Poor access to formal credit has compelled these households to take loan from informal sources who sometimes charge interest @ 60 to 120 per cent per annum, threatening the livelihoods of these smallholders and poor households. During the study period of three years (2010 - 2013), no change in situation was visible in the VDSA villages and the access to formal sources of agricultural credit seems to remain truncated.

1. Truncated Access to Institutional
Agricultural Credit as a Major Constraint
for Rural Transformation: Insights from
Longitudinal Village Studies
Ranjit Kumar, V Surjit, C Bantilan, MA Lagesh and US Yadav
Research Program: Markets, institutions & Policies
International Crops Research Institute for the Semi-Arid Tropics
Hyderabad- 500048

2. Setting the context…
Several policy measures:
• Setting up institutions like, NABARD, RRBs, CBs, Co-op banks,
KCCs, MFIs, SHGs/ JLGs
• Interest subsidy interventions: 4%p.a., even 1-2%p.a.
• Increased flow of institutional credit to agriculture by >10X (₹
0.53 lakh crore in 2001-02 to ₹.6.07 lakh crore in 2012-13).
• Priority sector lending: 18% of ANBC targeted for AGRICULTURE;
out of that 7-8% of earmarked for SMF (RBI, 2015).
• Shortages of formal rural credit are also blamed for delaying,
if not preventing, a timely adoption of new technology,
thereby slowing down rural transformation (WB, 2010).
• Only about HALF (57%) of 14 crore farm households
were covered by formal institutions (NABARD 2014, Hoda
and Terway, 2015)
15K
farmers
opt out of life
every year
since 1995
72.4% SMF
(Source: NCRB, 2014)
Primary
Reason???
Indebtedness

3. Specific objectives:
1) To examine the trend and pattern of rural
credit in eastern and semi-arid tropics (SAT)
regions of India;
2) To determine the access and distribution
pattern of different sources of rural credit;
and
3) To analyse the factors determining access
of various categories of farm households to
formal credit in both the regions.

4. Data and Methodology
Study period: 2010/11 thru 2013/14
Total sample: 1112 Panel Hhs
Grand total : 3336 Households
SAT region:
AP - 2 Ds, 4 Vs, 198 Hhs
MH- 2 Ds, 4 Vs, 162 Hhs
KA- 2 Ds, 4 Vs, 269 Hhs
Eastern region (ER):
BH - 2 Ds, 4 Vs, 160 Hhs
JH - 2 Ds, 4 Vs, 160 Hhs
OD - 2 Ds, 4 Vs, 163 Hhs
Analytical framework
• Both macro- and micro- level data used.
• Tabular analysis
• Tobit model with Random Effect
Dependent variable: Ratio of formal agricultural
credit to total agricultural credit availed by
individual household

5. • Formal credit supply growing, but
seriously diverging.
• Lack of rural financial infrastructure in
ER, not supporting flow of rural credit.
• Adverse C-D ratio in rural ER as
compared to SAT region.
• Formal agril. Credit disbursement in ER
is too meagre.
• More than 85% of rural households in
ER are smallholders.
Rural credit supply in the
regions
0
2000
4000
6000
8000
10000
12000
200120032004200520062007200820092010201120122013
Percapitacreditoutstanding(in₹)
Bihar Odisha Jharkhand
Andhra Pradesh Karnataka Maharashtra
State Rural popln
per branch
(‘000), 2013
Rural C-D
ratio (2013)
Per capita agril.
Credit outstanding
in rural area, 2013
BH 20 30 ₹ 1,572
JH 11 32 ₹ 1,672
OD 10 46 ₹ 2,960
AP 8 110 ₹ 17,557
MH 7 88 ₹ 9,331
KA 4 71 ₹ 13,302
Source: Banking Statistics, RBI

6. Participation of VDSA households in credit market
Rural indebtedness:
90% - SAT region;
45% - Eastern region
Huge appetite for
credit in SAT
region multiple
borrowing.
Region
Survey year
Total HH
No.
% of HH
availing any
credit
% of loanee HH
No Loan*
formal
source
Informal
source
East
India
2010 480 54.8 50.6 65.0 45.2
2011 483 58.2 45.6 68.3 41.8
2012 486 46.7 54.6 63.4 53.3
2013 492 44.5 59.4 53.0 55.5
SAT
India
2010 626 90.3 70.1 80.2 9.7
2011 627 89.2 70.3 82.6 10.8
2012 623 91.2 75.9 82.2 8.8
2013 625 90.4 70.1 78.2 9.6
Are they not
interested???
*Except small amount taken frequently from relatives & friends as interest free.
No. of HHs
availing
informal credit
No. of HHs
availing formal
credit
>
Transaction costs for smallholders & rural poor are much higher than that for Creditors

