Journal of Business & Economic Statistics, 37, 187–204. https://doi.org/10.1080/07350015.2016.1227711
Pabilonia, S. W., & Zoghi, C. (2005). Returning to the returns to computer use. American Economic Review, 95, 314–317. https://doi.org/10.1257/000282805774670509
Podder, N. (1996). Relative deprivation, envy and economic inequality. Kyklos, 49, 353–376. https://doi.org/10.1111/j.1467-6435.1996.tb01401.x
Ravallion, M., & Lokshin, M. (2010). Who cares about relative deprivation? Journal of Economic Behavior & Organization, 73, 171–185. https://doi.org/10.1016/j.jebo.2009.08.008
Singh, P., Bala, H., Dey, B. L., & Filieri, R. (2022). Enforced remote working: The impact of digital platform-induced stress and remote working experience on technology exhaustion and subjective wellbeing. Journal of Business Research, 151, 269–286. https://doi.org/10.1016/j.jbusres.2022.07.002
Stern, M. J., Adams, A. E., & Elsasser, S. (2009). Digital inequality and place: The effects of technological diffusion on internet proficiency and usage across rural, suburban, and urban counties*. Sociological Inquiry, 79, 391–417. https://doi.org/10.1111/j.1475-682X.2009.00302.x
UN. (2019). The age of Digital Interdependence: Report of the UN Secretary-General’s high-level panel on Digital Cooperation. https://digitallibrary.un.org/record/3865925. Accessed 31 Aug 2023
Walker, I., & Smith, H. J. (2002). Relative deprivation: Specification, development, and integration, relative deprivation: Specification, development, and integration. Cambridge University Press.
Wang, C., Wan, G., & Yang, D. (2014). Income inequality in the people’s Republic of China: Trends, determinants, and proposed remedies. Journal of Economic Surveys, 28, 686–708. https://doi.org/10.1111/joes.12077
Wang, Q., Liu, C., & Lan, S. (2022). Digital literacy and financial market participation of middle-aged and elderly adults in China. Economic and Political Studies, 0, 1–28. https://doi.org/10.1080/20954816.2022.2115191
Wirtz, D., Tucker, A., Briggs, C., & Schoemann, A. M. (2021). How and why social media affect subjective well-being: Multi-site use and social comparison as predictors of change across time. Journal of Happiness Studies, 22, 1673–1691. https://doi.org/10.1007/s10902-020-00291-z
Yitzhaki, S. (1979). Relative deprivation and the gini soefficient. The Quarterly Journal of Economics, 93, 321–324. https://doi.org/10.2307/1883197
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Competing Interest
None.
Additional information
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Appendix
Appendix
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Li, G. Digital Inequality and Household Income Distribution: Evidence from Rural China. Applied Research Quality Life 18, 3061–3087 (2023). https://doi.org/10.1007/s11482-023-10220-w
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11482-023-10220-w