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économie du Développement Cours n°3

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économie du Développement Cours n°3 Powered By Docstoc
					Development Economics


     Credit and microfinance
   Discussion about features of credit
    markets in LDCs
       Formal and informal sources of credit
   Group lending
       Get around the informational constraints
What is credit?

   agreement for repayment at a
    specified date or dates

   repayment includes an interest rate

   purpose of loan is usually specified to
    the lender
Sources of demand for credit
1       Fixed Capital

2       Working Capital

3       Consumption Credit
    1     Need for cash because of shock (need for
          insurance)
    2     Consumption smoothing to cope with
          seasonality.
    3     Exceptional expenditures (wedding, funeral…)
Default

1.   involuntary default
        non-productive investment
               -issue of monitoring, fungibility
        risky investment
2.   voluntary or strategic default
        enforcement mechanisms (formal,
         informal)
 Where does credit come from (1)?

1.   Institutional or Formal Lenders
        rural development banks
        advantage of moving capital across
         space
        enforcement and informational issues
         (relative to informal credit)
        transactions costs higher
  An example: r=10%, 2 projects

  Initial  Return Final    Bank    Investor
  investmt        return

1 100,000   15%   115,000 10,000   5,000


2 100,000   20%   120,000 10,000   10,000
Same project 2, but project 1 risky

100,000 - 230,000 with prob 0.5
       - 0 with prob 0.5
 Expected return:
       Borrower
           (1) 0.5 (230,000-110,000)+0.5 x 0 = 60,000
           (2) 10,000
       Bank
           (1) 0.5 x 10,000 +0.5 x 0 = 5,000
           (2) 10,000
   Limited liability, discrimination against the
    poor
   Rational for use of collateral
Where does credit come from (2)?

   Informal lenders
       can take different forms of collateral (eg labor)
       often have better information than formal lenders
       relative importance
           India (1951) 7.2 percent of all borrowing from
            governments, banks and cooperatives
           India (1981) 61.2 percent formal, 24.3 percent from
            moneylenders (Bell, 1993)
           Thailand (1975) 90 percent of total rural credit informal
           Thailand (1993) 50 percent informal
           Nigeria (1989) 7.5 percent in villages from formal
            sector
Characteristics of rural credit
markets
   High interest rates
       Chambar region of Pakistan: 18-200%, average is 79%
        (formal sector = 12%)
   Rationing
   Little use of collateral
   Simultaneous existence of formal and informal
    credit.
   Segmentation
       Chambar region in Pakistan –Aleem (1993):
       10 out of 14 moneylenders lend 75% of their funds to old
        clients) ;
   Interlinkages
   Exclusivity
Information constraints

   Costly
   Asymmetrical
   Validity dependant on the stationarity of the
    environment
   Hence
       Moral Hazard (use of the loan, reimbursement
        effort)
       Adverse selection.
       Need for auditing in case of non repayment.
Understanding features of
informal credit market

   Imperfect information
       Benchmark: competitive equilibrium with perfect
        information
       Competitive equilibrium with imperfect
        information
       Interactions between external and internal
        lenders
           Assume no voluntary default
   Imperfect enforcement and long-term
    relationships
           The question of voluntary default
General case

   2 types of borrowers: 1 and 2
   Returns of the projects in case of success:
       R(1)<R(2)
   Success probability: (1)> (2)
   (1).R(1)=(2).R(2)=R
       Same expected returns, one safe borrower (1)
        and a riskier one (2)
   Reservation utility: W(1)=W(2)=W
                               borrower      lender

        Success
                    (t)       R(t)-i        i
        Failure
                    1- (t)    0             0


   For the borrower: U(i, t)=(t)[R(t)-i]
   For the lender: (i, t)= (t).i

   Two hypotheses:
       Limited liability
       No voluntary default
Competitive equilibrium with perfect
information:
   ρ is the opportunity cost of funds (return on the
    risk-free capital market)(R>ρ≥1)
   In equilibrium, i(t) is such that:
       U(i1(t), t)≥W
       Π(i1(t), t)≥ρ
       There is no i(t)≠ i1(t) s.t. Π(i1(t), t)≥ρ and that borrower of
        type t would prefer to i1(t)
   For each type t, there is an equilibrium with
    lending characterized by the solution to:
             Max (t )(R(t )  i )
                i

             s.t. i. (t )   and  (t )(R(t )  i )  W
If R    W , there will be positive lending
                   
t , i1 (t ) 
                  (t )
and t , U (i1 (t ), t )  R  
i1 (1)  i1 (2)


   Each agent can be identified
        Different interest rates
        Lower interest rate for the safe type


