Can Farmer Managed Natural Regeneration, and the formalization of land rights boost agricultural productivity on degraded lands of the Sahel? Evidence from Niger

Last registered on January 06, 2025

Pre-Trial

Trial Information

General Information

Title
Can Farmer Managed Natural Regeneration, and the formalization of land rights boost agricultural productivity on degraded lands of the Sahel? Evidence from Niger
RCT ID
AEARCTR-0015106
Initial registration date
January 03, 2025

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
January 06, 2025, 12:33 PM EST

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

Locations

Primary Investigator

Affiliation

Other Primary Investigator(s)

PI Affiliation
University of Connecticut
PI Affiliation
Williams & Mary University
PI Affiliation
Williams & Mary University

Additional Trial Information

Status
On going
Start date
2024-12-09
End date
2027-12-31
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
The lack of participative forest regulation and inclusive forest governance have been disincentives for the adoption of Farmer Managed Natural Regeneration (FMNR) for natural reforestation (Binam et al., 2017; Toudou et al., 2020; Garrity and Bayala, 2019). There is currently missing evidence on how FMNR and the role of land rights can improve natural reforestation. The current study aims to fill these gaps through a partnership with the World Agroforestry Center and World Vision, who have been training farmers on the practice of FMNR in Niger and supporting tree protection’s conventions. We propose to conduct an RCT to determine the impact of FMNR and land tenure security on reforestation. Understanding such impacts has the potential to improve the use of public funds and international donor funds for reforestation by highlighting high value complementary investments to increase reforestation.

Registration Citation

Citation
Benyishay, Ariel et al. 2025. "Can Farmer Managed Natural Regeneration, and the formalization of land rights boost agricultural productivity on degraded lands of the Sahel? Evidence from Niger." AEA RCT Registry. January 06. https://doi.org/10.1257/rct.15106-1.0
Experimental Details

Interventions

Intervention(s)
In Niger, it is estimated that between 40 and 50% of the land was affected by deforestation during the second half of the 20th century (Botoni et al., 2016). One of the solutions identified to address this problem is the practice of FMNR, which was developed in Niger following the discovery of an underground forest of tree stumps, roots, and seeds that can be used to regrow native trees and shrubs in previously clear-cut fields (Carey 2020). It entails selectively pruning tree suckers to encourage additional growth of the tree’s trunk. FMNR is a low-cost natural reforestation technique (Botoni et al. 2010). Among the targeted farmers in the study are landlords, land tenants and borrowers.
Training these low-income farmers to the practice of FMNR will hopefully contribute to increasing the vegetation cover on their land and communities, increase carbon absorption, reduce erosion and land degradation, limit desertification, improve their resilience to climate shocks through additional income gained from the selling of timber and non-timber forest products generated by trees grown on their land. However, many of these farmers have an informal land rights status which exposes them to risk of land conflicts or land eviction and can affect their decision to adopt FMNR practices. World Vision has worked with both local and central governments in Niger to establish a local land commission and has done pilot work by helping groups of farmers trained to the practice of FMNR to acquire individual legal customary land certificates from the local land commission.
Intervention Start Date
2025-04-01
Intervention End Date
2025-12-31

Primary Outcomes

Primary Outcomes (end points)
The environmental outcomes we intend to measure through this RCT are woody vegetation cover, distribution and density, and carbon absorption. We will use biomass measurement, biodiversity of above ground woody vegetation, and soil erosion prevalence. The social and economic outcomes we intend to measure include the level of investment in farming and regreening activities, annual crops yields, annual crops revenues, time spent by women and children to collect firewood, share of households reporting a land conflict, share of villages reporting a land conflict, level of trust in local land governance institutions, and share of households reporting using land as a collateral for loan. An improvement in these outcomes will contribute to farmers' resilience to climate shocks during the long dry season.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
The aim of this RCT is to understand the impact of FMNR programming and to correct market failures that limit the adoption at a large scale of the FMNR, by relaxing the access to land titles constraints.
Our randomization unit will be the farmer. 2000 farmers (see power calculation below) will be randomly assigned to the FMNR treatment, and 1000 farmers will be randomly assigned to control groups. Within the treatment group, 1000 farmers will receive the land rights intervention. Apart from Goldstein et al. (2018) and Lewis et al. (2020) who measured the effect of farmers’ acquisition of customary land right certificates on farming investments and forest loss in terms of woody vegetation cover in Benin, there is no existing RCT which has measured the effect of farmer’s access to customary land rights certificates on the previously mentioned outcomes in contexts similar to Niger.
Experimental Design Details
Not available
Randomization Method
We computed random number, sorted them and proceed to random assignments.
Randomization Unit
As said before, our randomization unit will be the farmer. 2000 farmers (see power calculation below) will be randomly assigned to the FMNR treatment, and 1000 farmers will be randomly assigned to control groups. Within the treatment group, 1000 farmers will receive the land rights intervention.
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
The designed is not clustered.
Sample size: planned number of observations
The total number of farmers randomly assigned to treatment and control group is 3000: 2000 farmers are randomly assigned to treatment groups, and 1000 farmers are randomly assigned to the control group.
Sample size (or number of clusters) by treatment arms
As said before, 2000 farmers (see power calculation below) will be randomly assigned to the FMNR treatment, and 1000 farmers will be randomly assigned to control groups. The total sample size is 3000 farmers.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
The sample size has been calculated for the outcome “tree cover (proportion of land covered with trees)”. It is the only outcome for which existing studies, most notably Goldstein et al. (2018) and Lewis et al. (2020), have calculated a treatment effect. According to these authors, acquiring customary land certificates reduces annual tree cover loss by 0.1 to 0.3 percentage point in Benin. The baseline mean value and standard deviation of tree cover calculated by ICRAF (2022) are 0.66 and 0,02, respectively. We estimated an annual treatment effect of 0.1266 percentage point increase in tree cover as a result of FMNR and a maximum sample size of 3000, assuming a power target of 80% and a significance level of 5%. The treatment effect will be 0.1266 percentage point times three over the project duration (03 years). Our power calculation result is presented below. Note that this assumes comparing two treatment groups against each other, and then against the control.
IRB

Institutional Review Boards (IRBs)

IRB Name
Williams & Mary University
IRB Approval Date
2024-05-01
IRB Approval Number
PHSC-2024-04-05-16972-abenyishay