7. Nature of loan taken by the panel households, 2013-14
1
2
3
4
Mostly from SHGs, Co-operative and Friends & relatives for the
Agricultural purpose
Commercial banks, for purchase of livestock and agril. implements
From formal sources for the agriculture and agril. implements
Money lender, MFI and private banks for short term consumption
purposes and long term agril implements
Agriculture
Purchase of implements
Purchase of livestock
Social functions
Consumption
Education
Medical
Business
Repay old debt
Major repairs
Purchase of land
Marriage
Drill well/bore well
Others
No. of households
50100150200250 50
SATRegion
EasternRegion
Informal
loan
Formal loan
100
₹40K ₹42K₹67K ₹12K

8. Poor section of the
Truncated formal agricultural credit
(113
hhs)
(155
hhs)
(316
hhs)
(154
hhs)
30
20 18
64
52
47
36
19
15
60
50 49
34
21
12
69
50
53
39
16
11
59
51
48
GEN OBC SC/ST GEN OBC SC/ST
Eastern region SAT region
% of VDSA households
2010 2011 2012 2013
(271
hhs) (103
hhs)
SOCIAL CATEGORY
38
18
22
10
76
63
51
23
41
23
17
8
79
61
48
23
38
29
19
3
74
66
54
26
31
23
19
8
74
63
46
25
Large
Medium
Small
Landless
Large
Medium
Small
Landless
Eastern region SAT region
% of VDSA households
2010 2011 2012 2013
LAND-SIZE CATEGORY

9. Factors influencing access to formal agricultural credit
Variable E Region SAT region Pooled
Y: Ratio of formal agricultural credit to total agricultural credit
Land ratio NS 0.007*** 0.006***
Farm income NS 0.311* 0.339*
Education 0.011* 0.017*** 0.017***
Age -0.004** 0.003** NS
District HQ -0.012*** -0.003*** -0.003***
Rainfall -0.007*** NS NS
Year NS -0.036*** -0.024*
Farm size- D 0.113* 0.089*** 0.082***
Credit society-D -0.734*** -0.218*** -0.178***
Bank- D NS 0.071** NS
SHG- D -0.370*** (omitted) NS
Region- D --- --- 0.208***
Constant -189.251* 73.117** 47.784*
Sigma 0.395 0.4019 0.406
No. of observation 192 1000 1192
log likelihood -94.167 -507.443 -617.592
+ve influences:
 SAT region
 Large farm size
 Education level
-ve influences:
Ӧ Distance from township
Ӧ Presence of PACS/SHG
Formal credit should
have been great
equaliser in
transforming society.

10. Magic lies at the
Bottom of the
Pyramid…
Conclusions:
• Improved institutional credit flow to
agriculture, but truncated at
different social and economic
category.
• Unmet demand of credit: Focus on
rural credit, and not only crop loan.
• Financial inclusion must for rural
transformation- Interest subsidy
alone can’t guarantee rejigging
institutional framework
Way forward…
• High-level buy-in: strong institutional
commitment with different mind-sets,
approaches and systems.
• Flexible products: Loan tenure, disbursement,
and payment terms need to suit diverse profiles of
smallholders.
• Better understanding of cash flow
rather than assets
• Digital disruption: automation of data
capture, WALLET Banking, Staggered merchant payment,
etc. reduce transaction cost, faster delivery.
• Financial literacy and awareness: we
never find advt. for such loans as for home loan, vehicle
loan or any other urban fin products
Push the boundaries of
possibilities…

11. Thank you!
Email:
k.ranjit@cgiar.org
ICRISAT is a member of the CGIAR Consortium
The study was financially supported by Bill &
Melinda Gates Foundation (BMGF) under the
project on ‘Village Dynamics Studies in South
Asia (VDSA)’.
Visit us at: http://vdsa.icrisat.ac.in/