   Taking into account default probability can yield to
    high interest rates
Competitive equilibrium with imperfect
information = adverse selection

   The lender cannot distinguish the two types of risks but knows
    the proportion p1 of type 1 risks in the population. The interest
    rate is therefore unique and note that i:

        U (i,1)   (1)R(1)  i    (2)R(2)  i   U (i,2)
        (i,1)   (1).i   (2).i  (i,2)

   The participation constraint is
          (t )R(t )  i)  W

                                U (i, t )
   Obviously we have                      0
                                  i
   Hence we can define the highest interest rate at
    which borrowers are willing to borrow. Call it i*(1)
    for type 1 borrower. It is defined by equation:
              R   (1).i * (1)  W
                                 R-W
              hence i * (1) 
                                  (1)
   Define i*(2) in the same way.
   i*(1)<i*(2), so that safer borrowers drop out of the
    pools of borrowers first when the interest rate
    increases.
If i  i * (1), then E (i )  p(1) (1)i  [1  p(1)] (2)i.

If i * (1)  i  i * (2), type1 borrowersdrop out and lender income falls.
E (i )   (2).i

If i  i * (2), E (i )  0
Expected lender’s income as a
function of i
   The competitive equilibrium with adverse selection
    is then defined as an interest rate i2 such that

        E (i2 )  
        and there doesn't exist any i  i2 s.t. E (i )   and
        U(i,t)  U (i2 , t ) t and U (i, t )  W t
  If R-ρ>W, there will be lending in equilibrium.
 If   E(i * (1))  p1 (1)i * (1)  (1  p1 ) (2)i * (1)
Then, equilibrium interest rate will be i2   /  (2)
And only type 2 borrowers will want a credit.
  If   E(i * (1))
Then the interest rate will be given by

      i2   /p(1) (1)  [1  p(1)] (2)

Which is less than i*(1), and all potential borrowers
  will demand loans.
      Interactions between outside and local
      lenders

   Local lenders: well informed, high h.
   If R- h  W, then
        i3(1) = h /(1) and      i3(2) = h /(2)
        i3(1)  i*(1) et i3(2)  i*(2)

   Outside lenders are uninformed. Then cannot distinguish
    between type 1 and type 2, but low l. Offer a unique i.
   If i  i*(1) : type 1 borrowers drop out of the outside market
    as soon as i > i3(1) .
   If no local lenders:
         ĩ = l / (p1 (1) + (1- p1) (2) ) but ĩ > i3(1)
   With incomplete information
       Credit depends on the characteristics of
        other potential borrowers in her locality
       Adverse selection can lead to credit
        rationing even in the absence of govt
        interest rate controls
       Lenders with access to cheap funds may
        not be able to penetrate local markets
Voluntary default and enforcement
mechanisms

   Lack of formal legal enforcement
    mechanisms
       Why do borrowers repay?
       Construction of repayment incentives in
        the absence of legal sanctions
           Self-enforcing contracts
           Social sanctions
        Voluntary default.

   Low income before the harvest (Yg); high
    income after the harvest (Yh).
   Borrower:
        In autarky:
                UA  U (Yg) + U (Yh)

        With borrowing allowing consumption smoothing
               ULR  U (Yg+L) + U (Yh-(1+r)L)
               L>0 st ULR > UA since U concave.

        If voluntary default
                  ULD  U (Yg+L) + U (Yh)
    Lender:
        A = 0
        LR = rL
        LD = -L



    For the borrower ULD > ULR ,  No lending will happen.

    Lender/borrower    Repay :Yes          Repay : No

    Lend : Yes         ULR , LR           ULD , LD
    Lend :No           UA ,  A            UA ,  A
        Long-term relationship

   Repeated game: constant probability  to play during
    the next period
   For the borrower:
        If default : ULD at this period, UA during the following ones.
        If repay, ULR at each period

   Repayment will occur if
      U (Yh) - U (Yh- (1-r)L) < t=1, t (ULR - UA )
    Hence:
       ULD – ULR < (/(1-))(ULR - UA )
    Dynamic incentives
   Role of the size of the loan
       Upper limit on the size of self-enforcing loan contracts.
   Improving the probability of reimbursement in a
    repeated game:
       start with a small loan and work your way to bigger loans
       interest rate below the next best alternative source of credit
       credible threat to cut people off
   If other sanctions are possible (social or economic), with a utility
    cost D:
        ULD  U (Yg+L) + U (Yh) -D

    (similar role for collateral)
    It allows to reach a greater L with a smaller 

   If new sources of credit appear such that UA < UN < ULR (profit
    attracts other lenders; it generates more default)

    The previous reimbursement constraint might not hold anymore.
    The exclusivity in the relationship is crucial for the threat of
    exclusion from future loans to be credible.
   Limits on the size of the loans.

