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Smartphone-based information acquisition and wheat farm performance: insights from a doubly robust IPWRA estimator

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Abstract

This study examines the impact of smartphone-based information acquisition on crop yields, net returns, return on investment (ROI), and production costs, using survey data collected from 558 wheat farmers in rural China. We employ a double-robust inverse probability weighted regression adjustment estimator to address the potential selection bias issue. The results reveal that information acquisition via smartphones significantly increases wheat yields, net returns, and ROI by 7%, 31%, and 39%, respectively, and it has a negative but insignificant impact on production costs. These results largely echo the results estimated from propensity score matching and endogenous switching regression models. In general, our findings suggest that policy interventions targeting to boost farm economic performance should consider distributing agricultural production and marketing information via smartphones.

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Notes

  1. Ideally, smartphone-based information acquisition is expected to reduce production costs. It is worth to mention here that smartphone-based information acquisition might increase production costs if it induces farmers to use expensive inputs such as drought-tolerant wheat varieties, organic fertilizers and green pesticides.

  2. As rightly pointed by an anonymous reviewer, the crop price might have no variations if the marketing price of crops for the whole market is fixed at a certain time. Therefore, the crop price is discussed in Sect. 2.1 in consideration of the theoretical framework generalization, but it is not considered as an outcome variable in our empirical analysis.

  3. Although IPWRA estimator has advantages over PSM model, RA estimator, and IPW estimator, it cannot fully address the selection bias. In fact, IPWRA estimator only mitigates selection bias arising from observed factors [51, 65].

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Funding

Hongyun Zheng acknowledges the financial support from the National Natural Sciences Foundation of China (Grant No. 71873050). Wanglin Ma acknowledges the funding support from the Chinese Academy of Agricultural Sciences for the Science and Technology Innovation Project (No. IFND2019-3) and the funding support from the National Agriculture Science Data Center for the Food Nutrition and Health project.

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Authors and Affiliations

  1. College of Economics and Management, Huazhong Agricultural University, Wuhan, 430070, China

    Hongyun Zheng

  2. Institute of Food and Nutrition Development, Ministry of Agriculture and Rural Affairs, Beijing, China

    Wanglin Ma

  3. Department of Global Value Chains and Trade, Faculty of Agribusiness and Commerce, Lincoln University, Christchurch, New Zealand

    Wanglin Ma

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Appendix

Appendix

See Tables 8, 9 and 10.

Table 8 Summary statistics of agricultural inputs
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Table 9 Average treatment effects of smartphone-based information acquisition on outcome variables using PSM and ESR models
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Table 10 Average treatment effects of smartphone-based information acquisition on agricultural inputs: IPWRA estimator
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Zheng, H., Ma, W. Smartphone-based information acquisition and wheat farm performance: insights from a doubly robust IPWRA estimator. Electron Commer Res 23, 633–658 (2023). https://doi.org/10.1007/s10660-021-09481-0

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