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Financial Inclusion of the Poor in Peru. Dr. Ana Marr, University of Greenwich, London, UK Dr. Janina Leon, Universidad Catolica de Peru Mg. Fatima Ponce, Universidad Catolica del Peru LACEA 2012, Lima - PERU. Content. 1. Background 2. The importance of the study - PowerPoint PPT Presentation
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Financial Inclusion of the Poor in Peru
Dr. Ana Marr, University of Greenwich, London, UK
Dr. Janina Leon, Universidad Catolica de PeruMg. Fatima Ponce, Universidad Catolica del Peru
LACEA 2012, Lima - PERU
Marr/Leon/Ponce 2
Content1. Background2. The importance of the study3. The Peruvian microfinance experience4. Poverty in Peru5. Hypothesis and Empirical model 6. Analysis of results7. Main lessons
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1. BackgroundReview of international academic literature on
microfinance. Particular interest in the debate about potential trade-off
between MF financial sustainability and poverty reduction. Cull et al (2007): 124 MFs in 49 countries. Evidence of
trade-off based on loan methodology (group vs individual), MFI size and age. Larger and older individual-based MFIs performed worse on outreach to clients.
Mersland and Strom (2008): 32 NGOs, 68 private MFIs, in 54 countries. They find little evidence of importance of ownership but regulation matters.
Karlan and Morduch (2010): Financial inclusion. From simplest form (micro-credit) to broader inclusion (savings, insurance, remittances, etc). Links with poverty.
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2. The importance of the studyOne of the first studies on financial inclusion –
taken as a specific subject of research. Applied to one of the most dynamic
microfinance markets in the world, i.e. Peru. Obtained exclusive information about financial
inclusion of all regulated MFIs in Peru. We employ the simplest concept of financial
inclusion, i.e. access to micro-credit. The determinants include: MFIs’
characteristics (i.e. size, age, branches); performance; strategic alliances
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3. The Peruvian Microfinance ExperienceHistorical facts
Financial requirements Importance of public policy
Current Financial System and Microfinance (Table 2, p.11)Role of Prudential regulationMain formal and non-formal channels
Microfinance in Regulated Institutions Commercial banks “Non-bank” microfinance institutions
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4. Poverty in PeruMain features (Graph 1, p. 12)
Poverty and extreme poverty in the countryInequality of income –main trends
Financial Inclusion and Microfinance – main indicators (Graph 2, p.13)
Credits by Poverty LevelLoans by Poverty Level
Newly banked population (Graph 4, p.14; Graph 5, p.15)
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5. Hypothesis and Empirical modelResearch questions: How far has the Peruvian population
gained financial access to microfinance? Main hypothesis:
Financ.incl. = f(MFI charact; MFI profitab.; MFI social perf.; (+) (-) (+)
MFI strateg connect, econ sectors, ). (+) (¿?)
Methodological issues:Main variablesData basesEmpirical model
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6. Main Correlations of Newly Banked Clients
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GRAPH 6: SCATTER PLOT BETWEEN: TOTPERS and PROFITABILITY, TOTPERS and NUMBER of BRANCHES, AND TOTPERS and ASSETS
Source: Own elaboration.
0
4,000
8,000
12,000
16,000
20,000
24,000
28,000
32,000
0 10 20 30 40 50 60
ROE2008
TO
TP
ER
S
0
4,000
8,000
12,000
16,000
20,000
24,000
28,000
32,000
0 20 40 60 80 100
NSUC
TO
TP
ER
S
0
4,000
8,000
12,000
16,000
20,000
24,000
28,000
32,000
0 1,000 2,000 3,000 4,000
ASSETS
TO
TP
ER
S
Positive correlation between newly-bankable clients (TOTPERS) and MFI profitability (ROE, rTOTPERS, ROE= 0.73), number of MFI branches (NSUC, rTOTPERS,NSUC= 0.92) and the MFI total asset value (ASSETS, rTOTPERS,ASSETS= 0.95).
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6. Multivariate Analysis of Results ^TOTPERS = 1202.7 +7.07ASSETS + 64.2NSUC – 1364.4ANTIGUO + 1074
RBN9t-stat 1.43 6.5 2.3 -2.9 2.1
R2= 0.91 F=71.3All the slope coefficients with a significant level to 5%.
Positive relationship between the newly-banked clients and the value of total assets of MFI: For each million of New Soles increasing the MFI assets, around seven new clients will be banked, ceteris paribus.
Positive relationship between the newly-banked clients and the number of MFI branches: For each new MFI branch open, around 64 new clients will be banked, ceteris paribus.
Number of newly-banked clients closely associated to the MFI growth in Assets and # Branches; still estimated values are small.
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7. Main lessonsConclusions
Financial inclusion in the last decadeMicrofinance and poverty
Policy inferences
Further research
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TABLE 2: FINANCIAL INSTITUTION BY TYPE OF CREDITSType FI
Banks CMAC CRAC EDPYMES
Financial
Entities
Total
Commercial 56.1 9.1 6.6 3.0 11.0 97.
5
1.3 0.2 0.1 0.9 100.
0Mortgage 15.0 4.2 2.5 6.9 1.3 96.
7 2.2 0.3 0.4 0.4 100.
0Microcredit 10.9
66.9 69.7 79.4 53.1
52.0
26.2
5.7 3.6 12.5
100.0
Family consumption
18.0 19.9
21.2 10.6 34.7
82.6
7.5 1.7 0.5 7.8 100.0
Total 100.0
100.0
100.0
100.0
100.0
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GRAPH 1: PERUVIAN REGIONS BY INCIDENCE OF POVERTY, 2010
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GRAPH 2: LOANS BY TYPE OF FINANCIAL INSTITUTION AND REGION
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GRAPH 4: POVERTY INCIDENCE & NEWLY-BANKED BY REGIONS
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0.000.200.400.600.801.001.201.40
0.010.020.030.040.050.060.070.080.090.0
HUAN
CAVE
LICA
APUR
IMAC
HUAN
UCO
PUNO
AYAC
UCHO
AMAZ
ONA
SCU
SCO
LORE
TOCA
JAM
ARCA
PASC
OPI
URA
LAM
BAYE
QUE
LA LI
BERT
ADJU
NIN
SAN
MAR
TIN
ANCA
SHUC
AYAL
ITU
MBE
SAR
EQUI
PAM
OQ
UEGU
ATA
CNA
LIM
AIC
AM
ADRE
DE
DIO
S
Poverty Incidence (%) Newly-Banked pc (%)
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GRAPH 5: POVERTY INCIDENCE AND NEWLY BANKED – Scatterplot
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0.00
0.20
0.40
0.60
0.80
1.00
1.20
1.40
0.0 20.0 40.0 60.0 80.0 100.0
New
ly-Ba
nked
per c
apita
Poverty Incidence
Marr/Leon/Ponce 16
GRACIAS!!THANK YOU!!
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