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Building High-Growth Firms Through Training the Owner vs Through Linking the Firm to Business Service Markets

Last registered on March 14, 2018

Pre-Trial

Trial Information

General Information

Title
Building High-Growth Firms Through Training the Owner vs Through Linking the Firm to Business Service Markets
RCT ID
AEARCTR-0002769
Initial registration date
March 14, 2018

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
March 14, 2018, 5:52 PM EDT

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

Locations

Primary Investigator

Affiliation
World Bank

Other Primary Investigator(s)

PI Affiliation
Stanford University

Additional Trial Information

Status
On going
Start date
2016-02-09
End date
2020-06-30
Secondary IDs
Abstract
Many small firms lack the finance and marketing skills needed for firm growth. The standard approach in many government programs has been to attempt to train the owner to develop these skills, through business training sessions or personalized consulting services. However, an alternative is to link firms to these skills in the market through insourcing workers with these skills, or outsourcing these tasks to professionals specializing in these services. We test which approach works best to grow small firms through a randomized experiment. Firms with 2-15 workers each will be randomized into five groups: a control group, a group given business training for the owner, a group given consulting services, a group linked to HR specialists who will find a worker to insource these skills, and a group linked to companies with professionals specializing in business services to outsource these skills. Impacts on business practices, firm sales and employment growth will then be measured to determine the most effective way of building skills in SMEs.
External Link(s)

Registration Citation

Citation
Anderson, Stephen J. and David McKenzie. 2018. "Building High-Growth Firms Through Training the Owner vs Through Linking the Firm to Business Service Markets ." AEA RCT Registry. March 14. https://doi.org/10.1257/rct.2769-1.0
Former Citation
Anderson, Stephen J. and David McKenzie. 2018. "Building High-Growth Firms Through Training the Owner vs Through Linking the Firm to Business Service Markets ." AEA RCT Registry. March 14. https://www.socialscienceregistry.org/trials/2769/history/26658
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Experimental Details

Interventions

Intervention(s)
Firms will be randomly assigned to one of four interventions: business training; business consulting; insourcing of an accounting or marketing worker; or outsourcing to an accounting or marketing firm.
Intervention Start Date
2016-12-15
Intervention End Date
2018-12-31

Primary Outcomes

Primary Outcomes (end points)
In the short-term, we are interested in which program has the most impact on business practices
In the longer-term, key outcomes are business survival, profitability, sales, and employment
Primary Outcomes (explanation)
The pre-analysis plan will describe how these outcomes are defined and constructed

Secondary Outcomes

Secondary Outcomes (end points)
Short-term: time-use of the business owner
Longer-term: use of market for business services, access to and use of finance, subjective well-being, innovation
Secondary Outcomes (explanation)
The pre-analysis plan will describe how these outcomes are defined and constructed

Experimental Design

Experimental Design
Firms will be randomly allocated in enrolment batches. Within each batch, firms are randomly allocated to one of the four treatments, or to a control group, in equal proportions.
Experimental Design Details
To be included in the study, firms undertake the following steps:
Step One: apply online through the BIG platform in response to advertising campaign. McKenzie (2017) notes that requiring online application already screens on firms which are more sophisticated and likely to be plausible candidates for high-growth. Moreover, by applying for the program firms indicate their interest in developing their skills.
Step Two: pass an initial screening based on having complete data on the application, operating in one of the 5 GEM sectors, being 18 and older, and having more than one and fewer than 100 workers.
Step Three: attend an induction workshop in Lagos or Abuja, and answer baseline survey at this workshop. This screens further on motivation and effort.
Step Four: have a score of between 5 and 8 out of 10 for business practices based on this screen, have between 2 and 15 workers, and not be already outsourcing or insourcing both marketing and finance functions. This generates a group of potential high-growth firms who are determined to grow, and have made it past the barrier of hiring other paid workers apart from the owner.