   If imperfect information st voluntary and unvoluntary
    default cannot be distinguished, L if smaller and the
    probability of market collapse if higher.

   Market is segmented.
    Credit Institutions

   Formal.
   Informal:
       Better information (notably within the family)
       Better enforcement capacity because of the wider availability of
        social sanctions.
       Depends on the environment (availability ofcollateral,
        migrations…)
       Very segmented activities
   Examples:
       Informal lenders.
       ROSCAS (Tontines)
       Credit + insurance (Udry, Nigeria): 97% of the transactions
        occur within the village or within the family.
       Interlinked credit : obtained from the landowner or the trade
        intermediary.
    Group lending

   Some formal institutions attempt to cumulate the
    advantages of the formal system (spatial
    diversification, lower refinancing cost..) and from
    the informal one (information, sanctions):
   Group lending: Members of the group are jointly
    responsible for reimbursing loans and collectively
    sanctioned in case of default (exclusion from future
    loans).
   Ex: Grameen Bank
       Very low default rate … two years after the due date
       Reality of sanctions?
       Disputed impact on poverty.
        Group lending with joint
        liability.
   Recap: problems faced by a potential lender are:
       Adverse selection (what is the risk of a potential borrower?)
       Moral hazard (will the borrower se the loan so as to be able to
        repay it?)
       Auditing costs (assessing the reality of a project failure)
       Enforcement (how to enforce repayment in case of voluntary
        default?)
   Using local information and social capital among
    borrowers, group lending with joint liability may be able
    to deal with those problems.
     Group lending:
   Output Y takes two values: YH > YL =0
   YH is obtained with probability p
   Each project requires 1 unit of capital and repayment is
    ρ>1 (principal + interests)
     u is the opportunity cost of labour
   Project are socially profitable, i.e.
                     pY H    u
   In the case of individual liability, interest rate (gross) is r.
    In the joint liability case, if one member of the group
    default, the other has to pay an additional cost c.
     Dealing with adverse selection
   Two types of borrower: safe (a), risky (b).
   p varies with the type so that pa> pb
   The expected payoff for a borrower of type i paired with a borrower of
    type j in a joint liability contract is:

              EUij (r, c)  pi p j (Yi H  r )  pi (1  p j )(Yi H  r  c)
   Hence, the net expected gain for the risky borrower to have a safe
    partner writes:
                 EU ba (r , c)  EU bb (r , c)  pb ( pa  pb )c
   And the expected loss for a safe borrower of having a risky partner:
            EU aa (r , c)  EU ab (r , c)  pa ( pa  pb )c
   As a result, risky borrower are never ready to pay
    enough to compensate safe borrowers to be paired with
    them:
   → under joint liability, group formation should display
    positive assortative matching.
   This allows the bank to screen the borrowers by offering
    two different contracts: low interest rate and high joint
    liability (chosen by safe borrowers groups) and high
    interest rate and low joint liability (chosen by risky
    types).
     Dealing with Moral Hazard
   Peer monitoring works because group members have an incentive
    to take remedial action against a partner who mis-use her loan.

   Borrowers can choose a level of effort that affect probability of
    success at a cost. This level of effort is not observable by the bank,
    but is observable by other group members.

   Interest rate is like a tax on success, since you repay only when
    output is high: hence, the higher r, the lower the effort.

   Under joint liability, if borrowers do not cooperate, the same level of
    effort as under individual liability is chosen. Nevertheless, if they
    cooperate, they can choose higher p and benefit from lower r.

   This is true even if monitoring the others actions is costly.
Auditing.
   If group members face a lower cost of verifying
    each other’s output than the bank, then the bank
    can avoid the cost of performing its own audit every
    time a borrower claims she has low output by
    inducing her partner to undertake liability for her.

   The partner has an incentive to audit the borrower
    because he is partly liable for her repayment.

   Only when the whole group announces its inability
    to repay will the bank have to audit.
Enforcement.
   Issue arises from the lender’s limited ability to apply
    sanctions in case of voluntary default.

   But the group and the community can apply social
    sanctions (as already discussed).

