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Information Frictions and Firm Growth in Liberia
Last registered on August 21, 2017


Trial Information
General Information
Information Frictions and Firm Growth in Liberia
Initial registration date
June 13, 2017
Last updated
August 21, 2017 4:20 PM EDT
Primary Investigator
Other Primary Investigator(s)
PI Affiliation
Columbia University
Additional Trial Information
On going
Start date
End date
Secondary IDs
Information frictions appear to be pervasive in poor countries (Allen, 2012) and to severely constrain firm and market growth (Jensen, 2012). The goal of the study is to understand information frictions between buyers and suppliers in Liberia. While a lot of procurement tenders are published, it appears that some suppliers have an “information deficit” – e.g., that they lack knowledge about how to apply to tenders or believe that it is not possible for them to win tenders – that leads them to not submit bids. An NGO, Building Markets, runs a training that aims at teaching SMEs how to apply to tenders, and how to maximize their chances of winning. This project will (a) test the impact of the training and (b) seek to understand whether and how information frictions prevent SMEs from taking profitable actions by using different information provided to firms encouraged to get trained.
Registration Citation
Hjort, Jonas and Jonas Hjort. 2017. "Information Frictions and Firm Growth in Liberia." AEA RCT Registry. August 21. https://doi.org/10.1257/rct.2264-3.0.
Former Citation
Hjort, Jonas, Jonas Hjort and Jonas Hjort. 2017. "Information Frictions and Firm Growth in Liberia." AEA RCT Registry. August 21. http://www.socialscienceregistry.org/trials/2264/history/20666.
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Experimental Details
Firms in the treatment group are encouraged to attend a training session that teaches them how to apply to tenders.
Intervention Start Date
Intervention End Date
Primary Outcomes
Primary Outcomes (end points)
The key outcome variables are the capacity of the firm to apply to tenders, and to win bids, as well as the overall performance of the firm.
Primary Outcomes (explanation)
The capacity of the firm to apply to and to win tenders is measured by the number of bids submitted by the firms, the number of contracts won and the details of the bids and contracts (sector, clients, amount).
The overall performance of the firm is measure by the usual metrics of firms’ performance: the number and type of employees, the revenues and profits of the firm, intermediate actions (e.g. importing), as well as the firm qualifications (registration status, licenses, etc.).
Secondary Outcomes
Secondary Outcomes (end points)
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
The sample firms are randomly divided into a treatment and a control group. Only treatment firms are visited at baseline and encouraged to attend a training session.
Experimental Design Details
Because firm behaviors and outcomes at baseline can be measured in pre-existing Building Markets surveys, only the treatment firms are visited at baseline. They are given the opportunity to attend the training for free. Control firms can also attend training if they wish, but they have to pay the $50 fee and they are not visited by the research team and encouraged to do so. Several different sub-treatments are used to encourage firms to attend the training and to apply to tenders. These focus on the performance of firms of different types who did or did not attend the training/apply to tenders in the past.
Randomization Method
The randomization was done in office by a computer, the sample was separated into strata (by sector, geographical zone and number of employees) and the randomization was done within each strata to ensure a balanced sample in both groups.
Randomization Unit
The randomization was done at the firm level.
Was the treatment clustered?
Experiment Characteristics
Sample size: planned number of clusters
Sample size: planned number of observations
Sample size (or number of clusters) by treatment arms
840 firms were selected into treatment, and 420 into treatment.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
In the target group, firms bid on average on 1.10 (sd 2.9) tenders in the 6 months preceding the survey, and win 0.43 (sd 1.77). With a sample size of 1000 firms (334 control group, 667 in the treated group), a power of 0.8, and an 𝛼 of 0.05, to have a significant impact on the observed firms, the treatment needs to increase: - The number of bids by 0.55 (from 1.10 to 1.65) - The number of contracts won by 0.33 (from 0.43 to 0.76) These seem like reasonable effects, given that previous to this experiment firms who took the training have bid on twice as many tenders and win almost twice as many bids than firms who did not take the training.
IRB Name
Columbia University IRB
IRB Approval Date
IRB Approval Number
Analysis Plan

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Post Trial Information
Study Withdrawal
Is the intervention completed?
Is data collection complete?
Data Publication
Data Publication
Is public data available?
Program Files
Program Files
Reports, Papers & Other Materials
Relevant Paper(s)