In the 2016 launch, more than 2,500 firms attended the induction workshops in Lagos and Abuja, of whom 943 firms passed these screening criteria and become the first part of the experimental sample. The total planned sample size is 2,000 firms, although this is dependent on numbers inducted by the government program.

Firms are then randomized by induction group (enrolment batch) - for example, the batch of firms that attended the Lagos induction workshop on a particular date. Firms are randomly assigned in equal proportions to the four treatment groups and to a control group.

A second sample outside of Lagos and Abuja are randomly assigned to consulting, training, and control only.
Randomization Method
Randomization done in office by computer, stratified by enrolment batch
Randomization Unit
Firm
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
The number of clusters is the same as the number of units. It is planned to be 2,000 firms, but is currently 943 and the total sample will depend on the numbers inducted in 2018.
Sample size: planned number of observations
2,000 firms planned, currently 943
Sample size (or number of clusters) by treatment arms
The sample size is equally allocated across the five groups (subject to rounding).
The target is 400 in each group, but currently we have:
Training 190 firms; consulting 188 firms; insourcing 187 firms; outsourcing 191 firms; control 187 firms
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
The sample size is determined by the project budget and geographic distribution of applicants (firms applying from other parts of Nigeria will not be offered the insourcing or outsourcing treatments, but will still be randomized to control, grants, training, or consulting, and to date we have 730 control, 434 training, and 434 consulting outside of Abuja and Lagos – we will use this other sample to measure impacts of these first two treatments in those regions). Our power calculations are then designed to determine the minimum detectable effect possible with this sample. We are in a better position for making these calculations than most studies because the 2016 application window has closed and gives us data on the initial 943 experimental firms. Moreover, based on the first batches, we have over 90% take-up for the consulting, insourcing, and outsourcing treatments (training take-up data not yet available). We therefore assume 90% take-up in these calculations. We report the minimum detectable TOT effect assuming this take-up rate. Table 2: Minimum Detectable Effect (80% power, 5% significance level) Business Practices Score Employment Log Profits Unit Level Firm Firm Firm Variable Mean 6.31 4.22 13.05 Variable SD 0.75 2.59 1.35 MDE (in SD) 0.22 0.18 0.19 MDE (as % of reference mean) 2.6% 4.3% 25% Business practices: calculation is made using only a single round of follow-up data. MDE for the ITT is then 0.15, so for the TOT is 1.1*0.15 = 0.165. This is 0.22 s.d., or 2.6% increase in the mean. Since the score is on a 10-point scale, this is equivalent to a 0.02 improvement in the proportion of practices implemented. This is less than half the size found in business training experiments cited in the literature review. Employment: power calculations assume Ancova estimation, controlling for baseline value of employment. Autocorrelation is assumed to be 0.5. MDE is then 0.43 workers , so a TOT of 1.1*0.43 = 0.47 workers. This is 0.18 S.d., or a 4.3% increase on the control mean. For employment we believe the increase in the number of workers is the most useful metric. 0.47 workers increase in employment will occur if half the firms hiring an insourced worker keep this worker on, even if they do not grow enough to hire more workers. McKenzie (2017) finds high-growth enterprises achieve employment gains of 4-5 workers per firm from winning the business plan competition, so we are only trying to detect increases one-tenth of that size. Log monthly sales: power calculations assume Ancova estimation, controlling for baseline value of sales. Autocorrelation is assumed to be 0.5. MDE for the ITT is 0.23, so TOT is 0.25 log points, or a 25% increase in the control mean. We aim to reduce this further through three steps: i) controlling for baseline covariates like sector, business practices, and employment size that can soak up some of the variation in size and reduce heterogeneity; ii) budget allowing, use multiple measurements of monthly sales within a given follow-up period as in McKenzie (2012); and iii) reduce measurement error and hence noise by utilizing a cross-checking survey technology.
IRB

Institutional Review Boards (IRBs)

IRB Name
IRB Approval Date
IRB Approval Number
Analysis Plan

Analysis Plan Documents

Post-Trial

Post Trial Information

Study Withdrawal

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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