Practice What you Preach - Benchmarking Microfinance Institutions with Heterogeneous Preferences

IntroductionBenchmarking

ResultsConclusions

Practice What You PreachBenchmarking Microfinance Institutions with Heterogeneous

Preferences

Jaap Bos, Maastricht UniversityMatteo Millone, Maastricht University

ECCE Webinar, 17 April, 2013

Jaap Bos & Matteo Millone Practice What You Preach


ResultsConclusions

Motivation and ContributionResearch QuestionsFindings

What we do

Benchmark the efficiency of microfinance institutions, while takinginto account differences in business models.



ResultsConclusions


”No longer can microfinance investment be viewed as anexclusively do-good, low-risk, relative safe haven. [...] equityinvestors are reassessing the social and financial performanceof the asset class.” J. P. Morgan, Global MicrofinanceValuation Survey 2011

”Everyone involved in microfinance shares a basic goal: toprovide credit and savings services to thousands or millions ofpoor people in a sustainable way ... a problem of dualmaximisation” Rhyne, The Microbanking Bulletin



ResultsConclusions


Investing in microfinance

More than one criterium guides the decision to invest inmicrofinance:

1 Financial risk and return

2 Outreach and impact (social and political risk)

Large variation across microfinance institutions (MFIs)

Relative weight of criteria depends on preferences of investor

Unclear relationship between two sets of criteria



ResultsConclusions


Benchmarking Paradox

Benchmarking makes sense only if we compare apples to apples

Focus on efficiency

Relevant for microfinance, given scarcity of inputs!

Calculate efficiency by taking into account differentdimensions of output



ResultsConclusions


Research questions

Are MFIs really that different?

Is there a trade-off between number of clients served, missiondrift and price of the loans?

Are MFIs that lend to richer borrowers more efficient?

Is it possible to offer small and affordable loans?

Is there such a thing as an excessive focus on womenborrowers?



ResultsConclusions


Benchmarking and Engaging

Our methodology provides a useful tool to:

Benchmark Pick the most efficient institutions compared to apeer group.Advantage:Ranking valid across output measures.Target:Passive investors with predefined preferences,looking at investing in the best practice MFIs

Engage Identifies common traits of under performing MFIs.Advantage:Indicates size and direction of possibleefficiency gain.Target:Investors looking at opportunities to generatesocial impact through engagement.



ResultsConclusions


Preview of the results

MFIs differ strongly given differences in their legal status

There is indeed a non-linear trade off between missiondrift and number of clients served

Targeting richer borrowers reduces efficiency

Lending to the very poor is efficient, but not affordable(for the clients): MFIs with higher outreach charge higherinterest rates

Lending exclusively to women reduces efficiency



ResultsConclusions

ApproachMeasuring preferencesTheoryAdvantages

Benchmarking firms with heterogeneous preferences

Population of MFIs

Non-for profit Microfinance Institutions (MFIs) with highoutreach and dependent on subsidies

Profitable MFIs with lower outreach, high interest rate andprivate funding

... and a whole lot in between

How can we compare the performance of institutions with differentobjectives and incentives?



ResultsConclusions


Measuring preferences

MFIs have heterogenous preferences (goals), that need to be takeninto account when assessing performance.

Decompose output into 3 measures:

Yield - Price of the Loans

Average Loan Size - Mission Drift(Depth of Outreach)

Number of Loans - Outreach(Breadth of Outreach)

Value Added of Gross Loan Portfolio (Total Output) =Yield x Average Loan Size x Number of Loans



ResultsConclusions


Accounting for multiple dimensions

Given the same inputs:

The cost per dollar lent of a small loan will always be largerthan for a bigger loans...

...MFIs that serve the very poor will have higher costs andpoorer financial performance...

... which will lead to a lower added value of gross loanportfolio in the future.

Find a measure of performance that does not depend onpreferences:

Efficiency



ResultsConclusions


Average Loan Size

Num

ber

of

loans o

uts

tandin

g

C

A

B

D

Gross loan portfolioE

"Poorest of the poor" type MFI

"Mission drift" type MFI

Ineffi

cien

cy

Inefficiency



ResultsConclusions


Only one measure: Efficiency

The position on the curve (preferences) does not matter, onlyrelevant factor is the distance from the curve

Intuitive interpretation

80% efficiency: given inputs output can be increased by 20%

Circumvents limitations of rating agencies (CGAP, 2010):

Diversity of products and lack of clarityDuality between assessment for the MFI and service for theinvestorEmphasis placed by MFIs on professional and interpersonalrelationships with rating agencies may jeopardize neutrality ofagencies

Cheap, fast, standardized



ResultsConclusions

DataHeterogeneity of MFIsOutput trade-offEfficiency and Mission DriftExogenous Determinants of Efficiency

