Promoting High-Impact Entrepreneurship: An Evaluation of a Mexican Government Matching Grant Scheme

Last registered on December 21, 2016


Trial Information

General Information

Promoting High-Impact Entrepreneurship: An Evaluation of a Mexican Government Matching Grant Scheme
Initial registration date
December 21, 2016

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
December 21, 2016, 11:23 AM EST

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



Primary Investigator


Other Primary Investigator(s)

PI Affiliation
World Bank
PI Affiliation
World Bank
PI Affiliation
Columbia University

Additional Trial Information

In development
Start date
End date
Secondary IDs
This project aims to provide an evaluation of a Mexican government program to provide financial support to Mexican small and medium-sized enterprises (SMEs) through a matching grant scheme. The targeted firms are start-ups and scale-up firms that offer an innovative product, service or business model with high potential to compete globally and generate high impact in economic, social and environmental outcomes. We will work with the Mexican government to investigate the overall impact of the program on firms’ performance, as well as to explore how to more effectively pick high growth firms.
External Link(s)

Registration Citation

Atkin, David et al. 2016. "Promoting High-Impact Entrepreneurship: An Evaluation of a Mexican Government Matching Grant Scheme ." AEA RCT Registry. December 21.
Former Citation
Atkin, David et al. 2016. "Promoting High-Impact Entrepreneurship: An Evaluation of a Mexican Government Matching Grant Scheme ." AEA RCT Registry. December 21.
Experimental Details


Intervention Start Date
Intervention End Date

Primary Outcomes

Primary Outcomes (end points)
Number of employees
Number of Skilled Employees
Value of exports, share of sales, and countries
Labor and capital productivity
Patents and innovation indicators
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
Firms applications will be scored by an evaluation panel. Firms receiving scores above a certain threshold will be randomly chosen to receive the grant. We will then compare the performance of the firms randomly provided with a matching grant with those who were not. The characteristics of the reviewers who are able to pick better performing firms (judged in terms of growth) will also be evaluated.
Experimental Design Details
Evaluators are not explicitly asked to score firms based on the expected treatment effect, but instead on the firm's growth potential and the particular project's strength. Hence, small treatment effects may be evidence of an absence of credit constraints rather than a failure to pick good applications. Thus, we plan to evaluate not only the impact of the grant program, but also how the applications are evaluated.

In particular, we seek to understand whether these types of matching grant program are better evaluated by bureaucrats (who may be unbiased, but may also have little expertise in the relevant industry) or by experts (who may be biased towards friends or against competitors but will have expertise in the relevant industry). To create variation in who reviews each application, we will have a traditional panel comprised of evaluation specialist hired by the government, as well as a new "VC" panel, comprised of individuals with private sector business experience. When a panel reviews a firm, two reviewers are used. All firms will be reviewed by the traditional panel, and around half of the applications will be reviewed by the VC panel (so some firms will have 4 reviewers). To increase variation, VC reviewers will be randomized to create three groups. The groups will each contain different combinations of reviewers based on whether the reviewer has expertise in the industry that the applicant firms is in or not, and whether the reviewer is based in Mexico or abroad. Combined with other reviewer characteristics, this will generate variation in the proximity of reviewers to applicants. This variation, combined with firm outcomes, will allow us to discover whether more proximate reviewers score firms more accurately (because of their expertise), or just higher (because of their bias).
Randomization Method
Randomization done in office by a computer
Randomization Unit
Firms will be randomized into treatment and control within score stratas. Evaluators will also be randomized across applications.
Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters
1 Matching Grants Program
Sample size: planned number of observations
Sample size (or number of clusters) by treatment arms
150-200 treated firms, 150-200 non treated (firms with high scores but not treated), 100-200 additional controls (firms with low scores not treated)
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)

Institutional Review Boards (IRBs)

IRB Name
MIT Committee On Use of Humans as Experimental Subjects
IRB Approval Date
IRB Approval Number


Post Trial Information

Study Withdrawal

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Is the intervention completed?
Data Collection Complete
Data Publication

Data Publication

Is public data available?

Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials