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Why Don’t Small Firms Merge? Experimental Evidence on Information Barriers
Last registered on March 29, 2021

Pre-Trial

Trial Information
General Information
Title
Why Don’t Small Firms Merge? Experimental Evidence on Information Barriers
RCT ID
AEARCTR-0007428
Initial registration date
March 28, 2021
Last updated
March 29, 2021 10:56 AM EDT
Location(s)

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Primary Investigator
Affiliation
New York University Abu Dhabi
Other Primary Investigator(s)
PI Affiliation
IZA - Institute of Labor Economics
PI Affiliation
CERGE-EI Prague
PI Affiliation
New York University Abu Dhabi
Additional Trial Information
Status
On going
Start date
2019-08-01
End date
2022-04-01
Secondary IDs
Abstract
This research project aims to experimentally investigate information barriers to small firm consolidation. We exploit rich panel data on the universe of garment making firm owners in Hohoe, Ghana, including owner and owner household characteristics, firm characteristics and outcomes, and reported within-industry peer network interactions. We elicit firm owners’ willingness to pay for information about within-industry peer willingness to hire and be hired by the owner using Becker-Degroot-Marschak method and exploit the conditionally random variation to study the impacts of such information on firm-level growth and profitability as well as dyadic-level mergers.
External Link(s)
Registration Citation
Citation
Hardy, Morgan et al. 2021. "Why Don’t Small Firms Merge? Experimental Evidence on Information Barriers." AEA RCT Registry. March 29. https://doi.org/10.1257/rct.7428-1.0.
Experimental Details
Interventions
Intervention(s)
The intervention is the receipt of (a) list(s) of names of other firm owners the market that are willing to hire or be hired by the treated individual.
Intervention Start Date
2020-01-15
Intervention End Date
2020-02-15
Primary Outcomes
Primary Outcomes (end points)
firm size (number of workers and wage expenses), firm performance (profits and sales), firm boundaries (outsourcing expenses and revenue, capital rental expenses and revenue)
Primary Outcomes (explanation)
Secondary Outcomes
Secondary Outcomes (end points)
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
Following the Becker-Degroot-Marschak (BDM) method, each respondent receives 5
GHC (approximately 91 US cents at the time of the first wave) that can be used as offers
for the lists of other firm owners that are willing to work for or willing to hire the
respondent. Respondents can then bid for each list (in integer amounts), with a maximum
possible bid for each list of 3 GHC. Then, the price for the list is randomly drawn and takes
integer values between 0 and 4 GHC. If the bid is greater than or equal to the price, then
the list is successfully purchased, and any amount not spent is returned to the respondent
in cash. Each respondent was also placed into four different treatment groups, where the
information on the list varied. These groups are further described in the attached analysis plan.
Experimental Design Details
Not available
Randomization Method
Price randomization was completed by researchers using STATA prior to entering the field and preloaded on Survey CTO to be revealed to respondent (and enumerator) after willingness to pay exercise.
Randomization Unit
Firm owner
Was the treatment clustered?
No
Experiment Characteristics
Sample size: planned number of clusters
Information was randomized at the respondent (firm owner) level. There were 569 firm owners in the market identified during our census.
Sample size: planned number of observations
The number of observations varies by outcome (between 1 and 6 post-observations per firm owner).
Sample size (or number of clusters) by treatment arms
This is non-trivial for this project as the random treatment is conditional on willingness to pay.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB
INSTITUTIONAL REVIEW BOARDS (IRBs)
IRB Name
New York University Abu Dhabi
IRB Approval Date
2017-12-01
IRB Approval Number
Legacy-109-2017
Analysis Plan
Analysis Plan Documents
Analysis Plan

MD5: ea2dfbe3b760b0819cbf812362b3c13e

SHA1: c90d093fe8768b630832aeb742ef39f8e60b21f0

Uploaded At: March 28, 2021