1. Estimating the Causal Effect of Access to Public Credit on Productivity: the case of Brazil Eduardo P. Ribeiro (IE – UFRJ, Brazil) João A. De Negri (IPEA, Brazil)

2. Goal Evaluate the impact of access to BNDES (Federal Development Bank) on manufacturing TFP growth.

3. Motivation Aggregate TFP, 1992-2006, from Pessoa, Barbosa-Filho and Veloso (2008)

4. Motivation

5. Motivation (cont). Bond, Soderbom and Wu (2007) indicate that about 40% of Brazilian Firms are credit constrainted. In 2004, BNDES was responsible for about R$95 million in credits (US$1,00/R$2,00), or about 20% of all credit demand in the economy, and 5% of GDP (BCB, 2005). BNDES charges below market interest rates on its loans (e.g., average non-earmarked market rate on loans in 2006: 2.2%p.m., BNDES rates: from 1 to 1.5%p.m.)

6. Theoretical Framework While lower credit costs may boost investment, impact on productivity not clear a priori (Bustos, 2005, Ottaviano and Souza, 2008): With heterogeneous fixed and variable costs of innovations associated with investment, lower cost of funds may either (i) induce adoption of higher fixed cost more productive technology; or (ii) expand use of lower fixed cost less productive technology.

7. Identification BNDES requires significant collateral and has above market client credit risk ratings. Firms with higher TFP should have more revenues and capital (growth effect), that are used for credit screening. Yet theoretically, mark-ups – relevant for credit scoring – do not depend on TFP (Katayama, Lu, Tybout, 2006).

8. Two more identification rules: – BNDES interest rate variation across regions and firm sizes. – Proxy for informal market activity or tax delinquencies that forbids credit application (employment under-reporting when comparing RAIS –administrative – and PIA –statistical firm records).

9. Data TFP estimates: revenue and input use (labor investment, energy and materials from PIA (Manufacturing Annual Survey), 1996-2005; – Capital stock and capital expenditures estimated using perpetual inventory method, imputed cost of capital and depreciation, rental and leasing expenditures. – labor quantitites and expenditures, expenditures on labor, energy and materials, as well as depreciation and investment.

10. Data BNDES credit use (and proportion of investment expenditure financed by self, private and public sources) on machinery and innovation implementation from PINTEC (Innovation and Technology Survey), 2000, 2003,2005. Additional data: RAIS (Labor Administrative Forms): worker skill intensity, firm age.

11. Productivity measurement Cobb-Douglas function with coefficients set to input expenditures shares. Sector specific output and materials deflators; fixed investment and labor costs deflated using specific deflators. TFP it = y it – (  l l it +  k k it +  m m it +  e e it ) where  j are cost shares.

12. Descriptive Stats.

14. Preliminary results (1). OLS with robust s.e. using region, sector (2 digit) and year dummies; (2). Fixed Effects using year dummies; (3). TFP yearly growth. Specification as (1); (4). TFP yearly growth. Specification as (2); (5). TFP yearly growth. Specification as (3); (6). TFP yearly growth. Specification as (4); Note: a) using cumulative growth from t+1,…,T does not change results qualitatively; b) using proportion of investment financed by BNDES does not change results qualitatively.

15. Preliminary results

16. Preliminary conclusions Access to BNDES funds does not seem to be related with higher productivity.

17. Alternative Data set: Enterprise Surveys Advantages: more detailed financial data; not restricted to innovative firms. Disadvantages: no time series variation in financial data (but capital expenditures). Robustness analysis.

18. Alternative data source: Enterprise Surveys, Brazil, 2000-2003

19. Descriptive Stats – Enterprise Surveys 2000-2003  TFP 03  TFP 03 w 00  w 03 TFP 00  TFP 03  w 00 Total0.4250.2530.184-0.012 59%43%-3% no BNDES0.3940.2550.155-0.017 65%39%-4% BNDES0.031-0.0020.0290.004 -8%94%14%

20. Alternative Data set: Enterprise Surveys Econometric results do not change compared to PIA/PINTEC: negative TFP levels under homogeneity hypothesis and non-significant results for growth and instrumental variables (weak instruments).