Financial Development & Corporate Growth

1. Financial Development & Corporate Growth Jan Bena and Štěpán Jurajda LSE and CERGE-EI IN DIRECT INTERSECTORAL COMPARISONS LSE November, 2006

2. MOTIVATION • There is positive cross-country correlation between financial development and economic activity (Goldsmith, 1969; King & Levine, 1993). • Size of finance-growth effect? • Finance-growth effect on particular firm types? • But how can we disentangle two-way causality? • Supply → Firms need external finance to reap growth opportunities. • Demand ← Financial development reflects future growth opportunities. • Growth opportunities are unobservable. • No episodes of exogenous changes in financial development. • Identification relies on strong assumptions.

3. DEALING WITH REVERSE CAUSALITY: Literature • Cross-country studies • Initial period indicators of country financial development (King and Levine, 1993; Levine and Zervos, 1998) • Instrumental variables, mostly legal origin (La Porta et al., 1998; Levine et al., 2000) • Regional differences within a single country • Controls for unobservable country-level growth determinants (Jayarante and Strahan, 1996; Bertrand et al., 2004) • Experience of specific industries across countries • Quantify industry need of external finance (Rajan and Zingales, 1998; Beck et al., 2004; Guiso et al., 2004)

4. THE RAJAN-ZINGALES STRATEGY: Assumptions (A1) Industry growth opportunity shocks are global = the same need to expand production (A2) Industry technology is also constant across countries = the same $ of external finance to expand production by a unit →Cross-industry differences in the need for external finance are the same across countries. (A3) U.S. listed firms face a perfectly elastic supply of external finance. →Observed industry external finance dependence in the U.S. (US_EFD) serves as counterfactual for outside financing need in other countries.

5. THE RAJAN-ZINGALES STRATEGY: Implementation • Regress industry growth on • country and global industry fixed effects • interaction termUS_EFDINDUSTRY * Financial_DevelopmentCOUNTRY to ask whether industries more dependent on outside finance grow faster in financially more developed countries. • STRONG: Reverse causality endogeneity at country level. • WEAK: Constant industry differences in demand for external finance across countries such as U.S., Finland, Philippines, Zimbabwe, ... • Direct tests of assumptions are not available. • Similarity of technological content of industries across development levels threatened by empirical trade research (Schott, 2003).

6. AN ALTERNATIVE STRATEGY: Assumptions (A1) Industry growth opportunity shocks are global. (A4) Corporate growth in a given industry would be the same in absence of differences in country financial development. + Apply both assumptions in a more appropriate context: • EU-15 ‘single market’,1995-2003 (harmonized product market regulation) • Industry growth is verifiably highly synchronized • Comparable firms: Age, Size, Leverage, Tangibility, Quoted, Ownership, ... → Do two comparable EU-15 firms in the same industry but facing different financial system grow at different rates?

7. AN ALTERNATIVE STRATEGY: Cost and Benefits Benefits of (A4) • Avoid quantification of industry EFD • Obtain economically measurable estimates Costs of (A4) • Heterogeneity in financial development in EU-15 assumed orthogonal to other country-level determinants affecting growth. → Control for initial-period GDP to capture ‘convergence’ effects. • Use initial-period (predetermined) indicators of country financial development. What if markets are forward looking? → Control for country-level future growth opportunities

8. BASIC SPECIFICATION Gijkt = α + βFDi + γGDPi + δtj + Xk′ζ + εijkt

9. DATA Firm level:Amadeus‘TOP 250 thousand’ for EU-15 • Real value-added growth of manufacturing firms • Only public and private limited liability companies • Remove state-owned firms • Best firm-level EU data source available to date Country financial development indicators • World BankFinancial Structure and Economic Development Database • Total capitalization: Includes debt securities (Hartmann et al., 2006) • Control premium: Private benefits of control (Dyck & Zingales, 2004) Industry level: OECDSTAN • Industry growth rates used to identify synchronized industries.

10. CORPORATE DESCRIPTIVE STATISTICS: Firm-Year Data over 1995-2003

11. FINANCIAL DEVELOPMENT: The EU-15 over 1990-1994

12. FINANCIAL DEVELOPMENT AND CORPORATE GROWTH: Basic Estimates

13. FINANCIAL DEVELOPMENT AND CORPORATE GROWTH: Basic Estimates

14. FOCUS ON SYNCHRONIZED INDUSTRIES Our strategy is based on (A1) synchronization of industry growth shocks, so it will fail where industry growth is driven by local regulation. Hence, we identify synchronized industries usingANOVAsof industry growth with YEAR and COUNTRY factors. Synchronization corresponds to strong YEAR factors. • Differentiate Low-, Medium-, and High-synchronization industry groups. • Or use continuous synchronization measure.

15. DEVELOPMENT AND GROWTH: Industry Synchronization Groups

16. FIRM-TYPE INTERACTIONS Gijkt = α + β0FDi +β1xk⋅FDi + γGDPi + δtj + Xk′ζ + εijkt

17. AGE Interaction

18. SIZE Interaction

19. COLLATERALIZATION Interaction

20. TANGIBILITY Interaction

21. ROBUSTNESS CHECKS • Financial development measures misleading • if they reflect not only differences in available supply of finance, • but also demand for finance driven by future country growth opportunities. →Control for predicted future country growth: Take industry averages of EU-15 realized growth over 1995-2003, and weight them by initial-period country-level shares of each industry. • Robustness to removing UK and Greece • Median Regressions

22. Robustness to AGGREGATE GROWTH OPPORTUNITIES

23. Robustness to Removing UNITED KINGDOM and GREECE

24. CONCLUSIONS • We apply simple cross-country comparisons in an appropriate setting: • within EU-15, • to synchronized industries, • to many similar firms, both large and small. • As a result, we obtain • coefficients that translate to easy-to-interpret magnitudes, • differences in the finance-growth effect by firm types. • Findings: • Move from the least to the most developed financial system within the EU-15 boosts firm annual growth rate by2 to 3 percentage points. • Youngfirms have limited access to financial markets. • Ability to providecollateralhelps to get outside finance, especially if the firm is small or young. • We do not find asizeeffect interaction.