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Welfare, Nutritional, and Human Health Impacts of Post-Harvest Loss Prevention: A Large-Scale Field Experiment in Kenya (IMPACT)
Last registered on May 29, 2020
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Trial Information
General Information
Title
Welfare, Nutritional, and Human Health Impacts of Post-Harvest Loss Prevention: A Large-Scale Field Experiment in Kenya (IMPACT)
RCT ID
AEARCTR-0005845
Initial registration date
Not yet registered
Last updated
May 29, 2020 11:56 AM EDT
Location(s)

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Primary Investigator
Name
Matthias Huss
Affiliation
ETH Zurich
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Other Primary Investigator(s)
PI Name
Michael Brander
PI Affiliation
ETH Zurich
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PI Name
Menale Kassie
PI Affiliation
International Centre of Insect Physiology and Ecology (icipe)
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PI Name
Ulrike Ehlert
PI Affiliation
University of Zurich
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PI Name
Thomas Bernauer
PI Affiliation
ETH Zurich
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Additional Trial Information
Status
On going
Start date
2019-01-01
End date
2021-12-31
Keywords
Agriculture, Environment & Energy, Finance & Microfinance, Health, Welfare
Additional Keywords
Food Security, Post-Harvest Losses, Improved Storage
JEL code(s)
C93, D15, D25, D40, D60, D62, I30, O13, Q01, Q11, Q12
Secondary IDs
Abstract
Nourishing a growing world population in ecologically sustainable ways is one of the main goals of the United Nations’ 2030 Agenda for Sustainable Development. Current efforts prioritize increasing agricultural production, whereas reducing food waste and losses, including post-harvest losses, receives much less attention in policy-making. This bias is problematic, as hermetic storage bags, for instance, provide a simple and affordable means of preserving the quantity and quality of harvested food. Hermetic storage limits atmospheric oxygen, which causes desiccation of insects and other pests that damage stored grains.

Hermetic storage bags could thus, in principle, curb post-harvest losses and allow farmers to store their produce longer. This, in turn, could improve food security, food safety and incomes without putting additional pressure on natural resources, notably in poor areas of the world dominated by smallholder farming and high levels of food insecurity. However, as yet, the literature on human welfare impacts of post-harvest loss reduction is scarce and there is virtually no systematic empirical research on the implications of these technologies for a wide range of crucial outcomes.

This project addresses this research gap and analyzes the effects of improved on-farm storage on smallholder farmer’s welfare, in particular their a) income, poverty, and food security and b) nutrition and human health with a focus on pregnant women and newborns. We further analyse the potential of improved on-farm storage for reducing the adverse effects of fluctuating yields (e.g., due to climate change or other causes) on the main outcomes of interest. To analyze these effects, we implement a large-scale Randomized Control Trial (RCT) in Kenya. The randomly allocated intervention are five hermetic storage bags per smallholder farming household, with a capacity of 100kg of maize per bag, and a standardized training session on their use.
External Link(s)
Project Website
Project Website (Health Component)
Registration Citation
Citation
Bernauer, Thomas et al. 2020. "Welfare, Nutritional, and Human Health Impacts of Post-Harvest Loss Prevention: A Large-Scale Field Experiment in Kenya (IMPACT)." AEA RCT Registry. May 29. https://doi.org/10.1257/rct.5845-1.1.
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Experimental Details
Interventions
Intervention(s)
The randomly allocated intervention are five hermetic storage bags per smallholder farming household, with a capacity of 100kg of maize per bag, and a standardized training session on their use.
Intervention Start Date
2019-09-03
Intervention End Date
2019-09-15
Primary Outcomes
Primary Outcomes (end points)
Net-Income; Poverty (long-term); Food Security;
Primary Outcomes (explanation)
We use the Progress out of Poverty Index (PPI) to assess the baseline poverty status of households in relation to the international poverty line. However, PPI is relatively insensitive to changes in poverty status in the short run. We hence use a complimentary strategy to measure short-run effects based on the net-income from crop (maize) sales in participating smallholder households. Net-income is calculated as the difference between revenues from crop sales and expenditures for crop purchases. Self-assessed food insecurity is measured through the reduced Coping Strategies Index (rCSI). Standard weights and thresholds will be used to classify rCSI values into food (in)security categories. Data is collected through SMS-based mobile phone surveys, which is an efficient and effective method to collect data at high frequency.
Secondary Outcomes
Secondary Outcomes (end points)
Local market prices for maize; household maize stocks; maize sales and purchase quantity and timings; quantitative and qualitative post-harvest storage losses; maternal and child physical and mental health
Secondary Outcomes (explanation)
On-site visits will be used to collect detailed nutrition and health data for pregnant women and their newborns, and to collect grain samples to analyze quantitative and qualitative storage losses, and aflatoxin contamination (subject to the availability of funding). These on-site visits take place in randomly selected sub-samples of the study population. Market prices, household stocks, as well as sales and purchase information, are collected through SMS-based mobile phone surveys.
Experimental Design
Experimental Design
We use a matched-pair, cluster-randomization design (Imai, King and Nall, 2009). To minimize spill-over effects from treatment to control groups, matching and subsequent random allocation is done at the level of spatial clusters of farmer groups.
Experimental Design Details
Not available
Randomization Method
Automated random allocation, based on a random number seed for reproducibility, assigning the clusters in each matched pair to treatment or control conditions.
Randomization Unit
Random allocation is at the level of spatial clusters of farmer groups.
Was the treatment clustered?
Yes
Experiment Characteristics
Sample size: planned number of clusters
62 spatial clusters of farmer groups
Sample size: planned number of observations
5400 smallholder households (plus around 2500 households to estimate spillovers)
Sample size (or number of clusters) by treatment arms
31 spatial clusters of farmer groups in treatment, 31 spatial clusters of farmer groups in control
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials
IRB
INSTITUTIONAL REVIEW BOARDS (IRBs)
IRB Name
ETH Zurich Ethics Commission
IRB Approval Date
2018-08-28
IRB Approval Number
EK 2018-N-51
Analysis Plan