Weathering the Waste: Inventory Choice, Market Aggregation, and Food Loss Among Urban Street Vendors

Last registered on June 29, 2026

Pre-Trial

Trial Information

General Information

Title
Weathering the Waste: Inventory Choice, Market Aggregation, and Food Loss Among Urban Street Vendors
RCT ID
AEARCTR-0018750
Initial registration date
June 29, 2026

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
June 29, 2026, 9:46 AM 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
London School of Economics and Political Science

Other Primary Investigator(s)

PI Affiliation
London School of Economics and Political Science

Additional Trial Information

Status
In development
Start date
2026-07-15
End date
2027-01-22
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
Do decentralized markets efficiently aggregate supply decisions when firms must commit inventory under correlated uncertainty? We study street vendors selling perishable produce in Patna, India, who first commit to inventory at wholesale markets then set retail prices during the trading day. Demand uncertainty is driven by weather and marketplace-day footfall affecting all vendors simultaneously. Waste from spoilage provides a direct measure of costly supply mistakes. We develop a two-stage model identifying three inefficiency channels: business-stealing through prices, availability externalities through stockout spillovers, and coordination failure under correlated shocks. Our empirical strategy combines vendor-level panel data with randomized price experiments. Vendors are notified of treatment the evening before, so the experiment activates both the inventory response at the wholesale market and the price and sales response during the trading day. Conditional price subsidies for randomly selected vendors thereby identify demand substitution, strategic conduct, and uncertainty decomposition across both stages. We test whether vendors optimize individually and whether markets achieve efficient aggregation, classifying behaviour into scenarios based on individual versus market efficiency. The analysis will establish whether inefficiency arises from individual mistakes (learning errors, biases) or market failures (strategic competition, coordination)---a distinction critical for policy, since if markets exhibit individual efficiency with market inefficiency, improving individual forecasting cannot address strategic externalities.
External Link(s)

Registration Citation

Citation
Dhingra, Swati and Lachi Singh. 2026. "Weathering the Waste: Inventory Choice, Market Aggregation, and Food Loss Among Urban Street Vendors." AEA RCT Registry. June 29. https://doi.org/10.1257/rct.18750-1.0
Experimental Details

Interventions

Intervention(s)
Intervention Start Date
2026-07-18
Intervention End Date
2027-01-15

Primary Outcomes

Primary Outcomes (end points)
Incidences of stock outs, produce inventory, sales, produce waste
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
We study inventory decisions and market outcomes among informal fresh produce street vendors in Patna, India. Vendors are randomised to a treatment arm or a control arm, with treated vendors receiving a temporary price incentive on designated treatment days. The same vendors are observed across treatment and control days throughout the study. Primary outcomes are daily inventory procurement quantity, sales quantity, and end-of-day waste. Secondary outcomes include retail prices and stockout incidence.
Experimental Design Details
Not available
Randomization Method
Randomization done in office by a computer
Randomization Unit
First level of randomisation: treatment day assignment at the market level, re-randomised weekly.
Second level of randomisation: treatment arm assignment at the product-vendor level within each market, permanent throughout the study.
Was the treatment clustered?
Yes

Experiment Characteristics

Sample size: planned number of clusters
30 (experiment markets)
Sample size: planned number of observations
48,420 (807 product-vendors × 60 active survey days)
Sample size (or number of clusters) by treatment arms
~404 treatment product-vendors, ~403 control product-vendors
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
0.05 SD for the primary outcome (own-price effect on inventory procurement quantity), based on simulated power calculations with 30 markets, 60 observation days per product-vendor, and 18 treatment days per product-vendor. Power exceeds 0.99 at this MDE across all sensitivity panels.
IRB

Institutional Review Boards (IRBs)

IRB Name
LSE Research Ethics Review Board
IRB Approval Date
2026-06-05
IRB Approval Number
646914