1. 14/04/11 Relaxing Credit Constraints: The Impact of Public Loans on the Performance of Brazilian Firms IDEAS International Assembly 2011 * Corresponding Author fls@bndes.gov.br Filipe Lage de Sousa* and Gianmarco Ottaviano

2. Motivation Emerging markets are enlarging their participation in world GDP and trade, especially BRICS. Some of them have financial institutions to provide long term loans. BRICS are not exception to this rule (all have at least one) Brazilian Government provide those long term loans through its Brazilian Development Bank (BNDES). BNDES mandatory goal is to burst Brazilian economy without neglecting social aspects. Therefore, it is important to evaluate whether their financial support has been able to improve firms’ competitiveness, which will be measured by productivity.

3. Why productivity? “Productivity isn’t everything, but in the long run it is almost everything...... Compared with the problem of slow productivity growth, all other long-term economic concerns - foreign competition, the industrial base, lagging technology, deteriorating infrastructure and so on - are minor issues” (Krugman, 1992)

4. Asumption: In order to implement one project, firms decide on whether using: 1.Old (Low) Technology – lower fixed cost, but higher marginal cost 2.New (High) Technology – higher fixed cost, but lower marginal cost According to our model, credit constraints might affect those two fixed costs asymmetrically. 1.If it is more towards new technology, productivity increases. 2.If it is towards old technology, productivity reduces. 3.If it affects them symmetrically, productivity remains constant Theoretical Foundation

5. BNDES finances different types of firms, from micro to multinationals. In 2009, its disbursements reached US$ 78 billion (representing 13,3% of aggregate investment). We investigate two types of loans: 1.FINEM (direct – over US$ 5 millions); 2.Automatic BNDES (indirect – below this threshold); Both cover: creation of new plants; enlargement of existing ones; restructuring and modernization of processes; and innovation and technological development Why BNDES?

6. From 1995 to 2007, 9,828 firms were granted one of these loans; These two loans represents around 40% of BNDES resources. Some figures Using different data sources, some firms are discarded: Too small (no information in main data source where we measured productivity); If two firms merge, the loan will be registered to the new company, which didn’t exist before when there is the information; There is a time-lag for a firm to take part in the survey.

7. Empirical Strategy 1.Choosing treated group (1995 to 2007) a. Previous Period to find a reasonable counterfactual group b. Post Period to evaluate impact 2.Finding counterfactual groups by PSM or by other method. 3.Verify whether treated firms perform differently from non-treated firms. 4.Estimating by Naive Model (OLS) and Sophisticated Model (Dif- in-Dif) governments’ impact.

8. Treated Firms How many Treated Firms received first loan in 1998 How often?Indirect LoansDirect and Indirect Just Once6975 More than Once4366 Total112141 Year Selected = 1998.

9. Treated x Non Treated Non Treated FirmsTreated Firms Variables AllSur&Inv1 st 20071 st 98Ind 1 st 98Just 98Ind Just 98 Labour Productivity26,626,827,035,529,731,827,4 TFP (All 1996 = 100)99,3101,889,197,7100,7104,7102,5 Capital Stock31,619,634,984,429,053,924,1 % Qualified Workers5,8%6,8%5,7%9,2%8,1%9,2%8,4% Number of Employees175196255620332468285 Market Share0,09%0,11%0,12%0,33%0,11%0,31%0,09% Profitability5,9%6,7%7,9%5,7%5,9%6,4%6,1% Fin Costs / Total Costs3,9%3,6%3,2%4,7%4,5%5,0%4,9% Fin Costs / Net Revenue3,9%3,0%2,2%2,8% 3,1% Investments1,170,861,245,451,584,791,13 Revenue Growth22,1%20,6%16,9%17,5%13,7%13,8%11,9% Labour Productivity Growth30,3%26,0%14,3%31,7%27,6%34,6%33,8% Employment Growth0,1%4,3%1,8%8,8%10,3%6,2%6,3% High and Med-High (OCDE)22%26%18%32% 35%32% Number of Firms21.3806.3441281411127569

10. Treated (1st 98) x Non-Treated

11. Refined Control Group: Propensity Score Matching (PSM) 1st 98Ind 1st 98Just 98Ind Just 98 Paired118996561 Non-Paired2313108 After pairing, we tested whether average from treated and non-treated firms are similar and even productivity (which was not in the PSM) showed similar means.

12. Treated (1st 98) x Control Group

13. Main Results from Econometrics Control Groups or Counterfactual Groups a)Firms which have survived and invested (6 thousand firms) b)Firms first granted in 2007 c)Paired Firms using PSM Regardless which control group is considered, results are the same. 1.Naive Model (OLS) Labour Productivity - Positive Total Factor Productivity - Negative 2.Sophisticated Model (Difference-in-Differences) Non Significant Results

14. Main Conclusions BNDES Loans might be able to relax credit constraints However, it seems that it is not impacting productivity Reasons: 1.Projects selected might not be the most prominent 2.Loans may be reducing implementation costs for both old and new technology projects symmetrically, therefore not impacting average firms’ productivity Increase number of manufacturing firms in Brazil from 20 thousand to more than 40 thousand during 1996 to 2006. Filipe Lage de Sousa fls@bndes.gov.br