Contract farming and rural transformation: Evidence from a field experiment in Benin

Arouna, Aminou; Michler, Jeffrey D.; Lokossou, Jourdain

doi:10.1016/j.jdeveco.2021.102626

Cited by 56 publications

(33 citation statements)

References 58 publications

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“…Since we are estimating associations between digital extension services and several outcome variables, it is possible that some significant results occur simply due to chance meaning that false positives may be an issue. To address this potential issue when testing multiple hypotheses, we follow Arouna et al [ 53 ] and present p -values corrected for the family-wise error rate (FWER), which is the probability of making at least one false discovery among a family of comparison, using the Bonferroni correction and Holm [ 54 ] adjusted p -values (see S4 Table in the supporting information). For our main results, we also present sharpened q -values adjusted for multiple hypotheses testing [ 55 ].…”

Section: Econometric Approachmentioning

confidence: 99%

Personalized digital extension services and agricultural performance: Evidence from smallholder farmers in India

Rajkhowa

Qaim

2021

PLoS ONE

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Productivity growth in smallholder agriculture is an important driver of rural economic development and poverty reduction. However, smallholder farmers often have limited access to information, which can be a serious constraint for increasing productivity. One potential mechanism to reduce information constraints is the public agricultural extension service, but its effectiveness has often been low in the past. Digital technologies could enhance the effectiveness of extension by reducing outreach costs and helping to better tailor the information to farmers’ individual needs and conditions. Using primary data from India, this study analyses the association between digital extension services and smallholder agricultural performance. The digital extension services that some of the farmers use provide personalized information on the types of crops to grow, the types and quantities of inputs to use, and other methods of cultivation. Problems of selection bias in the impact evaluation are reduced through propensity score matching (PSM) combined with estimates of farmers’ willingness to pay for digital extension. Results show that use of personalized digital extension services is positively and significantly associated with input intensity, production diversity, crop productivity, and crop income.

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Section: Econometric Approachmentioning

confidence: 99%

Personalized digital extension services and agricultural performance: Evidence from smallholder farmers in India

Rajkhowa

Qaim

2021

PLoS ONE

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“…LSLAs may also deliver benefits through contract farming, where those who gain control over land (often companies) act as buyers of crops grown by local farmers under contracts specifying price, quantity and other market specifications (Bellemare andLim 2018, Agrawal et al 2019). Outside the context of LSLAs, contract farming programs can improve smallholder farmer incomes and welfare under a variety of contract conditions (Bellemare 2012, Ton et al 2018, Arouna et al 2021, although concerns related to unequal access remain (Sulle 2017, Isager et al 2018, Martiniello 2021.…”

Section: Introductionmentioning

confidence: 99%

Impacts of large-scale land acquisitions on smallholder agriculture and livelihoods in Tanzania

Sullivan

Brown

Moyo

et al. 2022

Environ. Res. Lett.

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Improving agricultural productivity is a foundational sustainability challenge in the 21st century. Large-scale land acquisitions (LSLAs) have important effects on both well-being and the environment in the Global South. Their impacts on agricultural productivity and subsequent effects on farm incomes, food-security and the distribution of these outcomes across households remain under-investigated. In particular, prior studies do not sufficiently attend to the mechanistic nature of changes in household agricultural practices that affect LSLA outcomes. To address these challenges, we use a novel household dataset and a quasi-experimental design to estimate household-level changes in agricultural productivity and other LSLA outcomes in Tanzania. We use causal mediation analysis to assess how four common mechanisms - contract farming, land loss, market access and technology adoption around LSLAs - influence agricultural productivity. We find that households near LSLAs exhibit 20.2% (95% CI: 3.1 – 37.3%) higher agricultural productivity, primarily due to increased crop prices and farmer selection of high-value crops. Importantly, the direction and magnitude of effect sizes associated with the different mechanisms vary. The presence of contract farming explains 18.1% (95% CI: 0.56%, 47%) of the effect size in agricultural productivity, whereas land loss reduces agricultural productivity by 26.8% (95% CI: -71.3%, -4.0%). Market access and technology adoption explain little to no portion of the effect size on agricultural productivity. Despite higher agricultural productivity mediated by contract farming, we do not find increased household incomes or food security. Plausible explanations include limited market access, higher crop prices restricting food access and elite capture of contract farming concentrating income effects to a few households. Our results stand in contrast to assumptions that technological spillovers occur through LSLAs and are the principal drivers of LSLA-induced agricultural transformation. We find instead that access to contract farming and high-value crops lead to greater agricultural productivity, but also that benefits related to these mechanisms are unequally distributed.

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“…Other market support policies can have a greater impact on providing incentives for farmers to invest in greater crop quantity or quality. Impact evaluations have shown that the certainty provided by sales contracts between farmers and buyers implemented at the beginning of the season can have sizeable productivity impacts without any additional support (Arouna, Michler, and Lokossou 2021). Investments in scales and thirdparty quality certification have also been shown to incentivize productivity investments with net income increases for farmers (Bernard et al 2017;Saenger, Torero, and Qaim 2014).…”

Section: Spending To Address Market Failures Is Often Of Higher Value...mentioning

confidence: 99%

Poverty and Shared Prosperity 2022: Correcting Course

2021

101

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Some rights reserved 1 2 3 4 25 24 23 22 This work is a product of the staff of The World Bank with external contributions. The findings, interpretations, and conclusions expressed in this work do not necessarily reflect the views of The World Bank, its Board of Executive Directors, or the governments they represent. The World Bank does not guarantee the accuracy, completeness, or currency of the data included in this work and does not assume responsibility for any errors, omissions, or discrepancies in the information, or liability with respect to the use of or failure to use the information, methods, processes, or conclusions set forth. The boundaries, colors, denominations, and other information shown on any map in this work do not imply any judgment on the part of The World Bank concerning the legal status of any territory or the endorsement or acceptance of such boundaries.Nothing herein shall constitute or be construed or considered to be a limitation upon or waiver of the privileges and immunities of The World Bank, all of which are specifically reserved.

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Contract farming and rural transformation: Evidence from a field experiment in Benin

Cited by 56 publications

References 58 publications

Personalized digital extension services and agricultural performance: Evidence from smallholder farmers in India

Personalized digital extension services and agricultural performance: Evidence from smallholder farmers in India

Impacts of large-scale land acquisitions on smallholder agriculture and livelihoods in Tanzania

Poverty and Shared Prosperity 2022: Correcting Course

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