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Institutional vs Non-institutional Credit to Agricultural Households in India:
Impact on Farmers' Welfare
Anjani Kumar
99th Annual Conference Indian Economic Association
27-29 December 2016Tirupati, Andhra Pradesh
India
Outline of the presentation Background Data Methodology Findings Conclusions
Background Credit plays a crucial role in agricultural
development enables farmers to undertake new investments and/or
adopt new technologies. access to credit can enhance the risk bearing ability of
the farmers and support them invest in a little risky ventures with higher potential returns
act as a catalyst to break the vicious circle of poverty in rural areas
Agricultural credit policy in India improve farmers’ access to institutional credit and
reduce their dependence on informal credit ratio of agricultural GDP increased from 10% in 1999-00
to 38% in 2012-13 Accounts for 85% of the purchased inputs in the
agriculture and allied sectors Major milestones of the rural credit before economic
reforms include acceptance of the Rural Credit Survey Committee’s Report (1954), nationalization of the large commercial banks (1969 and 1980), establishment of Regional Rural Banks (1975) and the National Bank for Agriculture and Rural Development in 1982
Contd… After financial reforms in India, the milestones
include Special agriculture credit plan (1994-95) Kisan credit cards (1998-99) Doubling agricultural credit (2004) Agricultural debt waiver and debt relief scheme (2008) Interest subvention scheme (2010-11) Jan Dhan Yojana (2014)
Other measures to strengthen formal credit programs in India
Lead bank scheme Direct lending for priority sector Banking sector’s linkage with the government sponsored
programs Differential rate of interest scheme Service area approach Self-help group banks linkage programs Special agricultural credit plans Rural infrastructure development fund
Contd..
Access to
Formal
Credit
Agricultural
Productivity
Source: Binswanger and Khandker, 1995; Carter 1989; Carter and Weibe 1990; Feder et al 1990; Pitt and Khandker, 1996, 1998; Khandker and Farooqui 2003; Awotide et al 2015; Narayanan 2016
Objective To understand and analyze
Characteristics of agricultural credit markets in India
Characteristics of institutional and non-institutional borrowers
Determinants of access to formal credit. The impact of institutional credit on agricultural
households’ welfare in India
Using unit level data from nationally representative sample of farm survey.
Net farm income and household consumption expenditure were taken as a proxies for measuring agricultural households’ welfare
Data Used “Situation Assessment Survey of Agricultural
Households” carried out by the National Sample Survey Organization (NSSO) in 2013
4529 villages spread across the country 35200 farming households Period; Agricultural year 2012-13
Comprehensive information on socio-economic well-being of agricultural households, consumption expenditure, income from productive assets, borrowing, lending and indebtedness, their farming practices and preferences, resource availability, receipts and expenses of household’s farm and non-farm
businesses, their awareness of technological developments and access to modern technology in the field of agriculture
Methodology Binary Logistic Regression
Determinants of farmers’ access to formal credit
Where; p represents the probability that the farmer
takes formal credit βs are the regression coefficients estimated
by the maximum likelihood method Xs represent the explanatory variables and
include several socio-economic and demographic characteristics of the farm households
Contd… Instrumental variable 2SLS
assess the impact of formal credit on farmers’ profits
Where; is net profit per ha received by a farm household from farming is a dummy variable (= 1 if the farmer takes formal credit and
0 otherwise) is a vector of observable farm and operator characteristics is an error term
Assumptions Estimation of the above equation using simple ordinary least
squares (OLS) may result in biased estimates. unobserved factors could be guiding farmers’ decision to access
the formal credit. Thus,, the variable representing farmer’s access to formal credit, is
likely to be endogenous and could be correlated with the error term, .
Conducted Hausman’s test for endogeneity and found access to formal credit to be endogenous
Proportion of farmers availing institutional credit in a village as the instrumental variable
Status of banking infrastructure in India (Global vis-à-vis India)
BangladeshBrazilChina
FranceGermany
IndiaIndonesia
JapanMalaysia
MexicoNepal
PakistanRussian Federation
Sri LankaUnited Kingdom
United States
0 10 20 30 40 50 60
No. of bank branches per 100,000 adult population
Cou
ntri
es
Source: WDI 2015 (World Bank)
Structure of credit delivery mechanism in India
Source: WDI 2015 (World Bank)
Institutional sources Government Cooperative banks Commercial banks
Non-institutional sources Money lenders Employer Shopkeepers/traders Relatives/friends
Share of institutional credit in rural borrowings in India (1951-2013)
1951 1961 1971 1981 1991 2003 20130.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
8.817.3
29.2
61.2 55.7 57.1 60.3
Year
Perc
ent
Source: AIRCS (RBI); AIDIS (NSSO)
International Food Policy Research Institute
Amount of borrowings in India: 1992, 2003 and 2013
Average amount of borrowing (Rs/ha at 1993-94 prices)
1992 2003 20130
1000
2000
3000
4000
5000
6000
980
3356
4850
International Food Policy Research Institute
Equity in disbursement of institutional credit in India, 2003 and 2013
Source: NSS, GoI
Landless, Marginal and Smallholders
SC & STs OBCs'0
0.2
0.4
0.6
0.8
1
1.2
0.720.44
0.980.840.49
1.13
Ratio of weaker sections in institutional credit and households
2003 2013
Distribution of loans by sources (%)
64%
36%
Formal SourcesInformal Sources
Formal Sources Informal Sources
Government Co-operative Society
Bank0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
0.020.040.060.0
Farmers’ access to credit from formal and informal sectors, 2012-13Distribution of HHs by borrowing
(%)Share of formal and informal
credit in borrowing households (%)
Marginal
Small Medium Large All0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
0.0
10.0
20.0
30.0
40.0
50.0
60.0
14.824.2
30.039.1
22.8
21.7
14.211.6
8.9
16.2
8.913.3
17.0
23.6
13.1
54.7
48.3
41.5
28.5
47.9
Formal sourcesInformal sources Marginal Small Medium Large All
0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
80.0
55.0
64.367.1
74.9
63.6
45.1
35.732.9
25.1
36.4
Formal Credit Informal Credit
Distribution of borrowers households by operational holding (%)
Share of HHs Share of Non-borrower
39.9
30.5
22.8
6.8
45.5
30.8
19.7
4.1
Marginal
Small
Medium
Large
Source of Borrowing Share in Credit
Marginal Small Medium Large0.0
10.0
20.0
30.0
40.0
50.0
60.0Formal Credit Informal CreditBoth Simultaneously
Marginal Small Medium Large0.0
5.0
10.0
15.0
20.0
25.0
30.0
35.0Formal Credit Informal Credit
General characteristics of institutional and non-institutional borrower
Particular Institutional
Non-institutional Particular Institutio
nalNon-
institutionalSocio-demographic variables Structure of households by farm categories
(%)Age (Years) 51.1 46.9 Marginal 25.9 41.6Family size (No.) 5.2 5.2 Small 32.5 28.6Land size (Ha) 1.7 0.8 Medium 30 22.2Per Capita Monthly Expenditure (Rs) 1603.7 1298.3 Large 11.7 7.6
Male headed households (%) 93.8 91 Principal source of household income (%)% received formal training in agriculture 3.7 1.9 Agricultural Income 79.2 74.8
Social structure by caste (%) Non-Agr. Income 17.4 22.4Schedule tribe 8.6 13.1 Pension 1.3 0.5Schedule caste 12.8 19.1 Remittance 1.7 2Other backward caste 46.1 47.2 Awareness and access to social safety nets (%)
General caste 32.2 20.7 Minimum Support Price Awareness 30.6 22.3
Social structure by religion (%) Having MGNREGA Job Card 93.1 90.7
Hindu 88.4 87.2 Have PDS Ration Card 37.4 51.6Muslim 6.1 9.7 Source of Technical AdviceChristian 1.8 1.1 Extension Agent 19.2 17.3Other 3.3 1.8 KVK & SAU 8.5 5Education level of the head of household (%) Pvt Commercial Agents 8.1 8.2Illiterate 30.1 49.4 Progressive Farmer 20.7 22.3
Primary 27.9 24.8 Radio / TV / Newspaper / Internet 28.8 22.7
Middle 17.3 13.6 NGO 1.3 0.8Secondary 12.2 7.6Higher secondary & above 12.4 4.7
Determinants of access to institutional credit
Significant variables dy/dx SELog of age of the household head 0.192*** (0.0134)Middle (Yes = 1, otherwise = 0) 0.0876*** (0.0129)Higher Secondary (Yes = 1, otherwise = 0) 0.138*** (0.0099)Graduate and above (Yes = 1, otherwise = 0) 0.199*** (0.0227)Schedule Tribe (Yes = 1, otherwise = 0) 0.0341* (0.0189)OBC (Yes = 1, otherwise = 0) 0.0321** (0.0155)
Other Caste (Yes = 1, otherwise = 0) 0.0275* (0.0150)
Log of Per Capita Monthly Expenditure (Rs) 0.0668*** (0.0126)Small (Yes = 1, otherwise = 0) 0.100*** (0.0110)
Medium (Yes = 1, otherwise = 0) 0.126*** (0.0138)Large (Yes = 1, otherwise = 0) 0.123*** (0.0208)
MGNREGA Job Card (Yes = 1, otherwise = 0) -0.0778*** (0.0130)Have Ration Card (Yes = 1, otherwise = 0) 0.0556*** (0.0178)Extension Agent (Yes = 1, otherwise = 0) -0.0389** (0.0178)KVK & SAU (Yes = 1, otherwise = 0) 0.0561*** (0.0174)Pvt Commercial Agents (Yes = 1, otherwise = 0) -0.0284 (0.0244)
Progressive Farmer (Yes = 1, otherwise = 0) -0.0444*** (0.0141)Radio / TV / Newspaper / Internet (Yes = 1, otherwise = 0) 0.0105 (0.0135)
NGO (Yes = 1, otherwise = 0) 0.0687* (0.0389)Minimum Support Price Awareness (Yes =1, otherwise = 0) 0.0254* (0.0141)
Constant -6.534***Observations 16583District fixed effect YesLog pseudo-likelihood -10588.192
Average return of net farm income and household consumption expenditure
Net farm income (Rs/ha)
Consumption expenditure (Rs/month/person)
Marginal Small Medium Large All0
10,000
20,000
30,000
40,000
50,000
Marginal Small Medium Large All0
500
1,000
1,500
2,000
Formal BorrowerInformal Borrower
Impact of institutional credit on net farm incomeSignificant Variables Coefficient Standard
ErrorInstitutional Credit (Yes = 1, otherwise = 0) 0.171*** (0.0456)Log of household size 0.387*** (0.0307)Gender (Male = 1, otherwise =0) 0.112*** (0.0361)Graduate and above (Yes = 1, otherwise = 0) 0.121*** (0.0371)OBC (Yes = 1, otherwise = 0) 0.0814** (0.0369)Other Caste (Yes = 1, otherwise = 0) 0.132*** (0.0379)Others Religion (Yes = 1, otherwise = 0) 0.446*** (0.0567)Agricultural Income (Yes = 1, otherwise = 0) 0.785*** (0.1420)Log of Per Capita Monthly Expenditure (Rs) 0.378*** (0.0368)Small landholding (Yes = 1, otherwise = 0) 0.707*** (0.0253)Medium landholding (Yes = 1, otherwise = 0) 1.084*** (0.0295)Large landholding (Yes = 1, otherwise = 0) 1.623*** (0.0480)MGNREGA Job Card (Yes = 1, otherwise = 0) -0.0784*** (0.0290)Private Commercial Agents Source (Yes = 1, otherwise = 0) 0.178*** (0.0607)Radio / TV / Newspaper / Internet Source (Yes = 1, otherwise = 0) 0.0662* (0.0350)NGO Source (Yes = 1, otherwise = 0) 0.258** (0.1120)MSP Awareness (Yes = 1, otherwise = 0) 0.246*** (0.0241)Share of food crop 0.570*** (0.0320)Share of high value crops 0.897*** (0.0338)Share of oilseeds 0.383*** (0.0524)Share of other crops (Non-food) 0.348*** (0.0443)Proportion of HHs availed institutional credit by village wise 0.956*** (0.0030)Constant 5.366*** (0.3760)Observations 16583District Fixed Effect YesR-squared 0.528
