The present study aims to estimate the effect of agricultural credit on paddy productivity and farm income in India. Using National Sample Survey Office data for the year 2018–2019, we deploy an endogenous switching regression model to assess the real impact of access to credit, and we find that it has significantly increased productivity and income. Access to credit is also expected to benefit those who have not yet accessed it. Some of the factors that significantly determine access to institutional credit for agriculture are extension contacts through progressive farmers, training, medium-sized farms, awareness of minimum support price, crop insurance and social category. Therefore, extending credit access to all farmers and enhancing the financial literacy of paddy farmers in utilizing institutional credit are likely to contribute to increased yields and higher farm incomes.
Abdul-RahamanA., IssahakuG., & ZereyesusY. A. (2021). Improved rice variety adoption and farm production efficiency: Accounting for unobservable selection bias and technology gaps among smallholder farmers in Ghana. Technology in Society, 64, 101471. https://doi.org/10.1016/j.techsoc.2020.101471
2.
AbdullahA.-H., AyamgaM., & AwuniJ. A. (2019). Impact of agricultural credit on farm income under the Savanna and Transitional zones of Ghana. Agricultural Finance Review, 79(1), 60–84. https://doi.org/10.1108/AFR-02-2018-0009
3.
AhimbisibweB. P., MortonJ. F., FelekeS., AleneA., AbdoulayeT., WellardK., MungatanaE., BuaA., AsfawS., & ManyongV. (2020). Household welfare impacts of an agricultural innovation platform in Uganda. Food and Energy Security, 9(3), e225. https://doi.org/10.1002/fes3.225
4.
AhmedM. H., GeletaK. M., TazezeA., & AndualemE. (2017). The impact of improved maize varieties on farm productivity and wellbeing: Evidence from the East Hararghe zone of Ethiopia. Development Studies Research, 4(1), 9–21. https://doi.org/10.1080/21665095.2017.1400393
5.
AbuB. M., & HarunaI. (2017). Financial inclusion and agricultural commercialization in Ghana: An empirical investigation. Agricultural Finance Review, 77(4), 524–544. https://doi.org/10.1108/AFR-02-2017-0007
6.
AmareM., AsfawS., & ShiferawB. (2012). Welfare impacts of maize–pigeonpea intensification in Tanzania. Agricultural Economics, 43(1), 27–43. https://doi.org/10.1111/j.1574-0862.2011.00563.x
7.
AssayeA., HabteE., SakuraiS., & AlemuD. (2022). Impact assessment of adopting improved rice variety on farm household welfare in Ethiopia. Journal of Agriculture and Food Research, 10, 100428. https://doi.org/10.1016/j.jafr.2022.100428
8.
AwotideB. A., AbdoulayeT., AleneA., & ManyongV. M. (2015). Impact of access to credit on agricultural productivity: Evidence from smallholder cassava farmers in Nigeria (No. 1008-2016-80242). Agricultural and Applied Economics Association. http://purl.umn.edu/210969
9.
BinswangerH. P., & KhandkerS. R. (1995). The impact of formal finance on the rural economy of India. The Journal of Development Studies, 32(2), 234–262. https://doi.org/10.1080/00220389508422413
10.
BocherT. F., AlemuB. A., & KelboreZ. G. (2017). Does access to credit improve household welfare? Evidence from Ethiopia using endogenous regime switching regression. African Journal of Economic and Management Studies, 8(1), 51–65. https://doi.org/10.1108/AJEMS-03-2017-145
11.
DiamouteneA. K., & JatoeJ. B. D. (2021). Access to credit and maize productivity in Mali. Agricultural Finance Review, 81(3), 458–477. https://doi.org/10.1108/AFR-05-2020-0066
12.
DossC. R., & MorrisM. L. (2001). How does gender affect the adoption of agricultural innovations? The case of improved maize technology in Ghana. Agricultural Economics, 25, 27–39. https://doi.org/10.1111/j.1574-0862.2001.tb00233.x
13.
EswaranM., & KotwalA. (1990). Implications of credit constraints for risk behavior in less developed economies. Oxford Economic Papers, 42(2), 473–482. https://doi.org/10.1093/oxfordjournals.oep.a041958
14.
FaltermeierL., & AbdulaiA. (2009). The impact of water conservation and intensification technologies: empirical evidence for rice farmers in Ghana. Agricultural Economics, 40(3), 365–379. https://doi.org/10.1111/j.1574-0862.2009.00383.x
15.
JenaP. R., StellmacherT., & GroteU. (2017). Can coffee certification schemes increase incomes of smallholder farmers? Evidence from Jinotega, Nicaragua. Environment, Development and Sustainability, 19, 45–66. https://doi.org/10.1007/s10668-015-9732-0
16.
GuirkingerC. (2008). Understanding the coexistence of formal and informal credit markets in Piura, Peru. World Development, 36(8), 1436–1452. http://dx.doi.org/10.1016/j.worlddev.2007.07.002
17.
HabtewoldT. M. (2021). Impact of climate-smart agricultural technology on multidimensional poverty in rural Ethiopia. Journal of Integrative Agriculture, 20(4), 1021–1041. https://doi.org/10.1016/S2095-3119(21)63637-7
18.
KarthickV., & MadheswaranS. (2018). Access to formal credit in the Indian agriculture: Does caste matter?Journal of Social Inclusion Studies, 4(2), 1–27. https://doi.org/10.1177/2394481118814064
19.
