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Credit Access in India. Abhijit V. Banerjee. How well is capital allocated?. Value added (in US$ millions) per establishment in 1990. 10.00. 9.00. 8.00. 7.00. 6.00. 5.00. 4.00. 3.00. 2.00. 1.00. 0.00. Textiles. Iron and steel. Transport. Food products. Machinery. Machinery,.

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credit access in india

Credit Access in India

Abhijit V. Banerjee

prima facie evidence

Value added (in US$ millions) per establishment in 1990

10.00

9.00

8.00

7.00

6.00

5.00

4.00

3.00

2.00

1.00

0.00

Textiles

Iron and steel

Transport

Food products

Machinery

Machinery,

Industrial

Other

Other non-

All industries

equipment

except electric

electric

chemicals

chemicals

metallic

mineral

products

Top nine ISIC 3 digit industries by value added for India in 1990

India

Comparator countries

Prima Facie Evidence

Figure 1. Average Firm Size in India and Comparator Countries in 1990

slide4
More…
  • TFPR dispersion within 4 digit industries (from Hsieh and Klenow)

U.S.ChinaIndia

90th/10th 1.9 5.6 5.7

75th/25th 1.3 2.5 2.4

a natural experiment on credit access priority sector lending in india
A natural experiment on credit access: Priority Sector Lending in India
  • Based on Banerjee-Duflo (2004)
  • Banks need to lend 40% of their portfolio to the priority sector, including SSI.
  • Changes in the priority sector rules:
    • January 1998: inclusion in the SSI sector of firms with investment in plant and machinery between 0.65 and 3 crores rupees.
    • Early 2000: firms with ipm between 3 crores rupees and 1 crore rupees taken away from the priority sector.
results
Results
  • We firms level data from 1 very well-regarded public bank.
  • We estimates the effect on credit, sales, and profits, using firms that were always in the priority sector as controls.
  • The firms that were included in the priority sector and then excluded grew much faster in all 3 measures when included, and fell behind on all 3 when excluded.
implications
Implications
  • 1 percent increase in credit generates 1 percent increase in sales and 3 percent increase in profits
  • Even after taking default rates (NPA) into account, the implied marginal product of capital is close to 100%! Average rates of NPA do not explain under-lending.
  • Evidence of systemic failure: Neither private lenders nor public banks are supplying these largish firms with the credit they need.
direct evidence from interest rates
Direct evidence from interest rates
  • There is a large body evidence showing that many smaller firms are also extremely short of credit.
  • In Banerjee (2002) I review evidence showing that small firms often pay interest rates of over 50% of which at most 5% is explained by default.
  • This tells us that their marginal product must be above 50% whereas the cost of capital is of the order of 5-6% at most.
  • On the other hand, from the ICOR for India (4.5), the average marginal product in India cannot be more than 22%.
  • So a lot of firms must be earning a lot less than 22%.
evidence from within industry allocation
Evidence from within industry allocation
  • Evidence from the knitted garment industry in Tirupur.
  • The firms that are associated with a cash-rich community start out almost three times larger than those started by other people.
  • These firms very soon fall behind in terms of output, but continue to have significantly more fixed capital.
lending rules for public sector banks
Lending rules for public sector banks
  • Maximum Permissible Bank finance: Since the Nayak Committee, banks can set their own rule (turnover based, or based on working capital gap)
  • For example in the bank we study, MPBF is the maximum of turnover based limit and the limit based on the working capital gap
  • Comments:
    • Rules set for limited growth.
    • Profitability does not enter in the official rule.
    • Inventories are not a very good collateral in practice
however the problem goes beyond the rules
However the problem goes beyond the rules
  • Banerjee and Duflo (2001) look at the actual lending decisions of a bank, and compare it with the actual limit.
  • Main results:
    • The lending limit changes very infrequently (in 64% of the case, it does not change) despite growth
    • Increases are not very responsive to firms’ characteristics and performance.
    • Lending in smaller than MPBF in 68% of the cases.
  • Systematic deviation from the rule in the direction of inertia.
understanding why banks do not lend
Understanding why banks do not lend?
  • Lack of positive incentives
  • Fear of lending
  • Lending to the government and the easy life
  • The risk of (marginal) default
fear of lending
Fear of Lending
  • Employees of public bank are subject to anti-corruption legislation: widespread concerns about the legal proceedings.
  • No incentive to lend more: it is easier to do nothing.
  • Using monthly data on lending combined with public data on CVC investigation, we examine whether there is a decrease in lending in a bank following CVC activity.
results20
Results
  • Following vigilance activity in a particular bank, total lending by the bank drops by 3-5%, compared to other banks and stay low for several years.
  • This understates the overall impact since there might be some anticipatory reaction as well (we have only data on the date at which the CVC advice was given).
  • This could imply a sizeable reduction in the credit supply in the economy.
what is going on
What is going on?
  • The attraction of easy life
    • The combination of high interest rates on government borrowing and a boom in consumer finance as the economy transitions to credit financing of durables reduces the pressure to lend to industry.
  • Test: Are banks in slow growing states more responsive to variation in government interest rates then banks in fast growing states ?
  • Data: yearly data on C/D ratio for 45 banks
  • Results: in high growth environment, banks are less elastic to the spread in their lending decisions
the risk of default
The Risk of Default
  • Are firms more likely to default because they are in the priority sector?
  • According to the data from our bank, 2.5% of loans in the priority sector become NPA every year
  • For firms included in 1998, the rates of default was and remained lower till 2002 (but climbs sharply in 2001, after they get excluded from the priority sector).
is public ownership the problem26
Is public ownership the problem?
  • Cole (2004) exploits a natural experiment the nationalization of banks in 1980 to answer this question.
  • The 1980 nationalization took place according to a strict policy rule: all private banks whose deposits were above a certain cutoff were nationalized.
  • He compares banks that were just above the 1980 cutoff to those that were just below the 1980 cutoff, while controlling for bank size in 1980.
  • The idea behind this comparison is that the relationship between size and behavior should not change dramatically around the cutoff, unless nationalization itself causes changes in behavior.
not much of a demonstrable gap between public and private banks
Not much of a demonstrable gap between public and private banks
  • Overall public lending grew at the same rate as private lending in the 80s; lagged behind in 90s
  • No differences in lending patterns today.
  • Historically public banks favored agriculture/rural borrowers, while neglecting trade/transportation. No differences in lending to small-scale industry.
what is happening right now some speculation
What is happening right now: some speculation
  • Over the last couple of years, there may well be a shift.
  • Lots of innovation going on in the financial sector.
    • Big banks like ICICI Bank and SBI are becoming increasingly aggressive
    • Private finance is growing fast
    • The stock market is booming.
    • Boom in retained earnings in the corporate sectors
    • Large corporates are borrowing heavily on the world markets
  • My prediction is that we will look back on this period and conclude that the recent growth acceleration had to do with a sharp inflow of capital into undercapitalized firms.