Impact Evaluation Step by Step Evaluating the Impact of Formality_GRADE
Impact Evaluation Step by
Evaluating the Impact of
Formality on Micro
in Lima, Peru
February 18 – 20, 2015
• 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
• 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?
• 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, 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
• 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.
• 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
• 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.
• Step 1: produce a roster of 604 informal firms (operating without a
• 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.
• 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
Collect Baseline Data.
Draw a Random Sample
to be Encouraged.
Second Round Data
Third Round Data
Fourth Round Data
• 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.
• 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
• Since each method relies on different assumptions, using both
methods allows us to check for robustness of the results.
• The study considered the impact of having a license over a set
of output and input variables:
– Outputs: revenues, sales, profits, profits per workers,
– 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)
• 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
• Having a license does not have any impact on firm performance
• 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.