   This compensates the detrimental effect of joint
    liability on enforcement due to the fact that
    moderately successful borrower might prefer to
    default on her own loan if the partner is defaulting
    rather than incurring all the cost.
Difficulties in implementation:

   Optimal group size?
       Big groups allow to diversify risk within the
        group.
       But big groups dilute the monitoring capacity.
   The cost of group lending
       meeting time cost
       one person’s risk is all’s risk
       if one borrower really needs to default, then the
        others may also prefer to default
       possible excessive pressure to undertake safe
        projects
       Joint liability in real life:
       Grameen Bank.
   About two millions borrowers.
   lends to individuals in self-selected group of 5 from the same
    village. If any individual within a group defaults, the group is
    responsible. No collateral is required. The groups meet weekly to
    check in with one another.
   Starts with a small saving. Then two members receive a loan, to be
    repaid weekly, for one year. If the repay, two more members get a
    loan.
   average loan size of around $100
   Repayment rates may average around 97-98 percent
   94 percent of borrowers are women
   technical assistance includes vocational training, productive inputs.
   Impose a code of conduct that dictates “life improving” changes
   interest rates average around 20 percent (real interest of 12
    percent)
Evaluating microfinance

   3 sets of criteria:
       the ability to earn revenues that exceed
        costs
       the ability to survive without subsidized
        inputs
       the ability to effect meaningful changes in
        the living standards of clients
                       Grameen Bank Balance Sheet Data from Morduch

                                      millions of US $

Variable                            1987     1989        1991     1992     1993     1994



Avg. annual loans outstanding       18.15   42.03        62.99    91.31    169.77   249.04

Annual disbursement                 35.77   64.67        100.03   164.59   321.96   380.98

Borrowers (millions)                0.329   0.648        1.042    1.385    1.683    1.861

Default Rate                         3.7      3.1          7       3.7      3.7      3.7

Income from lending                 2.45     5.07         9.09    13.51    27.31    41.13

Investment income                   1.98     2.85         4.62     3.85     2.99     1.44

Income grants                       0.11     1.86         1.98     1.61     1.94     2.17

Total income                        4.84     9.35        14.92    19.99    34.29    50.43

Total expenses                      4.83     9.28        14.92    20.13    34.04    49.88

Reported profit                     0.02     0.07         0.32    -0.15     0.25     0.54

Revised profit                      -0.1     -1.79       -1.66    -1.76     -1.7    -1.63

Total subsidies                     4.65     9.86        15.39     17.6    23.51     27

Subsidy per $ outstanding %          26       23          24       19       14       11
The Grameen controversy

   Wall Street Journal Critique:
       repayment rates of 95% not true
           2 northern districts 50+ late by more than 1 year
           19% of total portfolio over 1 year overdue
           using 2 year cutoff, 10% overdue
   causes:
       1998 flood
       competition  more default
       implementation mistakes, e.g. “group funds”
   responses: Grameen Managing Director
       fixing things, 95% repayment rate in 6 months
       15% having difficulties due to “external factors”
       “We built our system on the faith that the poor
        always pay back. Some times they take longer
        than the originally scheduled time period,
        sometimes natural disasters like flood, drought
        or political unrest, rules and procedures of the
        bank make it difficult or impossible to pay back,
        but given the opportunity, they pay back. Non-
        repayment is not a problem created by the
        borrowers, it is created by the factors external to
        them.”
Evaluating microcredit:
Welfare Effects

   “Current experience, supplemented with a host of
    short-term studies, attests to great possible
    achievements. The successful programs are
    clearly successes. Visits to areas served by
    programs show what cannot be seen in books of
    accounts – earnings from microfinance participation
    are funding new houses, further education for
    children, new savings accounts, new businesses.
    In the process, lives are being changed and poor
    households are lifting themselves up.”

   + Yunus’ Nobel price.
Evaluating micro-credit:
Welfare Effects

   participatory rural assessment
   program evaluation regressions:
       welfare= controls + receipt of credit
       selection bias
           participants differ in systematic, unobservable
            ways
           program placement
       can distort measured impact by up to
        100%
Fixing selection bias

   two stage correction (Heckman)
       estimate determinants of participation
       use these estimates to correct for
        selection bias in welfare outcomes
       importance of first stage variables
        (influence participation but no
        independent effect on outcomes from
        participating)
   Natural/control experiments
       need control with no spillovers
    Evaluation difficulties: Grameen
    Bank
    Pitt & Khandker (1998) estimate that household
     consumption increases by 18 taka for every 100 take
     lent to a woman.
    Strong identification hypotheses: relies on the fact that
     observable characteristics of individuals affect outcome
     differently for treated (eligible with access) and non
     treated groups, and assign all differences to the
     treatment. No non-linearities in the impact of Xs on
     outcome.
    Morduch (1998), with the same data, in a simple DD
     framework: hh with access have a lower consumption
     (by 7%) than those without.
    Both papers find impact on consumption smoothing.
    Banerjee et al.(2009) find that 15 months after lending,
     no effect on avg monthly expenditure but increase in
     expenditures in durable goods and in number of new
     businesses; heterogenous effect

				
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