MadheswaranS., & KarthickV. (2021). Access to institutional credit by caste among agricultural households in India: A decomposition analysis. Aarthika Charche, 6(1), 77–94. https://fpibengaluru.karnataka.gov.in/storage/pdf-files/Aarthika%20charche/AarthikaCharche-Vol6-No1-2021.pdf
20.
KhonjeM., MandaJ., AleneA. D., & KassieM. (2015). Analysis of adoption and impacts of improved maize varieties in eastern Zambia. World Development, 66, 695–706. https://doi.org/10.1016/j.worlddev.2014.09.008
21.
KumarA., SonkarV. K., & SarojS. (2020). Access to credit in Eastern India: Implications for the economic well-being of agricultural households. Economic and Political Weekly, 55(21), 46–54. https://www.epw.in/journal/2020/21/special-articles/access-credit-eastern-india.html
22.
Lan AnhH., CastellaJ. C., & PaulN. (2006). Social networks and information access: Implications for agricultural extension in a rice farming community in northern Vietnam. Agriculture and Human Values, 23, 513–527. https://doi.org/10.1007/s10460-006-9013-5
23.
LermanZ. (2004). Policies and institutions for commercialization of subsistence farms in transition countries. Journal of Asian Economics, 15(3), 461–479. https://doi.org/10.1016/j.asieco.2004.05.004
24.
LiC., ShiY., KhanS. U., & ZhaoM. (2021). Research on the impact of agricultural green production on farmers’ technical efficiency: Evidence from China. Environmental Science and Pollution Research, 28, 38535–38551. https://doi.org/10.1007/S11356-021-13417-4
25.
ListJ. A. (2007). Field experiments: A bridge between lab and naturally occurring data. The BE Journal of Economic Analysis and Policy, 6(2). https://www.degruyterbrill.com/document/doi/10.2202/1538-0637.1747/html
26.
LokshinM., & SajaiaZ. (2004). Maximum likelihood estimation of endogenous switching regression models. The Stata Journal, 4(3), 282–289. https://doi.org/10.1177/1536867X0400400306
27.
LuanD. X., & BauerS. (2016). Does credit access affect household income homogeneously across different groups of credit recipients? Evidence from rural Vietnam. Journal of Rural Studies, 47, 186–203. https://doi.org/10.1016/j.jrurstud.2016.08.001
28.
MaddalaG. S. (1983). Limited-dependent and qualitative variables in econometrics. Cambridge University Press.
29.
MojoD., FischerC., & DegefaT. (2017). The determinants and economic impacts of membership in coffee farmer cooperatives: Recent evidence from rural Ethiopia. Journal of Rural Studies, 50, 84–94. https://doi.org/10.1016/j.jrurstud.2016.12.010
30.
MuyangaM., & JayneT. S. (2014). Effects of rising rural population density on smallholder agriculture in Kenya. Food Policy, 48, 98–113. https://doi.org/10.1016/j.foodpol.2014.03.001
31.
NSSO. (2013). All India Debt & Investment Survey: NSS 70th Round, Schedule 18.2. Ministry of Statistics and Programme Implementation, Government of India.
32.
NordjoR. E., & AdjasiC. K. (2020). The impact of credit on productivity of smallholder farmers in Ghana. Agricultural Finance Review, 80(1), 91–109. https://doi.org/10.1108/AFR-10-2018-0096
33.
OlagunjuF. I., & AdeyemoR. (2007). Determinants of repayment decision among small-holder’s farmers in Ogbomosho agricultural zone of Oyo state, Nigeria. Journal of Social Science, 4(5), 677–686.
34.
RamasamyP., & MalaiarasanU. (2023). Agricultural credit in India: Determinants and effects. Indian Economic Review, 58(1), 169–195. https://doi.org/10.1007/s41775-023-00187-8
35.
RegassaM. D., DegnetM. B., & MelesseM. B. (2023). Access to credit and heterogeneous effects on agricultural technology adoption: Evidence from large rural surveys in Ethiopia. Canadian Journal of Agricultural Economics, 71(2), 231–253. https://doi.org/10.1111/cjag.12329
36.
RosenbaumP. R., & RubinD. B. (1983). The central role of the propensity score in observational studies for causal effects. Biometrika, 70(1), 41–55. https://doi.org/10.1093/biomet/70.1.41
37.
SalimaW., ManjaL. P., ChiwaulaL. S., & ChirwaG. C. (2023). The impact of credit access on household food security in Malawi. Journal of Agriculture and Food Research, 11, 100490. https://doi.org/10.1016/j.jafr.2022.100490
38.
SekyiS., DomanbanP. B., & HonyaG. K. (2020). The impact of informal credit on rural agricultural productivity in the savannah ecological zone of Ghana. African Journal of Economic and Management Studies, 11(2), 301–315. https://doi.org/10.1108/AJEMS-03-2019-0121
39.
ShiferawB., KassieM., JaletaM., & YirgaC. (2014). Adoption of improved wheat varieties and impacts on household food security in Ethiopia. Food Policy, 44, 272–284. https://doi.org/10.1016/j.foodpol.2013.09.012
40.
ViceiszaA. C. (2016). Creating a lab in the field: Economics experiments for policymaking. Journal of Economic Surveys, 30(5), 835–854. https://doi.org/10.1111/joes.12118
41.
WossenT., AbdoulayeT., AleneA., HaileM. G., FelekeS., OlanrewajuA., & ManyongV. (2017). Impacts of extension access and cooperative membership on technology adoption and household welfare. Journal of Rural Studies, 54, 223–233. https://doi.org/10.1016/j.jrurstud.2017.06.022