Impact of institutional credit on household consumption expenditure
Significant Variables Coefficient Standard ErrorInstitutional Credit (Yes = 1, otherwise = 0) 0.107*** (0.0239)Log of age of the household head 0.195*** (0.0152)Log of household size -0.482*** (0.0111)Gender (Male = 1, otherwise =0) -0.0463*** (0.0162)Middle School (Yes = 1, otherwise = 0) 0.0315*** (0.0120)Higher Secondary School (Yes = 1, otherwise = 0) 0.124*** (0.0131)Graduate and above (Yes = 1, otherwise = 0) 0.233*** (0.0217)Schedule Tribe (Yes = 1, otherwise = 0) -0.0857*** (0.0285)OBC (Yes = 1, otherwise = 0) 0.0584*** (0.0161)Other Caste (Yes = 1, otherwise = 0) 0.0939*** (0.0161)Muslim (Yes = 1, otherwise = 0) 0.137*** (0.0226)Christian (Yes = 1, otherwise = 0) 0.269*** (0.0396)Others Religion (Yes = 1, otherwise = 0) 0.450*** (0.0389)Non-Agricultural Income (Yes = 1, otherwise = 0) 0.143* (0.0790)Pension (Yes = 1, otherwise = 0) 0.249** (0.1110)Remittance (Yes = 1, otherwise = 0) 0.212*** (0.0805)Small landholding (Yes = 1, otherwise = 0) 0.0801*** (0.0123)Medium landholding (Yes = 1, otherwise = 0) 0.173*** (0.0148)Large landholding (Yes = 1, otherwise = 0) 0.311*** (0.0202)MGNREGA Job Card (Yes = 1, otherwise = 0) -0.0640*** (0.0132)Have Ration Card (Yes = 1, otherwise = 0) 0.137*** (0.0151)Krishi Vigyan Kendra & SAU Source (Yes = 1, otherwise = 0) 0.111*** (0.0246)Private Commercial Agents Source (Yes = 1, otherwise = 0) 0.0503* (0.0266)Radio / TV / Newspaper / Internet Source (Yes = 1, otherwise = 0) 0.0735*** (0.0092)MSP Awareness (Yes = 1, otherwise = 0) 0.0832*** (0.0146)Share of food crop -0.0505*** (0.0122)Share of high value crops 0.133*** (0.0173)Proportion of HHs availed institutional credit by village wise 0.957*** (0.0030)Constant 6.694*** (0.0968)Observations 16,583District Fixed Effect YesR-squared 0.360
Hausman test for endogeneity for net farm income and household consumption expenditure
Variable 2SLS^
Coefficient Standard ErrorNet farm income 0.171*** (0.0456)Household consumption expenditure 0.107*** (0.0239)
Ehat$ for net farm income -0.118** (0.0464)
Ehat$ for household consumption expenditure -0.0843*** (0.0249)
Note: ^ Used Instrumental variable 2SLS method to investigate the role of institutional farm credit on farm income and farm household consumption expenditures. Our instrumental variable was “proportion of HHs availed institutional credit by village wise”; $ Hausman’s test for endogeneity for net farm income and household consumption expenditure; Robust standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1
Conclusions Changing structure of rural credit market
in India increase in the flow and share of institutional
credit improvement in financial inclusion indicators land holding (marginal & small farmers) social group (SCs, STs and OBCs)
Concerns in the rural credit delivery system
disparity in disbursement of rural credit (states and social groups)
persistence of informal agencies (charging very high interest rates)
Conclusions Access to Institutional credit has positive
and significant effect Farmers’ profits Farmers’ monthly expenditure
Determinants for agricultural households’ access to institutional credit
age, education, caste affiliation, gender, occupation and assets ownership
Way forward
Flexible products and services
Emphasis on financial literacy
Simplification of lending procedure
Unique identification number for households
Convergence with extension and value chain
development
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