Microfinance Information Exchange market (MIX)

Widely used in the literature

Self reported balance sheet information

Unbalanced panel data

1,146 MFIs

2003-2010

3,890 total observations



ResultsConclusions


MFIs differ strongly depending on legal status

Bank NGO

Ou

tpu

ts

Average Loan Size 1627.5 650.4

Number of Loans 78132 45154

Yield 0.24 0.28

Yield(n) 0.33 0.35

GLP (millions) 88.5 12.9

Co

sts

Costs per loan 283.9 115.1

Cost per dollar 0.23 0.26

Oth

er

Portfolio at risk 30 0.05 0.05

% women borrowers 53.0 74.4



ResultsConclusions


Implications of MFI heterogeneity

Depending on legal status MFIs have very different businessmodels

Size of loans, cost per loan and % of women show largestvariation

Difficult to identify ”better” institutions

Warrants the use of a multi output performance tool



ResultsConclusions


Output trade-off

Mean Elasticityof Average Loan Size

Elasticity to number of loans -0.68***Elasticity to yield on gross loan portfolio -0.18***

Total input price elasticity 0.94***

How to read the coefficients

Negative elasticity implies a negative relationship (trade-off)

The larger the elasticity the stronger the trade-off

Total input elasticity <1 implies no economies of scale



ResultsConclusions


Implication of output trade-off

Breadth and depth of outreach are positively correlated

Offering larger loans (mission drift) does not help to increasethe number of clients

Smaller loans are more expensive

Increasing the size of the institutions does not lead toeconomies of scale



ResultsConclusions


Is the trade off constant?

.2

.4

.6

.8

1

− E

lasticity o

f A

LS

to N

um

ber

of Loans

0 5000 10000 15000 20000

Average Loan Size

−.2

0

.2

.4

.6

− E

lasticity o

f A

LS

to Y

ield

0 5000 10000 15000 20000

Average Loan Size



ResultsConclusions


Implications of non-linear trade-off

Increasing strength of elasticity to loan size

Number of loans and size of the loan are always negativelycorrelatedLarger loans are more expensive in terms of depth of outreach

No evidence that mission drift increases breadth ofoutreach

Decreasing strength of elasticity to yield on gross portfolio

As average loans size increases the negative relationship withyield tends to disappearFor a number of MFIs there is no need to charge higherinterest rates for smaller loans

No evidence that mission drift is always correlated witha reduction in interest rates



ResultsConclusions


Does mission drift increase efficiency?

.2

.4

.6

.8

1

Technic

al E

ffic

iency

Small Loans Large Loans

Correlation between average loans size and efficiency = -0.20***



ResultsConclusions


Implications of mission drift and efficiency

No evidence of MFIs offering larger loans being more efficient

Mission drift does not lead to better use of resourcesSmaller loans are more efficient

Challenges of moving upmarket

Lower quality of residual borrowersDifferent managerial skill setIncreased competition with banks



ResultsConclusions


Can the poor be served efficiently?

.65

.7

.75

.8

Eff

icie

ncy

Cheap Loans Expensive Loans

Small Large Small Large Small Large Small Large



ResultsConclusions


Implications of price and size of loans

Average efficiency is higher for MFIs that offer more expensiveloans

Easy way to cover costs... but requires low price elasticity of borrowersPositive effect on efficiency erased by large loan size

The poor could be served cheaply

The most efficient MFIs offer small expensive loans... but MFIs that offer relatively small and cheap loan can stilloperate above average efficiency



ResultsConclusions


How can efficiency be improved without changingpreferences?

Variables Effect

PAR30 · GrossLoanPortfolio -

%Women · Borrowers -***

Loans/Borrowers -***



ResultsConclusions


Implications of exogenous determinants of efficiency

Benefits of screening and monitoring do not outweigh thecosts in terms of efficiency

Focus on women, reduces efficiency as MFIs need to deviatefrom equilibrium

... but has positive social impact

Multiple loans should be avoided



ResultsConclusions

Main FindingsDiscussion

Main Findings

Which MFI can make the most out of its limited resources?

Mission drift decreases both breadth and depth of outreach

Serving richer borrowers does not increase efficiency

Cheap small loans are not common, but are possible (andefficient!)

Lending to women and over lending reduce efficiency



ResultsConclusions


Discussion

MFIs are efficient when they stick to what they know best

Mission drift (loan size creep) does not increase efficiency:

Insufficient economies of scaleLack of managerial skillsLoss of subsidesIncreased competition



ResultsConclusions


Limitations

Imperfect measure of prices

Take into account only lending

Possible applications to other industries with mixed social andfinancial returns


Practice What you Preach - Benchmarking Microfinance Institutions with Heterogeneous Preferences

Economy & Finance

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