Evaluating the Effects of Targeted Information on Public Procurement Competition: Pre-Analysis Plan

Last registered on January 17, 2025

Pre-Trial

Trial Information

General Information

Title
Evaluating the Effects of Targeted Information on Public Procurement Competition: Pre-Analysis Plan
RCT ID
AEARCTR-0014612
Initial registration date
January 17, 2025

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 17, 2025, 7:51 AM EST

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
Department of Economics, Faculty of Economics, Business and Tourism, University of Split

Other Primary Investigator(s)

PI Affiliation
Department of Economics, University Bocconi

Additional Trial Information

Status
In development
Start date
2025-01-18
End date
2025-06-30
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
This study examines whether providing targeted information to firms can increase competition in public procurement. The information we will provide is publicly available; however, it is scattered across the web and requires a more in-depth search to access. By curating and presenting this information in a targeted manner, we aim to enhance its relevance and accessibility for firms. This approach seeks to mitigate information asymmetries that may deter participation, particularly among smaller firms and firms further away from the public buyer. By enhancing firms' awareness of available procurement opportunities and offering them tailored insights on potential bidders and their bids, we investigate whether this approach will increase the number of bidders and improve the competitiveness of offers.
External Link(s)

Registration Citation

Citation
Decarolis, Francesco and Stjepan Srhoj. 2025. "Evaluating the Effects of Targeted Information on Public Procurement Competition: Pre-Analysis Plan." AEA RCT Registry. January 17. https://doi.org/10.1257/rct.14612-1.0
Sponsors & Partners

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Experimental Details

Interventions

Intervention(s)
Our intervention is composed of an e-mail providing details on a public tender matched to characteristics of the firm. Details in PAP.
Intervention Start Date
2025-01-18
Intervention End Date
2025-03-31

Primary Outcomes

Primary Outcomes (end points)
Tender-Level Outcomes:
1) Number of bidders on the public tender subject to the intervention.
2) Share calculated as final tender contracted price divided by estimated contract price.
Primary Outcomes (explanation)
1) Total number of bids received in a particular public tender;
2) Final winning price in a particular public tender divided by the ex-ante estimated contract price in a particular public tender.

Secondary Outcomes

Secondary Outcomes (end points)
Firm-Level Outcomes:
1) A dummy taking the value of 1 if the firm bid on the public tender subject to the intervention, and 0 otherwise.
2) A dummy taking the value of 1 if the firm bid and won the public tender subject to the intervention, and 0 otherwise.
Secondary Outcomes (explanation)
Researchers will collect data on the identification of bidders as well as winning firms in the public tender subject to intervention.

1) This information will be used to quantify whether and which treated and control firms bid in the particular public tender.
2) This information will be used to quantify whether and which treated and control firms won the particular public tender.

Experimental Design

Experimental Design
We will randomize the intervention at two levels: tender and firm-level.
Experimental Design Details
Not available
Randomization Method
Randomization done in office by a computer.
Randomization Unit
We will randomize the intervention at two levels: tender and firm-level.

First, at week-level we will randomize at the level of active tenders, we will conduct an equal split with computer generated random selection of tenders subject to intervention, and others that serve as control.

Second, within those treated tenders, we will randomly allocate firms with the expertise to participate in upcoming public tenders, determining which of these firms will receive a) information about the active tender, and b) a detailed report about the active tender. Within the treated tenders, firms will be randomly assigned to three groups: i) treatment arm 1 (information about the active tender), ii) treatment arm 2 (a detailed report about the active tender), and iii) a control group.


This approach allows us to capture nuanced variations in competition and bidding behavior across different tenders, ensuring that the intervention is relevant to the specific context of each procurement opportunity. By selecting certain tenders to receive the treatment while others serve as a control, we can effectively evaluate the overall impact of the intervention on competition at the public tender level. The second level of randomization is implemented within the treated tenders, where firms with the expertise to participate in upcoming public tenders are randomly allocated to receive targeted information about those tenders. This individual-level randomization enables us to analyze changes in firm behavior, such as participation rates and bidding strategies, while providing insights into how access to information influences decision-making among various firms, particularly smaller firm and firms further away from the public buyer. By incorporating both tender and firm-level randomization, our study will yield comprehensive findings on the effectiveness of the intervention and its implications for enhancing competition in public procurement.
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
800 tenders
Sample size: planned number of observations
3999 firms
Sample size (or number of clusters) by treatment arms
1333
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Tender-level number of competitors: mean competition: 1.650, Power: 90%, Total sample: 798, Effect: 0.05, Mean difference: 0.083, Standard deviation: 0.4, Cohen's d: 0.206, Alpha: 0.05. Firm-level probability of winning: Proportion in control group: 0.168, Power: 90%, Total sample: 3924, Effect: 0.05, Proportion in treated group: 0.218, Alpha: 0.05.
Supporting Documents and Materials

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IRB

Institutional Review Boards (IRBs)

IRB Name
Ethics committee, Faculty of Economics, Business and Tourism, University of Split
IRB Approval Date
2024-10-23
IRB Approval Number
KLASA: 004-01/24-01/03; URBROJ: 2181-196-02-05-24-05
Analysis Plan

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