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Journal of Integrative Agriculture  2021, Vol. 20 Issue (4): 998-1011    DOI: 10.1016/S2095-3119(20)63422-0
Section 3: Innovation and inclusive development for poverty alleviation Advanced Online Publication | Current Issue | Archive | Adv Search |
Poverty alleviation through e-commerce: Village involvement and demonstration policies in rural China
PENG Chao1*, MA Biao2*, ZHANG Chen3 
Administration and Management Institute, Ministry of Agriculture and Rural Affairs, Beijing 102208, P.R.China
2 School of Agricultural Economics and Rural Development, Renmin University of China, Beijing 100872, P.R.China
3 Institute of Population and Labor Economics, Chinese Academy of Social Sciences, Beijing 100006, P.R.China
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The diffusion of e-commerce has played a significant role in recent rural economic development in China.  E-commerce is also considered as an efficient channel to alleviate poverty in rural China.  Voluminous studies have investigated the contribution of e-commerce to agricultural development, yet it is lacking empirical evidence as to the effects of e-commerce on rural poverty alleviation.  Since the year of 2014, in order to develop rural e-commerce, Chinese government launched the National Rural E-commerce Comprehensive Demonstration Project.  This gradual involvement policy offered a natural experiment for evaluation of e-commerce.  Based on village-level survey data from rural China and Heckit method, our study finds that rural e-commerce has a signi?cantly positive effect on rural income.  Moreover, the effect is inverted U-shaped for the relative-poverty villages.  The estimation of the propensity scores matching model confirms that the results are robust.  The following policy recommendations are proposed: (1) policy support to rural e-commerce should prioritize the poverty-stricken villages.  By doing so, the marginal income effects of e-commerce will be maximized.  (2) Investment in internet infrastructure and establishment of human resources for e-commerce in rural areas will have spillover effects, increasing rural income through the “digital dividend”.
Keywords:   poverty alleviation        income        National Rural E-commerce Comprehensive Demonstration Project        Heckit method  
Received: 02 June 2020   Accepted: 28 March 2021
Fund: The authors gratefully acknowledge the financial support from the National Natural Science Foundation of China (71673274); the Outstanding Innovative Talents Cultivation Funded Programs 2019 of Renmin University of China.
Corresponding Authors:  Correspondence PENG Chao, E-mail:; MA Biao, E-mail:    
About author:  * These authors contributed equally to this study.

Cite this article: 

PENG Chao, MA Biao, ZHANG Chen. 2021. Poverty alleviation through e-commerce: Village involvement and demonstration policies in rural China. Journal of Integrative Agriculture, 20(4): 998-1011.

Acker J C, Mbiti I M. 2010. Mobile phones and economic development in Africa. Journal of Economic Perspectives, 24, 207–232.
Akca H, Sayili M, Esengun K. 2007. Challenge of rural people to reduce digital divide in the globalized world: Theory and practice. Government Information Quarterly, 24, 404–413.
Anang B T, Bäckman S, Rezitis A. 2017. Production technology and technical efficiency: Irrigated and rain-fed rice farms in northern Ghana. Eurasian Economic Review, 7, 95–113.
Baorakis G M, Kourgiantakis M, Migdalas A. 2002. The impact of e-commerce on agro-food marketing: The case of agricultural cooperatives, firms and consumers in Crete. British Food Journal, 104, 580–590.
Chan M. 2015. Mobile phones and the good life: Examining the relationships among mobile use, social capital and subjective well-being. New Media & Society, 17, 96–113.
Chen Y. 2012. Village-based networks and wage of rural-to-urban migrants: Estimating the causal effects of networks using combined identification strategies. Chinese Journal of Sociology, 4, 68–92.
Clark C, Gorski P. 2002. Multicultural education and the digital divide: Focus on socioeconomic class background. Multicultural Perspective, 4, 25–36.
Fafchamps M, Minten B. 2012. Impact of SMS based agricultural information on Indian farmers. The World Bank Economic Review, 26, 383–414.
Frank K A. 2000. Impact of a confounding variable on a regression coefficient. Sociological Methods and Research, 29, 147–194.
Gao Y, Zang L, Sun J. 2018. Does computer penetration increase farmers’ income? An empirical study from China. Telecommunications Policy, 42, 345–360.
Goldfarb A, Tucker C. 2019. Digital economics. Journal of Economic Literature, 57, 3–43.
Hartje R, Hübler M. 2017. Smartphones support smart labour. Applied Economics Letters, 7, 467–471.
Heckman J. 1979. Sample selection bias as a specification error. Econometrica, 47, 154–161.
Heckman J, Robb R. 1985. Alternative methods for evaluating the impact of interventions: An overview. Journal of Ecnometrics, 30, 239–267.
Jalali A A, Okhovvat M R, Okhovvat M. 2011. A new applicable model of Iran rural e-commerce development. Procedia Computer Science, 3, 1157–1163.
Jha S K, Pinsonneault A, Dubé L. 2016. The evolution of an ICT platform-enabled ecosystem for poverty alleviation: The case of EKutir. MIS Quarterly, 40, 431–445.
Knight J, Li S, Deng Q. 2010. Education and the poverty trap in rural China: Closing the trap. Oxford Development Studies, 38, 1–24.
Leng C, Ma W, Tang J, Zhu Z. 2020. ICT adoption and income diversification among rural households in China. Applied Economics, 52, 3614–3628.
Leong C, Pan S L, Newell S, Cui L. 2016. The emergence of self-organizing e-commerce ecosystems in remote villages of China: A tale of digital empowerment for rural development. MIS Quarterly, 40, 475–484.
Li L, Du K, Zhang W, Mao J. 2016. Poverty alleviation through government-led e-commerce development in rural China: An activity theory perspective. Information Systems Journal, 29, 914–952.
Liu M, Feng X, Wang S, Qiu H. 2019. China’s poverty alleviation over the last 40 years: successes and challenges. Australian Journal of Agricultural and Resource Economics, 59, 1–20.
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.
Ma W, Renwick A, Yuan P, Ratna N. 2018. Agricultural cooperative membership and technical efficiency of apple farmers in China: An analysis accounting for selectivity bias. Food Policy, 81, 122–132.
Ministry of Commerce of China. 2019. E-commerce in China. China Commerce and Trade Press, Beijing. (in Chinese)
Mintert J, Andresen D, Schroeder T. 2003. Improving efficiency in business-to-business information transfers: A web-based solution in the beef sector. International Journal of Information Management, 23, 415–424.
NBSC. 2019. China’s rural poor population decreased by 13.86 million in 2018. [2020-5-20]. (in Chinese)
Ogutu S O, Okello J J, Otieno D J. 2014. Impact of information and communication technology-based market information services on smallholder farm input use and productivity: The case of Kenya. World Development, 64, 311–321.
Parker C, Ramdas K, Savva N. 2016. Is it enough? Evidence from a natural experiment in India’s agriculture markets. Management Science, 62, 2481–2503.
Qin C, Chong T T L. 2018. Can poverty be alleviated in China? Review of Income and Wealth, 64, 192–212.
Semykina A, Wooldridge J M. 2010. Estimating panel data models in the presence of endogeneity and selection. Journal of Econometrics, 157, 375–380.
Shimamoto D, Yamada H, Gummert M. 2015. Mobile phones and market information: Evidence from rural Cambodia. Food Policy, 57, 135–141.
Song M X, Yang M X. 2019. Leveraging core capabilities and environmental dynamism for food traceability and firm performance in a food supply chain: A moderated mediation model. Journal of Integrative Agriculture, 18, 1820–1837.
Tao T Y, Zhao M. 2012. An ontology-based information retrieval model for vegetables e-commerce. Journal of Integrative Agriculture, 11, 800–807.
Wan G, Zhou Z. 2005. Income inequality in rural China: Regression-based decomposition using household data. Review of Development Economics, 9, 107–120.
Zeng Y, Guo H, Jin S. 2018. Does e-commerce increase farmers’ income? Evidence from Shuyang County, Jiangsu Province, China. Chinese Rural Economy, 2, 49–64. (in Chinese)
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