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Drought-tolerant Maize in East Afric...

Paul, Laura Anne.

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Drought-tolerant Maize in East Africa: Crop Resilience, Yield Gap, and Farmers' Adoption Decisions.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Drought-tolerant Maize in East Africa: Crop Resilience, Yield Gap, and Farmers' Adoption Decisions./
作者:	Paul, Laura Anne.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2019,
面頁冊數:	113 p.
附註:	Source: Dissertations Abstracts International, Volume: 81-04, Section: A.
Contained By:	Dissertations Abstracts International81-04A.
標題:	Agricultural economics. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=22617583
ISBN:	9781392473337

Drought-tolerant Maize in East Africa: Crop Resilience, Yield Gap, and Farmers' Adoption Decisions.
Paul, Laura Anne.

Drought-tolerant Maize in East Africa: Crop Resilience, Yield Gap, and Farmers' Adoption Decisions. - Ann Arbor : ProQuest Dissertations & Theses, 2019 - 113 p.

Source: Dissertations Abstracts International, Volume: 81-04, Section: A.

Thesis (Ph.D.)--University of California, Davis, 2019.

This item must not be sold to any third party vendors.

Crop failure from drought has severe economic and welfare consequences for farmers, particularly in Eastern and Southern Africa. The vulnerability of households without resources exacerbates the consequences of crop failure. Improved crop varieties, such as Drought-Tolerant (DT) maize, can increase yield levels while decreasing yield variability. Yet farmers are slow to adopt DT maize varieties despite the potential for increased yield stability and income security. Chapter 1 introduces the research questions, focused on why DT adoption is low, Chapter 2 provides a literature review on maize, drought, and DT technologies, and Chapter 3 describes the data from On-Farm Trials, weather data, and household survey data. These set up the analysis in Chapter 4 of DT maize yield outcomes, and in Chapter 5 on the role of availability bias in adoption decisions. Chapter 6 concludes the dissertation, suggesting the limitations of DT maize as a solution to food insecurity in East Africa. In the first of two analytical chapters, Chapter 4 identifies the unconditional and stochastic advantages of the DT trait using high resolution climate data, while also demonstrating heterogeneity among farms. DT maize has a significant unconditional yield advantage over comparison varieties in the On-Farm Trials. Further, there is a stochastic benefit, or protective effect, to the DT trait: it is indeed a more resilient variety under drought conditions. The DT maize has an average yield gain of 10% over comparison varieties under normal rainfall levels, and that benefit increases to 12% in drought conditions. There is significant heterogeneity in returns from the DT maize seed technology--lower-productivity farms experience the weakest unconditional and stochastic benefits. Variation in realized advantages might reduce the large expected benefits from the DT maize technology. Chapter 5 analyzes the adoption of DT maize in the context of expectations of the stochastic and heterogeneous benefits to the technology. A farmer's adoption decision is based on subjective beliefs about the likelihood of drought and the crop response to drought stress. Farmers' expectations of drought likelihood depend on experience and on common cognitive biases. The adoption decision model gives insight into the limited uptake of DT maize due to the role of information and expectations. Detailed household survey data combined with high-resolution climate and yield data show that adoption patterns indicate only a limited comprehension of how the DT trait actually works. Additionally, cognitive biases, such as recency and salience bias, might encourage adoption of DT among farmers.

ISBN: 9781392473337Subjects--Topical Terms:

3172150
Agricultural economics.
Subjects--Index Terms:

Africa

Drought-tolerant Maize in East Africa: Crop Resilience, Yield Gap, and Farmers' Adoption Decisions.
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520 $a Crop failure from drought has severe economic and welfare consequences for farmers, particularly in Eastern and Southern Africa. The vulnerability of households without resources exacerbates the consequences of crop failure. Improved crop varieties, such as Drought-Tolerant (DT) maize, can increase yield levels while decreasing yield variability. Yet farmers are slow to adopt DT maize varieties despite the potential for increased yield stability and income security. Chapter 1 introduces the research questions, focused on why DT adoption is low, Chapter 2 provides a literature review on maize, drought, and DT technologies, and Chapter 3 describes the data from On-Farm Trials, weather data, and household survey data. These set up the analysis in Chapter 4 of DT maize yield outcomes, and in Chapter 5 on the role of availability bias in adoption decisions. Chapter 6 concludes the dissertation, suggesting the limitations of DT maize as a solution to food insecurity in East Africa. In the first of two analytical chapters, Chapter 4 identifies the unconditional and stochastic advantages of the DT trait using high resolution climate data, while also demonstrating heterogeneity among farms. DT maize has a significant unconditional yield advantage over comparison varieties in the On-Farm Trials. Further, there is a stochastic benefit, or protective effect, to the DT trait: it is indeed a more resilient variety under drought conditions. The DT maize has an average yield gain of 10% over comparison varieties under normal rainfall levels, and that benefit increases to 12% in drought conditions. There is significant heterogeneity in returns from the DT maize seed technology--lower-productivity farms experience the weakest unconditional and stochastic benefits. Variation in realized advantages might reduce the large expected benefits from the DT maize technology. Chapter 5 analyzes the adoption of DT maize in the context of expectations of the stochastic and heterogeneous benefits to the technology. A farmer's adoption decision is based on subjective beliefs about the likelihood of drought and the crop response to drought stress. Farmers' expectations of drought likelihood depend on experience and on common cognitive biases. The adoption decision model gives insight into the limited uptake of DT maize due to the role of information and expectations. Detailed household survey data combined with high-resolution climate and yield data show that adoption patterns indicate only a limited comprehension of how the DT trait actually works. Additionally, cognitive biases, such as recency and salience bias, might encourage adoption of DT among farmers.
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