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Impact Evaluation Step by Step Evaluating the Impact of Formality_GRADE

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Impact Evaluation Step by Step Evaluating the Impact of Formality_GRADE

  1. 1. 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
  2. 2. 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)
  3. 3. The research question and its policy relevance
  4. 4. 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?
  5. 5. 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.
  6. 6. Methodological challenges
  7. 7. Methodological challenges, 1 • What most studies do is to compare firms between 0 and p1 with firms between p2 and 1.
  8. 8. 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.
  9. 9. Methodological choices: methods and data
  10. 10. 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.
  11. 11. Implementing the method
  12. 12. 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.
  13. 13. 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.
  14. 14. 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
  15. 15. Analysis and results
  16. 16. 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.
  17. 17. 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)
  18. 18. Results
  19. 19. 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.
  20. 20. 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.
  21. 21. Communicating results
  22. 22. Final step: communicating results • Key messages and audiences. • Engaging different audiences.
  23. 23. THANKS!!! #TTIX2015

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