The Economics of Integrated Pest and Pollinators Management in Horticulture Production

Last registered on June 25, 2024
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Pre-Trial

Trial Information

General Information

Title
The Economics of Integrated Pest and Pollinators Management in Horticulture Production
RCT ID
AEARCTR-0013818
Initial registration date
June 18, 2024

Initial registration date is when the trial was registered.

It corresponds to when the registration was submitted to the Registry to be reviewed for publication.

First published
June 25, 2024, 9:23 AM EDT

First published corresponds to when the trial was first made public on the Registry after being reviewed.

Locations

Country
Ethiopia
Region
East Africa

Primary Investigator

Name
Mulat Goshu Gebeyehu
Affiliation
Department of Economics, College of Business and Economics, Addis Ababa University, Addis Ababa, Ethiopia and Social Sciences and Impact Assessment Unit, International Centre of Insect Physiology and Ecology (icipe), Nairobi, Kenya
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Other Primary Investigator(s)

PI Name
Zewdu Abro
PI Affiliation
International Centre of Insect Physiology and Ecology (icipe), Nairobi, Kenya
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PI Name
Menale Kassie
PI Affiliation
International Centre of Insect Physiology and Ecology (icipe) Nairobi, Kenya
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PI Name
Alemu Mekonnen
PI Affiliation
Department of Economics, College of Business and Economics, Addis Ababa University, Addis Ababa, Ethiopia
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PI Name
Abebe D. Beyene
PI Affiliation
Environment and climate Research Center, Policy Studies Institute, Addis Ababa, Ethiopia
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PI Name
Shepard Ndlela
PI Affiliation
International Centre of Insect Physiology and Ecology (icipe) Nairobi, Kenya
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PI Name
Samira Mohammed
PI Affiliation
International Centre of Insect Physiology and Ecology (icipe) Nairobi, Kenya
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Additional Trial Information

Status
In development
Start date
2023-10-01
End date
2026-07-31
Keywords
Agriculture, Behavior, Firms & Productivity, Gender, Welfare
Additional Keywords
Integrated pest management, pollinators management, horticulture production, Digital Extension services
JEL code(s)
D13, Q12, Q16, O12, O13
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
Horticultural crops such as mangoes, avocados, and citrus are playing a crucial role to sub-Saharan African economies, supporting the livelihoods millions of farmers. Nevertheless, these crops face various challenges stemming from pests, diseases, and the impacts of climate change. Among the primary threats are fruit flies and white mango scale, causing significant economic losses. The uptake of Integrated Pest and Pollination Management (IPPM) presents a promising strategy to prevent crop damages caused by pests and diseases, ultimately leading to increased yields and income, while simultaneously reducing the dependency on uses of harmful agrochemicals like pesticides. Yet, the adoption of IPPM remains low due to insufficient extension services, resulting in poor knowledge and skills, limited access to IPPM resources, and inadequate economic incentives to foster adoption. Using a clustered randomized controlled trial (RCT), this research project evaluates the impact of three scaling strategies of IPPM. The interventions are Mango Integrated Pest Management (IPM) Training, Mango Integrated Pest and Pollination Management (IPPM) training and beehive distribution to farmers to place in their mango orchards, and Mango Integrated Pest and Pollination Management with Digital Extension (IPPM-DE). The study will evaluate the impacts of the interventions on IPPM adoption, mango yield, and income using data from 96 villages (944 mango farmers) in South Ethiopia Regional State. Analysis of covariance (ANCOVA) will be utilized to estimate the impact of the interventions.
External Link(s)

Registration Citation

Citation
Abro, Zewdu et al. 2024. "The Economics of Integrated Pest and Pollinators Management in Horticulture Production." AEA RCT Registry. June 25. https://doi.org/10.1257/rct.13818-1.0
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Experimental Details

