Assessing the Impact of Agricultural Technology Adoption on Farmers' Well‐being Using Propensity‐Score Matching Analysis in Rural China

Wu, Haitao; Ding, Sheng; Pandey, Sushil; Tao, Dayun

doi:10.1111/j.1467-8381.2010.02033.x

Cited by 91 publications

(68 citation statements)

References 16 publications

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“…For instance, the large proportion of studies (e.g. Mendola 2007;Becerril and Abdulai 2010;Wu et al 2010;Kassie, Shiferaw, and Muricho 2011;Awotide et al 2013) relied on the propensity score matching (PSM) approach. However, this technique only works if the difference between the two groups can be captured by using only observable variables.…”

Section: Introductionmentioning

confidence: 99%

The Impact of improved maize varieties on farm productivity and wellbeing: evidence from the East Hararghe Zone of Ethiopia

Ahmed

Geleta

Tazeze

et al. 2017

Development Studies Research

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The aim of this study is to measure the impact of improved maize varieties on farm productivity and smallholders' wellbeing using data collected from the East Hararghe Zone of Ethiopia. We combined propensity score matching method with endogenous switching regression to estimate the impact on the welfare of farmers and we applied the stochastic frontier corrected for sample selection to measure the impact on farm productivity. The results show that adoption of improved maize varieties leads to significant gains in wellbeing and improves farm productivity. ARTICLE HISTORY

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Section: Introductionmentioning

confidence: 99%

The Impact of improved maize varieties on farm productivity and wellbeing: evidence from the East Hararghe Zone of Ethiopia

Ahmed

Geleta

Tazeze

et al. 2017

Development Studies Research

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“…In order to reduce the estimation bias caused by the possibly existed endogeneity of land tenure security, only the village level tenure security variable was introduced. Market access is found to be positively correlated with intercropping adoption [84]. Meanwhile it is also relevant to income, since market access is crucial in deriving incomes from fruit and farming.…”

Section: Variable Definition and Descriptive Statisticsmentioning

confidence: 99%

Assessing the Effect of a Crop-Tree Intercropping Program on Smallholders’ Incomes in Rural Xinjiang, China

2017

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Governments in developing counties often promote intercropping (crops intercropped with fruit trees on cultivated land) schemes in order to improve smallholders' income. However, the implementation of such schemes is often hindered by inappropriate institutional environments and inefficient project management. It is important to assess the impacts of such intercropping programs, especially since such a cultivation strategy can often align closely with smallholders' livelihood strategies, particularly in poor and remote rural regions. This paper attempts to assess the impact of an intercropping program on participants' incomes in rural Xinjiang (China), and to explore the possible shortcomings in the program's design and implementation. We apply a propensity score matching method, based on a survey dataset of 352 households, supplemented with descriptive analysis based on our anecdotal field observations. The findings demonstrate that the intercropping program had negative effects on the incomes that participants derived from farming, their off-farm income and their gross income. Overall, participants experienced significant losses of income. Anecdotal observations show that land tenure insecurity played a crucial role in negating the anticipated income improvement effect of this program. Farmer's perceptions that they have limited security of tenure made them reluctant to invest the necessary time and resources to make the new cropping systems a success, while the available subsidies only partially covered the costs involved. In addition, the program led to a significant drop in yields of field crops as the trees were competing for a limiting and fixed supply of irrigation water.

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“…According to Caliendo & Kopeinig (2005), propensity score is the probability of the participants for observed characteristic X. Propensity score matching method compares average outcomes of the adopters and non-adopters based on estimated propensity score values. If technology was randomly assigned to farmers, the causal effect of technology adoption can be assessed by comparing the difference of variables between treated and untreated, however, the technology is rarely randomly assigned in non-experimental studies which results self-selection bias (Wu et al 2010). When treatments were not randomly assigned, it was difficult to determine casual inferences whether the difference in outcome between the treated and control groups was due to the treatment effect or other characteristics.…”

Section: Theoretical Frameworkmentioning

confidence: 99%

The Impact of Village Poultry Technology Adoption on the Livelihood of Smallholder Farmers in the Central Oromia Region, Ethiopia

Tsadik¹,

Z²

2015

J. Anim. Prod. Adv.

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The study was conducted to assess the impact of village poultry technology adoption on smallholder farmers in central Oromia Region, Ethiopia.Using multi-stage random sampling method, 180 technology participants were selected for face to face interview. Structured questionnaire was employed to collect data. Propensity score matching (PSM) Logit model was used to test the impact of the technology. The study revealed that adopters were significantly benefited by 68.5% from the technology and could produce 101 more eggs per/layer, consumed 18 more eggs/year and got 168.65 Birr more income per layer/year as compared to non-adopters. In conclusion, improved chicken breeds intervention had positive impact on average treatment effect on treated (ATT) and average treatment effect (ATE) on study population. Except livelihood change, the significant differences between adopters and non-adopters on outcome variables were not due to hidden bias but due to the treatment effect of technology intervention.

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Assessing the Impact of Agricultural Technology Adoption on Farmers' Well‐being Using Propensity‐Score Matching Analysis in Rural China

Cited by 91 publications

References 16 publications

The Impact of improved maize varieties on farm productivity and wellbeing: evidence from the East Hararghe Zone of Ethiopia

The Impact of improved maize varieties on farm productivity and wellbeing: evidence from the East Hararghe Zone of Ethiopia

Assessing the Effect of a Crop-Tree Intercropping Program on Smallholders’ Incomes in Rural Xinjiang, China

The Impact of Village Poultry Technology Adoption on the Livelihood of Smallholder Farmers in the Central Oromia Region, Ethiopia

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