Why Do Firms in Low-Income Countries Grow Slowly? An Investigation of Demand-Side Mechanisms

Last registered on September 30, 2021
View Trial History

Pre-Trial

Trial Information

General Information

Title
Why Do Firms in Low-Income Countries Grow Slowly? An Investigation of Demand-Side Mechanisms
RCT ID
AEARCTR-0008278
Initial registration date
September 27, 2021

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
September 30, 2021, 11:19 PM EDT

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

Locations

Country
Uganda
Region
Kampala

Primary Investigator

Name
Anna Vitali
Affiliation
University College London
Contact Primary Investigator

Other Primary Investigator(s)

Additional Trial Information

Status
On going
Start date
2021-04-25
End date
2022-05-31
Keywords
Firms & Productivity
Additional Keywords
JEL code(s)
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
Why do firms in low-income countries grow slowly? My research will provide new evidence on demand-side constraints, that is the challenges that firms face in building a customer base. Specifically, I will study how asymmetric information on product quality limits the ability of high-quality firms to attract customers. Accessing new customers may be especially difficult in developing countries due to high search costs that limit quality observability ex-ante (search frictions) and the lack of institutions that can enforce quality standards ex-post (contracting frictions). In this study, I will explore the role of these two frictions in limiting firm access to demand. To do that, I will combine data from a matched firm-customer survey with lab-in-the-field experiments to measure quality dispersion and asymmetric information in a number of small manufacturing sectors in Kampala, Uganda. I will then use this data to estimate a structural model of search with unknown quality and perform counterfactual analysis to quantify the relative importance of search and contracting frictions on firm and employment growth, entry/exit dynamic, and the distribution of quality. The structural approach of this study allows examining the mechanisms through which policies aimed at reducing asymmetric information on product quality may affect market outcomes in a general equilibrium framework. This can be informative of the type of interventions that would be most effective at stimulating firm expansion and the generation of employment in low-income economies.
External Link(s)

Registration Citation

Citation
Vitali, Anna. 2021. "Why Do Firms in Low-Income Countries Grow Slowly? An Investigation of Demand-Side Mechanisms." AEA RCT Registry. September 30. https://doi.org/10.1257/rct.8278-1.0
Sponsors & Partners

There is information in this trial unavailable to the public. Use the button below to request access.

Request Information
Experimental Details

Interventions

Intervention(s)
As part of this study, I will conduct a mystery shoppers exercise where I will randomize the characteristics of the customers. Specifically, I will instruct shoppers to use scripts that differ in the stated purpose of the purchase: 50% of the mystery shoppers will say that they are buying a product for private consumption, while 50% will state that they are sampling potential suppliers for their businesses. The type of script that will be recited to firms will be randomized. This will ensure that any difference in the price and the quality of the goods produced by firms receiving the two scripts can be attributed to differences in the script itself. The purpose of the exercise is to study whether firms alter their behaviour as a function of the net present value of a relationship.
Intervention Start Date
2021-09-01
Intervention End Date
2021-09-30

Primary Outcomes

Primary Outcomes (end points)
Product price, quality score (including quality of the product and customer care), time taken for production, timely delivery
Primary Outcomes (explanation)
Product quality will be assessed by an independent expert tailor. The identity of the firm will be hidden to the expert. The product assessed will be a dress (with the exception of firms that do not produce dresses, in which case shoppers will be instructed to buy the most typical product sold by the business). Quality will be rated on a scale from 0 to 100 according to the following criteria: product difficulty, accuracy of darts, collar, sleeves, skirt, zip, seam, hem, measurements, finishing and packing. Customer care will instead be based on a subjective evaluation of the mystery shoppers based on the following criteria: cleanliness and tidiness of business premises, and friendliness of business owner and employee.

Secondary Outcomes

Secondary Outcomes (end points)
Quality observability and learning
Secondary Outcomes (explanation)
Mystery shoppers will be asked to rate the product quality (i) at the moment when the order is placed, (ii) when the finished product is picked up. The ratings will be on a scale of 0 to 10. We will compare these two ratings to evaluate whether customers update their assessment when they observe the finished product. We will also compare these ratings to the quality score given by the expert tailor to study the extent to which quality is observed by customers. Finally, we will analyse whether shoppers' evaluations become more precise as they place more orders to understand whether learning occurs with experience.

Experimental Design

Experimental Design
The sample for this study comprises of 600 firms in the garment sector operating in Kampala, Uganda. I will employ mystery (i.e. anonymous) shoppers to purchase an identical products from each of these firms, which will then be evaluated by an expert in the sector to obtain accurate measures of quality. Mystery shoppers will be required to follow a precise script for the purchase. I will however produce two different versions of the script. Specifically, the scripts will vary in the stated purpose of the purchase: 50% of the mystery shoppers will say they are buying a product for private consumption ("Final Customer" script), while 50% will state that they are sampling potential suppliers for their businesses ("Business Customer" script). The type of script that will be recited will be randomized at the firm level.
Experimental Design Details
Firms will be sampled from an initial census of all garment firms in 14 parishes across Kampala. Firms in the census will be stratified by type of parish (central vs. periphery) and type of location within the parish (clustered vs. unclustered) and a total of 600 firms will be randomly selected across strata. The randomization of firms to treatment will be done within strata, so 50% of firms in each stratum will be assigned to the "Final Customer" script and 50% to the "Business Customer" script.
Randomization Method
Randomization done in office by a computer
Randomization Unit
Firm
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
600 firms
Sample size: planned number of observations
600 firms
Sample size (or number of clusters) by treatment arms
300 firms will be assigned to the "Final Customer" script and 300 to the "Business Customer" script
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
University College London Research Ethics Committee
IRB Approval Date
2021-04-04
IRB Approval Number
13391/001
IRB Name
Mildmay Uganda Research Ethics Committee
IRB Approval Date
2020-03-23
IRB Approval Number
0402-2020
IRB Name
Uganda National Council for Science and Technology
IRB Approval Date
2021-04-29
IRB Approval Number
SS711ES
Analysis Plan

Post-Trial

Post Trial Information

Study Withdrawal

There is information in this trial unavailable to the public. Use the button below to request access.

Request Information

Intervention

Is the intervention completed?
No
Data Collection Complete
Data Publication

Data Publication

Is public data available?
No

Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials