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Formal versus Informal Finance: Evidence from China

Formal versus Informal Finance: Evidence from China. Meghana Ayyagari Asli Demirgüç-Kunt Vojislav Maksimovic. The Financial system and growth:. Finance and growth literature : Developed financial system  growth

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Formal versus Informal Finance: Evidence from China

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  1. Formal versus Informal Finance: Evidence from China Meghana Ayyagari Asli Demirgüç-Kunt Vojislav Maksimovic

  2. The Financial system and growth: • Finance and growth literature: • Developed financial system  growth • King and Levine (1993), Demirguc-Kunt and Maksimovic (1998), Rajan and Zingales (1998) • The literature recognizes that the financial system is diverse: • Informal components: Angel financing and informal loans • Can the informal system substitute for the formal system?

  3. Is China a counterexample? • Allen, Qian and Qian (2005): • “China is an important counter example to the findings in the law, institutions, finance and growth literature” • In the absence of an efficient formal financial sector: “there exist effective alternative financing channels and corporate governance mechanisms such as those based on reputation and relationships to support the growth of the Private Sector” • “Although our results are based on China, similar ‘‘substitutes’’ based on reputation and relationships may be behind the success of other economies as well including developed economies”. • “Our [private sector] evidence is mainly based on a survey of 17 entrepreneurs and executives in Zhejiang and Jiangsu provinces, two of the most developed regions in China

  4. In this paper: • Does the informal sector act as a substitute to the formal financial system and finance the fastest growing firms or does the informal sector primarily serve the lower end of the market? • To answer this question, we proceed in steps: • Are Chinese firms’ financing patterns different compared to other countries? • How do formal and informal financing patterns vary across different types of firms in different cities and regions? • How are bank finance and financing from informal sources associated with • firm sales growth • productivity growth • profit reinvestment. .

  5. The context • Formal organizational structure, the legal system and performance • Demirguc-Kunt, Love and Maksimovic (2006), Beck, Demirguc-Kunt and Maksimovic (2005) • Chinese financial system • Cull and Xu (2005), Cull, Xu and Zhu (2007), Dollar, Wang, Xu and Shi (2004), Farrell et al (2006), Fan, Morck, Xu and Yeung (2006) • Financial system and development • Guiso, Sapienza, and Zingales (2002), Bertrand, Schoar, and Thesmar (2004)

  6. Data • Investment Climate Survey, a major firm level survey conducted in China in 2003 and led by the World Bank. The survey has information on financing choices for approximately 2400 firms across 18 different cities. • While most of the qualitative questions pertain only to the year 2002, a short panel from 1999 to 2002 is available for the quantitative questions. • Strength of the survey is in broad coverage of small and medium sized firms • The firms are randomly surveyed from both manufacturing and services industries with a restriction on minimum firm size where firm size is defined by number of employees. • The minimum number of employees was set at 20 for manufacturing firms, and at 15 employees for services firms.

  7. Cities in China covered by ICA Survey Northeast Haerbin B- Changchun A Benxi B- Dalian A- Central Zhengzhou A Wuhan B+ Nanchang B+ Changsha B+ Coastal Hangzhou A+ Wenzhou A+ Shenzhen A+ Jiangmen A+ Ranking of Cities by their Investment Climate (Source: Dollar et al. (2004)) Northwest Lanzhou B- Xian B+ Southwest Chongqing A Guiyang B Kunming B Nanning B 1.Haerbin 2.Changchun Beijing 3.Benxi 4.Dalian 17.Lanzhou 9.Zhengzhou 18.Xian 13.Chongqing 10.Wuhan 5.Hangzhou 11.Nanchang 14.Guiyang 12.Changsha 6.Wenzhou 15.Kunming 16.Nanning 7.Shenzhen 8.Jiangmen

  8. Additional Data • As of 2006, there were 67 country surveys covering over 40000 firms. Since the core survey instrument is the same across all countries, we have comparable information on financing sources across the different countries.

  9. Methodology • Correlations --- what is the role of bank financing on growth, reinvestment, productivity? • Selection model: controls for the endogeneity of access to bank loans • Matching model: controls for matches based on observables using propensity scores.

  10. How different is China?China vs. Other Developing Countries

  11. How different is China?China vs. RoW

  12. Individual Financing Patterns Within China

  13. Bank Financing and Firm Performance • Firm Performance =  + 1Bank Dummy+ 2 Firm Size dummies + 3 Age dummies + 4 Corporations + 5Collectives + 6 State Ownership + 7Competition Dummies + 8City Dummies +  where • Firm Performance: • Sales Growth [2001-2002, 1999-2002] • Productivity Growth [2001-2002, 1999-2002] • Profit Reinvestment Rate [2001-2002] • Bank Dummy: • 1 if the firm states that is has a loan from a bank or financial institution • 0 if the firm states that it has no bank loan and no overdraft facility or line of credit • OLS Regressions with clustered standard errors.

  14. Bank Financing and Firm PerformancePartial Correlations

  15. Selection Model • Two step selection model (Heckman, 1978) that allows prediction of which firms obtain bank finance. • Selection Equation: Bank Dummy = 1 if • 0 + 1 Collateral + 2Size dummies +3 Age dummies +4Corporations + 5Collectives + 6State Ownership + 7Competition Dummies + 8City Dummies + z >0, • where z~(0,2) is proprietary information observed by the bank. • Collateral is identifying variable • Second Stage Equation: • Firm Performance = 1 + 1BankDummy+ 2Size dummies+ 3Age dummies + 4Corporations + 5Collectives + 6State Ownership + 7Competition Dummies + 8City Dummies +  + ε • where  is Inverse Mills Ratio (estimate of selection bias)

  16. Reasons why loan application was rejected

  17. Selection Model and Identifying Restriction • We use Collateral as our identifying variable. • 1 if firm reported ‘yes’ to the question “Did the financing require collateral” • 0 if firm reported ‘no’ to the question “Did the financing require collateral” OR • 0 If firm reported it did not apply for a loan because collateral requirements were too stringent OR • 0 if firm reported its application for a loan was rejected • How contingent are our results on the way Collateral is defined? • We perform robustness checks using Propensity Score Matching: • Do not need to use collateral as an identifying variable • Also use fixed assets in place of collateral variable.

  18. Bank Financing and Firm Performance – Selection Model

  19. Selection Model Robustness • Expanded Selection Model • Variables to proxy for Government Help variables, Bank Corruption, Property Rights Protection, Loan from Group or Holding Company, Loan Guarantee Program, Located in Export Processing Zone, CEO Education Level, Politically Connected CEO • Broader measure of access to bank finance • Access Dummy, takes the value 1 if the firm had access to a bank loan in any year prior, from 1990-2001, and 0 otherwise.

  20. Financing Proportions of New Investments and Working Capital :Bank Financing versus Informal Financing • Bank Financing: • 1 if the firm states that it has a loan and reports that bank finances at least 50% of new investments or working capital. • 0 if the firm states that it has no loan or said it had no overdraft facility or line of credit and the bank financing of new investments and working capital was equal to 0% • Self Financing1 • 1 if the sum of Informal financing and Other financing of either new investments or working capital is greater than 50%. • 0 if the sum of informal and other financing of new investments and working capital is equal to 0 %. • Self Financing2 • broadens the definition of self financing and takes the value 1 if the sum of Informal, Family, and Other financing of new investments or working capital is greater than 50%

  21. Financing Proportions of New Investments and Working Capital :Bank Financing versus Informal Financing

  22. Robustness • Median Regressions • Matching model (in progress): • Use propensity score to find matching firms for each firm with a bank loan. • With and without collateral. Alternative measures of tangible assets Radius Matching, Common Support, Bootstrap Standard Errors

  23. Collateral

  24. Overview • Chinese firms in our sample do not look different in their use of bank loans. • Firms with bank loans grow faster and reinvest more. • Firms with bank loans do not report lower productivity. • Who gets loans: • Large firms • Relatively few competitors. • Have government help • Part of group • Located in export processing zones • Collateral is important • Particularly in less developed provinces. • Land and buildings • Bank corruption is reported, but implications for efficiency and allocation are not evident

  25. Conclusion • Little evidence that the formal system is being bypassed or that the informal system is a good substitute for fast growing firms. • Caveat: The unit of analysis is firm, not loan value.

  26. Why Chinese firms do not apply for bank loans?

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