Do Search Frictions in the Retail Sector Cause Upstream Misallocation: Price Information Intervention

Last registered on October 28, 2024

Pre-Trial

Trial Information

General Information

Title
Do Search Frictions in the Retail Sector Cause Upstream Misallocation: Price Information Intervention
RCT ID
AEARCTR-0014638
Initial registration date
October 27, 2024

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
October 28, 2024, 1:42 PM EDT

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

Locations

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Primary Investigator

Affiliation
U.C. Santa Cruz

Other Primary Investigator(s)

PI Affiliation
U.C. Santa Cruz

Additional Trial Information

Status
On going
Start date
2024-08-14
End date
2024-12-13
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
The retail sector intermediates between the demands of consumers and the products of suppliers. This project will study whether the sourcing decisions of retailers—in particular, the efficiency of their search for cheaper suppliers—plays a quantitatively meaningful role in the allocation of resources across firms in upstream sectors. The final stage of the project is a randomized-controlled trial that will measure the impact of giving small retailers information about prices charged by suppliers. Treated shops will receive either general information about the distribution of prices, or specific price quotes and contact information for low-cost suppliers.
External Link(s)

Registration Citation

Citation
Samaniego de la Parra, Brenda and Ajay Shenoy. 2024. "Do Search Frictions in the Retail Sector Cause Upstream Misallocation: Price Information Intervention." AEA RCT Registry. October 28. https://doi.org/10.1257/rct.14638-1.0
Sponsors & Partners

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Experimental Details

Interventions

Intervention(s)
The study focuses on prices, purchases, and sales of four target products: onions, bananas, cooking oil, and water. The sample of retailers and suppliers are screened to sell one or more of the four target products. The study will survey roughly 850 retailers, and also suppliers in the locations where the retailers source their inventory. Each group (retailers and suppliers) will be surveyed in person, then contacted again by phone every two weeks to construct panel data on their prices and other data. The first round of the supplier panel will collect price quotes from suppliers that will be used in the intervention.

The retailers are divided into two treatment groups (T1 and T2) and a control group (C). The control group will receive only a suggestion that the most profitable retailers actively search for low-cost suppliers. T1 will receive the same general suggestion, and also general information about the distribution of prices. Specifically, this group will be given a flier that shows the quartiles of the distribution of price quotes, and an explanation of what the quartiles mean (e.g. 25% of retailers charge less than X). T2 will receive specific price quotes from relatively low cost suppliers: the exact price and the contact information of the supplier.

The study will measure impacts using two sources of data: the phone-based panel survey (which will run for 4 rounds, with the intervention beginning in Round 2), and expenditures from an inventory grant. The grant will be given to all retailers in all three groups, and paid as a reimbursement based on receipts that record the supplier as well as prices and quantities for all goods purchased. Enumerators will record these data to use as an additional dataset for measuring impacts.
Intervention Start Date
2024-10-28
Intervention End Date
2024-11-08

Primary Outcomes

Primary Outcomes (end points)
Buying from a new supplier
Order prices paid for inventory (adjusted for weight/volume)
Primary Outcomes (explanation)
New supplier = one not purchased from in the past 3 months, measured using a binary survey question

Secondary Outcomes

Secondary Outcomes (end points)
Search for new suppliers
Beliefs about the distribution of order prices
Purchases (stocking) and sale of target goods
Retail prices and per-unit profit
Share of sales to lower-cost suppliers
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
TBD
Experimental Design Details
Not available
Randomization Method
Randomization by Stata
Randomization Unit
Shops were clustered into spatial "groups" using ArcGIS Pro. A shop is included in a cluster if and only if it lies within 20m of a shop within the cluster. (If two clusters are within 20m, they are combined.)
Was the treatment clustered?
Yes

Experiment Characteristics

Sample size: planned number of clusters
221
Sample size: planned number of observations
842 shops. Some regressions will be done at the shop-product level, which would have an unpredictable number of observations depending on how many of the 4 target products are stocked by each shop.
Sample size (or number of clusters) by treatment arms
T1=73, T2=73, C=75
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Using conventional t-stat inference (with standard errors clustered at the unit of treatment) and only a single round of data (no control for pre-treatment outcomes) we are powered to detect a 12.5 percentage point reduction in the share that buy from a supplier purchased from in the past 3 months. At the time of submission we do not have the data needed to calculate power after controlling for baseline outcomes.
IRB

Institutional Review Boards (IRBs)

IRB Name
UC Santa Cruz IRB
IRB Approval Date
2024-05-16
IRB Approval Number
HS-FY2024-232
IRB Name
ERES Converge (Zambia)
IRB Approval Date
2024-08-02
IRB Approval Number
2024-Jul-005