Interventions

Intervention(s)
In this study, we introduce three interventions to tackle challenges facing mango farmers. The first intervention involves training lead farmers in Mango Integrated Pest Management (IPM) to implement IPM practices and create learning sites in their fields, promoting community sharing of knowledge and best practices in mango IPM.
The second intervention is Mango Integrated Pest and Pollination Management (IPPM), aiming to address pollinator deficits by providing beehives with colonies to farmers for placement in mango fields. This approach combines pest management with pollination to create a more ecosystem-friendly food production system that benefits both mango production and pollinators such as honeybees.
The third intervention is Mango Integrated Pest and Pollination Management with Digital Extension (IPPM-DE), enhances the impact of IPPM by utilizing digital platforms. Farmers will receive periodic information about mango integrated pest management (IPM) extension, market trends, pest dynamics, and pollinator management via SMS messages on their mobile phones.
Intervention Start Date
2024-07-01
Intervention End Date
2025-07-31

Primary Outcomes

Primary Outcomes (end points)
We are interested in assessing the impacts of the interventions on three primary outcome variables:
1. Adoption of IPPM practices
2. Mango yield (kg/tree), and
3. Total income from mango production (Birr).
Primary Outcomes (explanation)
1. Adoption of IPPM practices: Adoption of Integrated Pest and pollination Management (IPPM) will be defined in two ways: i) It will be defined as the adoption of one or more practices advocated by the project. These practices include topworking, orchard sanitation, pruning, maintaining regular spacing of mango trees, appropriate fertilizer application, fruit thinning, protective bagging of fruits, and introducing beehives into the mango orchard to promote pollination.
ii) IPPM adoption will also be defined by counting the number of IPPM practices that farmers have actually adopted. The more of these practices that a farmer includes into their mango production methods, the higher their level of adoption of IPPM.
2. Mango yield is amount of mango fruits produced (kg) divided by the total number of fruits giving mango trees.
3. Income from mango production is the price of mango the farmer receives (Birr/kg) times total mango produced (kg).

Secondary Outcomes

Secondary Outcomes (end points)
The secondary outcome variables are three. They are:
1. Mango fruit quality
2. visitation rate of honeybees and
3. Pollinator diversity.
Secondary Outcomes (explanation)
Secondary Outcomes (explanation)
1. Mango fruit quality assessment will involve two methods:
i) Farmers will rate the quality of their mangoes on a scale of 0 to 10, where 0 indicates poor quality and 10 indicates excellent quality.
ii) A mango quality index will be calculated using principal component analysis based on the survey design to evaluate mango quality.
2.Visitation rate of honeybees: refers to the frequency at which bees visit flowers to forage for nectar and pollen. It will be measured by observing the number of bee visits to flowers within a specific time period.
3. Pollinator diversity: refers variety of pollinators (like bees, butterflies, birds, etc.) in a given ecosystem (e.g., mango orchard) facilitating plant reproduction through pollen transfer. We will measure the diversity of pollinators along a distance gradient from local clusters of bee hives, in treatment villages. We will also measure the diversity of pollinators in comparable habitat in control villages.

Experimental Design

Experimental Design
For this study, we will utilize a village-level cluster randomized assignment approach. The villages were categorized into four arms for the study: Mango Integrated Pest Management (IPM) treatment (Arm 1), Mango Integrated Pest and Pollination Management (IPPM) (Arm 2), Mango Integrated Pest and Pollination Management with Digital Extension (IPPM-DE) (Arm 3), and pure control group (Arm 4). In Each treatment arm contains 24 villages and pure control arm contains 24 villages
Experimental Design Details
Not available
Randomization Method
Randomization will be done in the office using a computer.
Randomization Unit
Mango producer level randomization
Was the treatment clustered?
Yes

Experiment Characteristics

Sample size: planned number of clusters
96 villages
Sample size: planned number of observations
Total 944 Mango producing farmers
Sample size (or number of clusters) by treatment arms
Control, 236 (24 villages)
IPM training, 236 (24 villages)
IPPM training, 236 (24 villages)
IPPM training + digital extension, 236 (24 villages)

Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
It was determined by the available budgets
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
Institutional review board (IRB), College of Business and Economics, Addis Ababa University
IRB Approval Date
2024-03-05
IRB Approval Number
CBE/A/Dean/RTT/010/2024
Analysis Plan

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