Impact Evaluation Step by

Step:

Evaluating the Impact of

Formality on Micro

Enterprises Performance

in Lima, Peru

Miguel Jaramillo

Lorena Alcázar

February 18 – 20, 2015

Istanbul, Turkey

Motivation

• For decades, policy makers have argued in favor of promoting the

transition of firms from the informal sector to the formal sector.

• Many efforts have been made for the purpose of reducing informality:

initially increasing the price of operating informally and more recently

decreasing administrative barriers.

• However, informality continues flourishing.

• For SMEs, municipal bureaucracy is one of the main obstacles in the

formalization process (In Peru, 60% of the time).

• In 2004, IFC and the Municipality of Lima carried out an administrative

simplification process that was effective in increasing the number of

firms’ licenses demanded and granted (260% growth in 6 months)

The research question and its policy

relevance

The research question

• Previous information point to the success of reforms in terms of

facilitating access by firms to an operating license…

• But, the key question is: Does having an operating license

improve firm performance?

Objective

• To empirically measure the impact that operating with municipal

license has on different outcome variables related to the performance

of micro firms in downtown Lima.

Methodological challenges

Methodological challenges, 1

• What most studies do is to compare firms between 0 and p1 with firms

between p2 and 1.

Methodological challenges, 2

• Entrepreneurs have different characteristics which lead them to their

decisions of operating formally or informally.

• To isolate the effect of having a license, the study needs comparable

entrepreneurs/firms.

• Even controlling for firms observable characteristics, it is very likely

that there will be unobservable variables (motivation,

entrepreneurship) that may affect the formalization decision and the

firm performance variables.

Methodological choices: methods and

data

Methodological solution: Encouragement approach

• In order to evaluate the impact of being formal we need to go beyond

just comparing formal and informal firms.

• We need identical firms only that some will be formal and others

informal.

• A random encouragement to formalize is used: encouragement

generates the exogenous variation in otherwise similar firms needed

to identify the impact of having a license.

Implementing the method

Implementation, 1

• Step 1: produce a roster of 604 informal firms (operating without a

license).

• Step 2: Collect data to generate a baseline.

• Step 3: Select randomly a sub-sample (300 firms out of the 600) to

receive an incentive to obtain the operating license.

– The incentive was a voucher with a monetary value to be effective only for

the firm to pay for a portion of the operating license.

Implementation, 2

• Step 4: implement the encouragement

• Step 5: follow the firms for 2-3 years.

– A survey was applied at four different moments in time over a period of

two and a half years .

• Encouragement proved very useful beyond solving endogeneity

problem, showing lack of demand for licenses.

Data Collection Process

Identify Firms without License.

Collect Baseline Data.

Draw a Random Sample to be Encouraged.

Second Round Data Collection.

Third Round Data Collection.

Fourth Round Data Collection.

6 months

1 year

1 year

Analysis and results

Impact estimation

• To measure the effect of having a license over a set of firm

performance variables, we used 2 different estimators:

1. A difference in difference estimator.

2. An instrumental variables estimator (IV), using as instrument the

incentive offer to the random sub-sample of firms, i.e.

encouragement.

• The Diff-in-Diff estimator eliminates selection bias by isolating time-

invariant factors while the IV through the isolation of the license effect

from unobservable factors.

• IV: encouragement associated to license but not to observable or

unobservable factors.

• Since each method relies on different assumptions, using both

methods allows us to check for robustness of the results.

The variables

• The study considered the impact of having a license over a set

of output and input variables:

– Outputs: revenues, sales, profits, profits per workers,

employment.

– Inputs: number of employees, access to credit, investment

in infrastructure and machinery, access to new clients

• Main control variables: age of the respondent, gender,

entrepreneurial experience, time experience in business,

education, age of the business, size of business.

• Treatment variable: having a license (both considering

encouraged and non encouraged firms)

Results

Results

• Our estimates show that operating with municipal license has no

statistically significant effect on firms’ performance indicators.

• Neither final outcome variables (outputs) such as revenues, sales,

profits, profits per workers, nor intermediate outcome variables, such

as number of employees, access to credit, investment in infrastructure

and machinery (inputs) are statistically affected by the fact the firms

operate with license.

• For two variables (profits per worker and number of workers) we

obtain significant coefficients, but these are not robust to alternative

methods.

Conclusions

• Having a license does not have any impact on firm performance

indicators.

• Importance of encouragement approach both to estimate impact

and to understand issues (unexpected results).

• Demand for formality may be overestimated based on firms

responses. It seems that microfirms, as those in Downtown Lima,

do not perceive much advantage in operating with a license.

• Findings are relevant for policy decisions: formalization programs

are not enough if their focus is just to provide licenses. They must

have a broader scope.

Communicating results

Final step: communicating results

• Key messages and audiences.

• Engaging different audiences.

THANKS!!!

#TTIX2015