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Coronavirus (COVID-19) Small Business Government Relief Takeup Project
Last registered on July 29, 2020

Pre-Trial

Trial Information
General Information
Title
Coronavirus (COVID-19) Small Business Government Relief Takeup Project
RCT ID
AEARCTR-0005626
Initial registration date
March 31, 2020
Last updated
July 29, 2020 2:02 AM EDT
Location(s)

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Primary Investigator
Affiliation
Princeton University
Other Primary Investigator(s)
PI Affiliation
Oxford University
PI Affiliation
Yale University
Additional Trial Information
Status
On going
Start date
2020-03-27
End date
2020-12-31
Secondary IDs
Abstract
Many small businesses have already been deeply affected by the COVID-19 crisis, leading them to lay off employees, temporarily close shop, or go out of business completely. In response, governments have passed specific provisions to help support small businesses as part of large aid packages. However, we document in a baseline survey that many small businesses may not understand who is eligible for aid, what aid is available or how to apply. This project evaluates the roles of information frictions on small businesses’ utilization of newly available government assistance. To begin, we survey small businesses in the United States and Latin America about how they have been affected by the COVID-19 crisis. Next in the first round of the pilot outreach program, we randomly assign small businesses from eight Latin American countries to informational interventions with different levels of intensity. Businesses will then be followed up to see if they successfully applied for aid, and how the aid affected expectations, layoffs and probability of going out of business. Using the experimental design, we will study the role of information frictions on differences in applying for aid by firm size, and how that aid affects business survival. The more effective measures will then be scaled up if any are found to be cost-effective.
Registration Citation
Citation
Humphries, John Eric, Christopher Neilson and Gabriel Ulyssea. 2020. "Coronavirus (COVID-19) Small Business Government Relief Takeup Project." AEA RCT Registry. July 29. https://doi.org/10.1257/rct.5626-2.0.
Sponsors & Partners

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Experimental Details
Interventions
Intervention(s)
We survey small businesses in Latin America about how they have been affected by the COVID-19 crisis. Next, we randomly assign small businesses to different informational interventions with different levels of intensity. Businesses will then be followed up to see if they successfully applied for aid, and how the aid affected owner's expectations, layoffs and probability of going out of business. Using the experimental design, we will study the role of information frictions on differences in applying for aid by firm size, and how that aid affects business survival. The more effective measures will then be scaled up in a second round if any are found to be cost-effective.
Intervention Start Date
2020-04-22
Intervention End Date
2020-07-17
Primary Outcomes
Primary Outcomes (end points)
1. Firm survival, 2. Number of layoffs
Primary Outcomes (explanation)
1. Firm survival: whether the firm is still open (or temporarily closed but plans to reopen). It will be measured using a follow up survey, and eventually administrative data.
2. Number of workers laid off: this is the number of full-time equivalent workers (full-time + 0.5*part-time) laid off since January (i.e. pre-covid). It will be determined using a follow up survey, and eventually administrative data. Notes on how we count jobs lost in case of business closure:
If the firm had 0 employees in January and it closes, then this counts as 1 job lost (the owner’s)
If the firm had N full-time equivalent employees in January, and it closes, then that is N+1 jobs lost
Secondary Outcomes
Secondary Outcomes (end points)
1. Awareness about government relief policies, Take up of government aid (2. Whether the firm applied for aid, 3. Whether the firm got aid), 4. Expectations of the owner about recovery
Secondary Outcomes (explanation)
2. Whether the firm applied for any of the relief policies available in their country: This will be asked directly in the follow up survey.
3. Whether the firm got aid from such relief policies: This will be asked directly in the follow up survey, and we also expect to determine it by looking at administrative government records of firms that received aid, when they become available.
4. Expectations of the owner about recovery: This will be measured using three questions of the follow up survey
a) Do you think your business will recover in the next two years?
b) How many months do you think it will take for your business to fully recover?, and
c) What is the probability (1-100) that your business will go bankrupt/permanently close in the next 6 months?
Experimental Design
Experimental Design
Small businesses are recruited through social media to take our baseline survey conducted in Qualtrics. Those who share contact information with us are included in the experiment sample. Firms are randomly assigned to the "low-intensity" information intervention group, or to the "high-intensity" information intervention group. In Mexico, there is also a "medium-intensity" information intervention group. Randomization is stratified by country and date of response.
Experimental Design Details
Not available
Randomization Method
Randomization was done by a computer. It was stratified by country and date of response. For firms in Mexico, we further stratified by State, as there was substantial variation in policies across states.
Randomization Unit
The firm
Was the treatment clustered?
No
Experiment Characteristics
Sample size: planned number of clusters
To assess the impact of T2 vs. T1 the sample size is 10,895 firms (Sample 1). To assess the impact of T3 vs. T1 the sample size is 2,804 firms (Sample 2). Finally, with the 3,334 firms from Mexico (Sample 3) we can test both T4 vs. T1, and T4 vs. T2. As per our intervention description, a group of Mexican firms belong to both Sample 1 and Sample 3.

Overall, there are 15,367 firms in our experiment sample. More details can be found in the Pre Analysis Plan
Sample size: planned number of observations
To assess the impact of T2 vs. T1 the sample size is 10,895 firms (Sample 1). To assess the impact of T3 vs. T1 the sample size is 2,804 firms (Sample 2). Finally, with the 3,334 firms from Mexico (Sample 3) we can test both T4 vs. T1, and T4 vs. T2. As per our intervention description, a group of Mexican firms belong to both Sample 1 and Sample 3. Overall, there are 15,367 firms in our experiment sample. More details can be found in the Pre Analysis Plan
Sample size (or number of clusters) by treatment arms
Email (T1): 8,921 firms
Email + Phone session + Chatbot (T2): 3,252 firms
Email + Phone session (T3): 1,526 firms
Email + Chatbot (T4, only in Mexico): 1,668 firms
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
The Pre Analysis Plan provides a more comprehensive account of the power calculations we have performed. We list here the Minimum Detectable Effects for T1 vs T2. Consider the following to interpret the MDE calculations: For all calculations, our alpha was set at the standard 0.05 level, power was set at 0.8. and we considered critical values for a one-sided test. For each outcome, we show (where possible -and relevant) the baseline mean of the control group and the Minimum Detectable Effect of our intervention. Some outcomes (Business is open, Business applied for help, Business got help) do not have a measure in the world without COVID, so we calculate MDEs with respect to 3 possible scenarios for the control mean. For the outcome “jobs lost from January to follow up”, we also make an assumption about the jobs that will be lost in the control group. We know the average number of jobs lost in the control group from January to the moment of the baseline. The approximation we use is 1.5 times this number. In general, we expect the take up of the treatment to be 60% in the treatment group (0.6 compliance) and 0% in the control group (0% spillover). We adjust our MDEs taking this into account (multiplying by 1/0.6 = 1.66) MDE calculations T1 vs T2 in 5 countries, primary outcomes: (1) Business is open, MDE relative to 3 possible values for control mean if control mean = 0.98, MDE = 0.0111 if control mean = 0.95, MDE = 0.0179 if control mean = 0.90, MDE = 0.0251 (2) Number of jobs lost from baseline to follow up control mean (assumed) = 3.5, MDE = -0.0864 (3) Proportion of owners aware of programs control mean = 0.21, MDE = 0.0357 (4) Proportion that applied for help, MDE relative to 2 possible values for control mean if control mean = 0.1, MDE = 0.0267 if control mean = 0.15, MDE = 0.0315 (5) Proportion that got help, MDE relative to 2 possible values for control mean if control mean = 0.03, MDE = 0.0156 if control mean = 0.06, MDE = 0.0213
IRB
INSTITUTIONAL REVIEW BOARDS (IRBs)
IRB Name
Small Business Emergency Survey
IRB Approval Date
2020-04-15
IRB Approval Number
12750
Analysis Plan

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