Financial Inclusion, Technology Adoption, and Farm productivity: Experimental Evidence from Smallholder Farmers in Ethiopia

Last registered on December 23, 2021


Trial Information

General Information

Financial Inclusion, Technology Adoption, and Farm productivity: Experimental Evidence from Smallholder Farmers in Ethiopia
Initial registration date
December 20, 2021

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
December 23, 2021, 10:42 AM EST

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



Primary Investigator

Adama Science and Technology University

Other Primary Investigator(s)

PI Affiliation
Adama Science and Technology University
PI Affiliation
Adama Science and Technology University

Additional Trial Information

In development
Start date
End date
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Smallholder farmers account 80% of Ethiopia’s farms and are crucial in the effort to end hunger and alleviate malnutrition in the country. However, their farm productivity is poor due to their limited use of modern technologies in agriculture. Evidences show that smallholder farmers lack financial ability to purchase modern technologies that are required to increase their farm productivity and income. Evidently, smallholder farmers in Ethiopia have been excluded from the modern financial system and have no or little access to financial credits provided by financial institutions. With the goal of making financial institutions accessible to rural farmers, the National Bank of Ethiopia (NBE) in collaboration with relevant stakeholders has designed an intervention plan called ‘Rural Financial Inclusion Program’, to be implemented sooner or later. Among the objectives of the program is making financial credits accessible to rural farmers by tailoring collateral system of financial institutions to the needs of rural households. The goal of this study therefore is to examine the impact of the ‘Rural Financial Inclusion Program’ (specifically, access to financial credit) on smallholder farmers adoption of technologies (.e.g., fertilizers, improved seeds, irrigation, etc.) and to what extent the adoption of technologies in agriculture increase farm productivity and income of rural farmers using Randomized Controlled Trial (RCT) Design.
External Link(s)

Registration Citation

Bogale, Fetene, Shibiru Melesse and Birku Reta. 2021. "Financial Inclusion, Technology Adoption, and Farm productivity: Experimental Evidence from Smallholder Farmers in Ethiopia." AEA RCT Registry. December 23.
Experimental Details


Intervention Start Date
Intervention End Date

Primary Outcomes

Primary Outcomes (end points)
Agricultural technology adoption, farm productivity, and farm income
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
The aim of this research is to examine if access to credit increases the extent of smallholder farmers’ adoption of modern technologies in agriculture and ultimately farm productivity and income. To do so, we will conduct a randomized controlled trial design in rural part of Ethiopia as follows.

We will choose to districts (Woredas) in Oromia Regional State, the largest and most populous state in Ethiopia. In Ethiopia for administrative purposes, regions are subdivided into districts (Woreds). The districts (Woreds) are sub divided into Kebeles and Kebeles into villages (groups). Rural Villages comprise up to 32 households and on average there are 24 villages in a kebele. Farming is the primary sources of income for rural households in Ethiopia in general.

We first identify farmers who meet the new criteria for getting credit from financial institutions in randomly selected villages in the two districts and register them. Second, inform farmers in the selected villages about the availability of financial credit and the minimum criteria to get the credit. Then after, we ask those who meet the minimum criteria and willing to take the financial credit to go to the nearest agricultural extension service center and get registered by providing all the necessary documents (e.g., land ownership certificate, etc.). Households in selected villages will be contacted through their respective village representatives (all villages have formal representatives who are accountable to kebele managers). Next, we obtain list of farmers who are willing to take financial credit and assess their eligibility for the credit against the minimum criteria set by financial institutions providing it.

After obtaining lists of willing and eligible farmers from each selected villages, we randomly assign the villages into treatment and control groups. Households who are in treatment village will be provided financial credit while households in the control group will not receive anything. That is, we cluster households at village levels.

Prior to assigning villages to treatment or control groups, we will collect baseline data from each village regarding population, land size, weather condition, main crop, soil type, distance from city (town), technology adoption history, credit history, etc. The baseline information is vital to understand the status quo and make sure that the two groups are balanced so that the two groups are different only in terms of access to financial credit. In addition, we will gather baseline information at household level in both treatment and control groups using indicators such as household size, technology adoption history, land size, livestock size, gender of head of a household, credit history, education, etc.

Having randomly assigned the villages to treatment or control groups, and collected baseline data, we provide credit to selected households in the treatment villages through financial institutions (Commercial banks), our implementing partners. The amount of credit will be decided depending on several factors such as the size of collateral presented by the credit applicant (in this case the smallholder farmer), amount requested by the applicant, and credit ceiling set by the borrowing institution.

After one year of financial credit provision to the treatment villages, we undertake end-line survey to collect data on our outcome variables including extent of adoption of technologies in agriculture and farm productivity, and income from both treatment and control villages.
Experimental Design Details
Randomization Method
Randomization is done in office by a computer
Randomization Unit
Randomization unit is village
Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters
96 villages
Sample size: planned number of observations
480 household heads
Sample size (or number of clusters) by treatment arms
240 treatment, 240 control
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
MDES= 0.25 for fertilizer adoption and SD= 0.43 (obtained from previous similar study)

Institutional Review Boards (IRBs)

IRB Name
IRB Approval Date
IRB Approval Number


Post Trial Information

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Is the intervention completed?
Data Collection Complete
Data Publication

Data Publication

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Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials