[PPT] - Financial markets in developing countries (rough notes, use only as PowerPoint Presentation

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Financial markets in developing countries (rough notes, use only as guidance; more details provided in lecture) The role of the financial system

up by themselves)

prices, etc.

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greatest returns)

made liquid through the stock market, etc.)

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Credit markets

financial markets are efficient (perfect information, perfect enforcement) then resources flow to highest returns (highest skills)

with, not their talents

reach its potential

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countries?

be: — unable to repay (information needed in advance to prevent this; this is costly) — unwilling to repay (enforcement needed ex-post to prevent this; this is costly) — evidence from India: in 1997, 3.2 outstanding debt cases; 40% for more than 8 years — also, limited liability — in today’s world there are legal limits on punishment for reneging on contracts (not true in the past or in black markets)

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Lenders anticipate these issues, so they:

riskiness/type)

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FACTS

India; 28-62% in urban; in the US — 6-14% 1980-2000 — cannot be explained by default alone (explains at most 23% of the interest rate level) — cannot be explained by monopoly power alone — why kill the demand so much? also, public banks and competition from informal sector present

30% of all loans)

60% without arbitrage)

possible, no matter what the interest rate — “credit rationing”

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rate (not consistent with standard supply and demand theory under perfect markets)

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— the case of Debt Recovery Tribunals in India (Visaria, 2007) — sped up resolution of civil cases about unpaid loans; — reduced loan delinquency by 6-11 percentage points — interest rates fell by 1-2 percentage points

— study 129 countries over 25 years — finds that lenders’ legal rights (ability to enforce repayment; sell the collateral) is positively correlated with the private debt to GDP ratio

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— across countries the size of domestic credit market positively correlated with GDP per capita — however, causality can run the other way around — richer countries may have larger market for credit — or, both can be caused by third factors (institutions, good government policies) — however, they also find a strong positive evidence on financial development on growth of industries that are more credit-dependent.

levels of financial development and subsequent growth (controlling for many country and policy characteristics)

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THEORY Three major problems causing financial market imperfections

successful investment, hence repayment

riskiness) affect probability of repayment

enforcement problem (1.) or asymmetric information between lenders and borrowers (2. and 3.)

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Limited Enforcement Example

caught (loan enforced) is π < 1 — limited enforcement

borrowed must return $(1 + r), e.g. $1.20)

A < I

q − (1 + r)(I − A) > q − πF (1)

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should be larger than the expected income if default (escape with the money) — the right hand side

A > I − πF 1 + r (2)

not lend to someone they know will default; think of F as jail time, etc. not something that the lender gets).

inefficiency! — some poor people will not obtain loans, even if their business projects are profitable (say q > (1 + r)I)

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fine or the probability of repayment — the more people will be able to

interest rate, the higher the wealth threshold.

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Moral Hazard Example

low (failure), yL = 0

for simplicity prob(yH) = e and prob(yL) = 1 − e.

Case I: self-financed entrepreneur max

e(2) − ρ(1) − 1 2e2

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take the derivative and set to zero to find the optimal effort level: e∗ = 2

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Case II: borrowing when effort is observable (no incentive/moral hazard problems)

effort.

nothing otherwise)

e(1 − r) − 1

way to maximize joint profits: Π = ΠL + ΠB = 2e − ρ − 1

exactly the same expression as that of the self-financed entrepreneur.

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Case III: moral hazard due to unobservable effort

when output is high he must pay the interest;

in effort (a ‘moral hazard’ problem occurs)

max

e(yH) − e(1 + r)I − (1 − e)(0) − 1 2e2 = 2e − e(1 + r) − 1 2e2

2 − (1 + r) − e = 0

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default rates than in the first best; lower expected output).

borrower lose something in the low output case) will alleviate the moral hazard problem by increasing incentives to work hard

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Adverse Selection Example

probability of success of their business projects

— ‘risky’ borrowers have prob. of success 1/2 in which case they get return of 4 — ‘safe’ borrowers have prob. of success 1 in which case they get return

— note, the expected return is the same (2) in both cases but the risky types have uncertain (variable return, 4 or 0) vs. the sure return from the safe types.

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information’, since borrowers know their type)

both types (higher for the risky ones)

must be charged since unable to tell who is who

depending how high it is — if the interest rate set by the lender is low, both types will apply for a loan — however, setting a high interest rate will only attract the risky types (since they only pay back when their project succeeds) — note, the risky type expected income is (1/2)(4)+(1/2)(0)−(1/2)(1+ r)L = 2 − (1/2)(1 + r) so they will borrow up to an interest rate of

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r = 3 (this is the maximum r at which they get at least zero expected income) — for safe types, their expected income is 2 − (1 + r)L = 1 − r so they’ll

set determines the pool of borrowers a lender faces

in a conventional market) may result in facing increasingly more risky borrowers and actually decrease profits.

for loans (credit rationing again) — but lenders don’t raise the price (the interest rate) as this may reduce their profits due to the adverse selection effect.

very small deductibles likely to attract very risky clients

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r but high collateral and one with high r but low collateral — borrowers will self-select into them (safe will pick low r, risky will pick high r) — can show this can restore efficiency (obtained in the benchmark with no asymmetric information)

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APPLICATIONS/POLICY

innovative credit mechanisms in developing countries such as microcredit ROSCAs (rotating credit and savings associations)

formed in LDCs to facilitate buying expensive households asset (e.g. TV, washer) or business assets (e.g. motorbike) — group of people make monthly contributions and one (often randomly) chosen to take the pot each month — on average, everyone but the last person to win the pot buys the asset sooner — efficiency improvement — issues: enforcement, how to ensure people keep contributing after winning; group size/composition matters

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Microfinance institutions (MFI)

people who are otherwise outside the formal financial sector (rationed

lending — a group of borrowers responsible for a loan to one of its members — meaning that if a group member does not pay — all others are responsible for their loan; can be cut off from future credit — typically, no collateral required — very high repayment rates reported

several reasons, related to the theory discussion above.

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(the bank effectively delegates these costs to the borrowers)

and would form groups with people like them

pressure to ensure repayment

information, monitoring and enforcement serves as ‘social collateral’ that the lender can exploit to provide credit to poor people who would

as commercial banks

— dynamic incentives — at first small loans are given and new, larger

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loans provided only if previous loans are paid (same as what credit card companies here do) — flexible collateral — accept items that are valuable to the borrower (e.g. wedding ring; working animals) even if not so valuable to the lender — targeting women borrowers — higher repayment rates achieved. Why? possible explanations are that women are more risk-averse (psychology) and that they have fewer outside options (lower incentives to default, ‘nowhere to go’)

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MFI and subsidies

microentrepreneurs) or filling in a profitable niche in the financial market?

by the poor and are costly to participate in (act as screening mechanism to find out who really needs the money