Information Frictions in Government-Firm Relationships

Last registered on November 30, 2021

Pre-Trial

Trial Information

General Information

Title
Information Frictions in Government-Firm Relationships
RCT ID
AEARCTR-0005400
Initial registration date
February 05, 2020
Last updated
November 30, 2021, 7:57 PM EST

Locations

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Primary Investigator

Affiliation

Other Primary Investigator(s)

Additional Trial Information

Status
On going
Start date
2019-04-01
End date
2022-08-31
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
Public procurement of goods and services represents the primary area of government investment, accounting for a large share of the GDP in low-income countries. As a result, its potential as a driver of private sector development is massive. Yet, frictions in the functioning of procurement markets can lead to low competition, potentially resulting in an inefficient allocation of resources. Our project aims to estimate various information-related interventions that have been conducted in collaboration with the Uganda Public Procurement and Disposal of Public Assets Authority (PPDA), i.e. the national public procurement supervisory agency. Here, we test whether an intervention aiming to increase transparency of public procurement opportunities affects firm-level outcomes.
External Link(s)

Registration Citation

Citation
Colonnelli, Emanuele. 2021. "Information Frictions in Government-Firm Relationships." AEA RCT Registry. November 30. https://doi.org/10.1257/rct.5400-1.1
Experimental Details

Interventions

Intervention(s)
We conduct two interventions aimed at reducing information-related frictions on both sides of the procurement market. First, on the firm-side, we study whether making information about tenders available in a timely and efficient manner affects firm-level outcomes. Second, on the government side, our treatment provides public entities with access to a large pool of data about potential providers.
Intervention Start Date
2019-09-01
Intervention End Date
2021-12-31

Primary Outcomes

Primary Outcomes (end points)
See attached pdf. Our main firm-level outcomes are the bidding and winning behavior in public procurement, as well as measure of firm activity. Our main PDE-level outcomes are measures of competition (overall and new firms winning and bidding, HHI, share top X firms) and the quality/efficiency of executed contracts (delays, cost over-runs, audit outcomes, our own/expert quality checks, value for money a la Bandiera et al (2009)).
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
We use strata for firm location (Kampala vs other), sector (works, supply, services), and size (above and below sample median). Out of 3,049 firms, 765 are allocated to T1 (tender information), 761 to T2 (tender information plus nudge), and 1,523 to the control group. We use strata for public entity type (central, local) and for size based on number of contracts assigned (large, small). Out of 260 public entities, 131 are allocated to treatment (access to database of firms) and 129 to control.
Experimental Design Details
Not available
Randomization Method
The randomization is done in office using Stata. We use strata for firm location (Kampala vs other), sector (works, supply, services), and size (above and below sample median). We use strata for public entity type (central, local) and for size based on number of contracts assigned (large, small).
Randomization Unit
The unit is the "firm" for the firm-level intervention and the "public entity" for the public entity intervention.
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
3,049 firms, 260 public entities.
Sample size: planned number of observations
3,049 firms, 260 public entities.
Sample size (or number of clusters) by treatment arms
Out of 3,049 firms, 765 are allocated to T1 (tender information), 761 to T2 (tender information plus nudge), and 1,523 to the control group. Out of 260 public entities, 131 are allocated to treatment (access to database of firms) and 129 to control.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB

Institutional Review Boards (IRBs)

IRB Name
The University of Chicago Social and Behavioral Sciences Institutional Review Board
IRB Approval Date
2018-11-28
IRB Approval Number
IRB18-1475
Analysis Plan

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