Pakistan'da Mikro Kredi Katılımı ve Tarımsal Verimlilik: Finansal Okuryazarlık, Dijital Finans ve İklim Şoklarının Rolü

Öz

Mikrokredi, küçük ölçekli çiftçilerin karşılaştığı finansal kısıtlamaları hafifletmek için uzun zamandır önemli bir araç olarak önerilmektedir. Ancak tek başına tarımsal verimlilik üzerinde etkisinin olamayacağı da bir gerçektir. Bu çalışma, Pakistan'da mikrokrediye başvurmanın verimlilik üzerindeki etkisini, özellikle finansal okuryazarlık, dijital finans kullanımı ve iklim şoklarına maruz kalmanın bu sonuçları nasıl şekillendirdiğine odaklanmıştır. Çalışma Pencap'taki 384 küçük ölçekli çiftçiden toplanan birincil verilerden oluşmaktadır. Elde edilen veriler, mikrokredinin nedensel etkilerini tahmin etmek için eğilim puanı eşleştirme (PSM) analizi ve heterojen etkileri belirlemek için moderatörlü regresyon modelleri kullanılarak test edildi. Bulgular, mikrokredi katılımının ürün verimliliğinde önemli artışlarla ilişkili olduğunu, buğday ve pamuk verimlerinin sırasıyla yaklaşık %13 ve %16 arttığını göstermektedir. Bununla birlikte, bu kazanımlar çiftçiler arasında homojen değildir. Finansal okuryazarlık kritik bir faktör olarak ortaya çıkmakta olup, finansal olarak daha yetenekli çiftçiler krediden önemli ölçüde daha yüksek verimlilik kazanımları elde etmektedir. Benzer şekilde, dijital finansal hizmetlerin kullanımı, likidite yönetimini iyileştirerek, zamanında girdi alımlarını kolaylaştırarak ve işlem maliyetlerini azaltarak mikrokredinin etkinliğini artırmaktadır. Buna karşılık, iklim şoklarına maruz kalma bu faydaları önemli ölçüde zayıflatmakta, krediyle finanse edilen yatırımların getirisini azaltmakta ve tarımsal üretim sistemlerinin kırılganlığını vurgulamaktadır. Genel olarak, sonuçlar mikro kredinin etkinliğinin hem çiftçinin yeteneğine hem de çevresel riske büyük ölçüde bağlı olduğunu göstermektedir. Finansal okuryazarlığı, dijital finansı ve iklim kırılganlığını analize entegre ederek, bu çalışma tarımsal finansman ve kırsal kalkınma üzerine giderek artan literatüre katkıda bulunmaktadır. Bulgular, küçük ölçekli çiftçiler arasında sürdürülebilir verimlilik kazanımları elde etmek için kredi sağlamayı finansal eğitim, dijital kapsayıcılık ve iklime dayanıklı tarımsal uygulamalarla birleştiren entegre politika yaklaşımlarına duyulan ihtiyacın altını çizmektedir.

Anahtar Kelimeler

• Mikrokredi
• Tarımsal Verimlilik
• İklim değişikliği
• Finansal okuryazarlık
• Dijital finans

Etik Beyan

There is no need to obtain permission from the ethics committee for this study.

Microcredit Participation and Farm Productivity in Pakistan: The Role of Financial Literacy, Digital Finance and Climate Shocks

Öz

Microcredit has long been suggested as an important tool for alleviating the financial constraints faced by small-scale farmers. However, it is also true that it cannot have an impact on farm productivity on its own. This study examines the impact of microcredit participation on farm productivity among smallholder farmers in Pakistan and investigates the moderating roles of financial literacy, digital finance use, and climate shock exposure. Primary data were collected from 384 wheat and cotton farmers in Punjab and Sindh Provinces, the obtained data were analyzed using propensity score matching (PSM) to estimate the causal effects of microcredit, and moderated regression models to identify heterogeneous effects. The findings indicate that microcredit participation is associated with significant increases in crop productivity, with wheat and cotton yields rising by approximately 13% and 16%, respectively. The productivity gains are significantly larger among farmers with higher level of financial literacy and those utilizing digital financial services. In contrast, exposure to climate shocks significantly weakens these benefits, reducing the returns to credit-financed investments and highlighting the vulnerability of agricultural production systems. Overall, the results demonstrate that the effectiveness of microcredit is highly conditional on both farmer capability and environmental risk. By integrating financial literacy, digital finance, and climate vulnerability into the analysis, this study contributes to the growing literature on agricultural finance and rural development. The findings underscore the need for integrated policy approaches that combine credit provision with financial education, digital inclusion, and climate-resilient agricultural practices to achieve sustainable productivity gains among smallholder farmers.

