Rural Roads and Agricultural Value Chains

Last registered on January 23, 2023


Trial Information

General Information

Rural Roads and Agricultural Value Chains
Initial registration date
January 11, 2023

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 23, 2023, 5:55 AM EST

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



Primary Investigator

The World Bank

Other Primary Investigator(s)

PI Affiliation
The World Bank
PI Affiliation
The World Bank
PI Affiliation
The World Bank
PI Affiliation
University of California-Berkeley
PI Affiliation
The World Bank

Additional Trial Information

On going
Start date
End date
Secondary IDs
Prior work
This trial is based on or builds upon one or more prior RCTs.
What are the impacts of transportation costs on agricultural value chains? We introduce experimental variation in transportation costs by randomizing the provision of transportation services for agricultural produce from truckers to randomly selected farmers and local aggregators. We estimate impacts on prices, transportation costs, and agricultural production and marketing. In addition, we use a BDM mechanism to elicit truckers' costs of providing transportation services; we combine this with transaction-level data to shed light on the determinants of intermediation in agricultural value chains including transportation costs.
External Link(s)

Registration Citation

Gonzalez-Navarro, Marco et al. 2023. "Rural Roads and Agricultural Value Chains." AEA RCT Registry. January 23.
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Experimental Details


We use a BDM mechanism to recover revealed preference estimates of transportation costs along feeder roads for truckers using these randomized subsidies (Berry et al., 2020). We focus on the cost of a single trip between a remote community and the nearest market, as qualitative work has suggested this is the service truckers typically contract over with farmers or rural aggregators in remote communities. Truckers are randomly assigned a price for providing transportation services to randomly selected rural aggregators and farmers. To implement this, we offer traders a contract to provide a single trip of transportation services to a selected rural aggregator and 5 selected farmers. The contract will ask the trucker to ration space in the truck first to the farmers and then to the rural aggregator. We ask the trucker the minimum price they would need to be paid to fulfill this contract, and then randomly select a price from a range of prices. If the minimum price they requested is higher than the selected price, then no transaction occurs. However, if the minimum price they requested is lower than the selected price, they are paid the selected price conditional on fulfilling the contract. To minimize probability of default, the contracts will include a stamp indicating formal endorsement. Standard theory suggests that traders will bid their marginal cost of providing transportation services, which is useful for measurement. We implement this WTA exercise for both the 2023 long rainy season (2023A) and the 2023 short rainy season (2023B) harvests.

Farmers and Rural aggregators
Within each village, we randomize which farmers or aggregators the truckers will be connected to. For both farmers and rural aggregators, they will be informed at the start of the 2023A and 2023B seasons just before planting and told that these services will be made available at the end of 2023A and 2023B. In communities where only one trucker bid below their offered price for transportation services, we will ask that they coordinate with the 5 selected farmers, and that priority for space in the truck go to the farmers. In communities where 0 truckers bid below their offered price for transportation services, we will identify a fourth trucker and pay them the prevailing price for transportation services where one exists, in order to ensure that selected farmers and rural aggregators in each community receive transportation services. In communities not yet accessible by road because their feeder road segment has not yet been rehabilitated and no road accessible to vehicles exists that can reach the remote community, this intervention will not be possible. Comparisons across farmers and rural aggregators within community allow estimates of the impacts of reduced transportation costs on producer prices.
Intervention Start Date
Intervention End Date

Primary Outcomes

Primary Outcomes (end points)
Trade flows (traffic counts, number of trips), trade costs, price of transportation services for farmers & rural aggregators, agricultural sales & prices, agricultural production
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
The randomly assigned treatment is the randomly selected price offered in the willingness-to-accept exercise. Prices will be randomized stratified at the feeder road segment level, to ensure that at least one trucker receives a high offered price per segment, ensuring that transportation services are procured in each feeder road segment. These auctions will be conducted towards the end of the 2023A and 2023B seasons, just before farmers and rural aggregators ship harvests from those seasons. This randomization is conducted independently for 2023A and 2023B.

Rural aggregators
In each remote community, one rural aggregator is randomly selected (from a pool of two listed rural aggregators) to be connected to transportation services. Rural aggregators are told that we’ve procured transportation services on their behalf from truckers, and that they can use these services as they would like.

In each remote community, five farmers are randomly selected (from the pool of 10 surveyed farmers) to be connected to transportation services. Farmers are told that we’ve procured transportation services on their behalf from truckers, and that they can use these services as they would like.
Experimental Design Details
Not available
Randomization Method
Trucker offers, and the selection of aggregators and farmers is randomized in office by a computer using R
Randomization Unit
Farmer, Rural aggregator, and Trucker
Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters
543 truckers across 181 road segments
1,810 farmers across 181 road segments
362 rural aggregators across 181 road segments
Sample size: planned number of observations
543 observations of truckers across 181 road segments 1,810 observations of farmers across 181 road segments 362 observations of rural aggregators across 181 road segments
Sample size (or number of clusters) by treatment arms
905 farmers receive transportation services, 905 farmers in control
181 rural aggregators receive transportation services, 181 rural aggregators in control
181 truckers offered low prices, 181 truckers offered medium prices, 181 truckers offered high prices
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
We provide estimates of the MDE for our most important farmer level outcome, prices of agricultural output that farmers receive. Using household survey data we’ve collected in Rwanda, we estimate that a regression of log price on treatment, with 182 communities, two seasons of household survey data, 10 households per community, and treatment randomly assigned at the household level stratified at the community level, yields a standard error of 0.047. This implies a minimum detectable effect of 0.13 with 80% power and 5% alpha. In other words, we will be powered to detect the effect of access to transportation services on prices if this increase prices by 13%.

Institutional Review Boards (IRBs)

IRB Name
Innovations for Poverty Action
IRB Approval Date
IRB Approval Number