Internet Use, Sustainable Agricultural Practices and Rural Incomes: Evidence from China
Relatively little is known about the association between Internet use and environmentally‐friendly agricultural innovation adoption. To fill this void, this study examines the impact of Internet use on the adoption of sustainable agricultural practices (SAPs) and their heterogeneous effects on farm...
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Published in | The Australian journal of agricultural and resource economics Vol. 64; no. 4; pp. 1087 - 1112 |
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Main Authors | , |
Format | Journal Article |
Language | English |
Published |
Oxford
Blackwell Publishing Ltd
01.10.2020
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Subjects | |
Online Access | Get full text |
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Summary: | Relatively little is known about the association between Internet use and environmentally‐friendly agricultural innovation adoption. To fill this void, this study examines the impact of Internet use on the adoption of sustainable agricultural practices (SAPs) and their heterogeneous effects on farm income and household income. Unlike previous studies that analyse the dichotomous decision of agricultural innovation adoption, this study captures the number of SAPs adopted. We apply both endogenous‐treatment Poisson regression model and unconditional quantile regression model to analyse unique farm‐level data collected from China. The empirical results show that Internet use exerts a positive and statistically significant impact on the number of SAPs adopted, and the joint effects of Internet use and SAP adoption on farm income and household income are heterogeneous. In particular, we show that Internet use has a larger impact at the upper tail of household income but it has no significant impact on farm income. SAP adoption is negatively associated with farm income and household income across the selected quantiles. |
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Bibliography: | This paper was written while Wanglin Ma was a visiting scholar at the China Centre for Agricultural Policy (CCAP) at Peking University. He gratefully acknowledges the financial support provided by the New Zealand Centre at Peking University. Xiaobing Wang acknowledges funding support from the National Natural Sciences of China (Ref. No. 71673008). |
ISSN: | 1364-985X 1467-8489 |
DOI: | 10.1111/1467-8489.12390 |