Anahtar Kelimeler

• Microcredit
• Farm productivity
• Financial literacy
• Digital finance
• Climate shocks

Etik Beyan

There is no need to obtain permission from the ethics committee for this study.

Kaynakça

1. Abubakar, I. R., Bala, A. and Garba, S. B. (2019). Financial literacy and agricultural productivity: Empirical evidence from rural farmers in Nigeria. Journal of Development and Agricultural Economics, 11(9): 200–208.
2. Addison, M., Ohene-Yankyera, K. and Aidoo, R. (2020). Quantifying the impact of agricultural technology usage on intra-household time allocation: Empirical evidence from rice farmers in Ghana. Technology in Society, 63: 101434.
3. Angelucci, M., Karlan, D. and Zinman, J. (2015). Microcredit impacts: Evidence from a randomized microcredit program placement experiment by Compartamos Banco. American Economic Journal: Applied Economics, 7(1): 151-182.
4. Bakare, A. Y., Ogunleye, A. S. and Kehinde, A. D. (2023). Impacts of microcredit access on climate change adaptation strategies adoption and rice yield in Kwara State, Nigeria. World Development Sustainability, 2: 100047.
5. Banerjee, A., Duflo, E., Glennerster, R. and Kinnan, C. (2015a). The miracle of microfinance? Evidence from a randomized evaluation. American Economic Journal: Applied Economics, 7(1): 22–53.
6. Banerjee, A., Karlan, D. and Zinman, J. (2015b). Six randomized evaluations of microcredit: Introduction and further steps. American Economic Journal: Applied Economics, 7(1): 1–21.
7. Baptista, D., Spray, J. A., Unsal, F. and Unsal, M. F. D. (2023). Coping with Climate Shocks: Food Security in a Spatial Framework. International Monetary Fund-IMF Working Paper, 23/166.
8. Bauchet, J., Marshall, C., Starita, L., Thomas, J. and Yalouris, K. (2011). Latest Findings from Randomized Evaluations of Microfinance. CGAP Access to Finance Forum, no. 2 Washington, D. C., U. S. A. World Bank. http://documents.worldbank.org/curated/en/324001468329347456

9. Beck, R., Müller-Bloch, C. and King, J. L. (2018). Governance in the blockchain economy: A framework and research agenda. Journal of the Association for Information Systems, 19(10):1020-1034.
10. Beck, T., Demirgüç-Kunt, A. and Levine, R. (2009). Financial institutions and markets across countries and over time: Data and analysis. World Bank Economic Review, 24(1): 77–92.
11. Belton, B., Win, M. T., Zhang, X. and Filipski, M. (2021). The rapid rise of agricultural mechanization in Myanmar. Food Policy, 101:102095.
12. Bialowolski, P., Cwynar, A. and Weziak-Bialowolska, D. (2022). The role of financial literacy for financial resilience in middle-age and older adulthood. International Journal of Bank Marketing, 40(7): 1718-1748.
13. Bylander, M., Jacoby, L., Bradley, P. And Pérez, A. B. (2019). Over‐indebtedness and microcredit in Cambodia: Moving beyond borrower‐centric frames. Development Policy Review, 37: O140-O160.
14. Caliendo, M. and Kopeinig, S. (2008). Some practical guidance for the implementation of propensity score matching. Journal of Economic Surveys, 22(1): 31–72.
15. Carter, M. R., Laajaj, R. and Yang, D. (2018). Subsidies and the persistence of technology adoption: Field experimental evidence from Mozambique. Journal of Development Economics, 133: 1–16.
16. Carter, M. R., Little, P. D., Mogues, T. and Negatu, W. (2007). Poverty traps and natural disasters in Ethiopia and Honduras. World Development, 35(5): 835–856.
17. Chen, L., Pan, Y., Zhang, H., Chen, Y., Wang, C., Qiu, Z. and Chen, L. (2025). Propensity score matching analysis of valve-sparing versus aortic root replacement in type A aortic dissection patients. Nature Communications, 16(1): 1238.
18. Cochran, W.G. (1977). Sampling Techniques (3rdedition) John Wiley & Sons, New York, U. S. A.
19. Cole, S., Sampson, T. and Zia, B. (2011). Prices or knowledge? What drives demand for financial services in emerging markets? Journal of Finance, 66(6): 1933–1967.
20. Das, S., and Maji, S. K. (2023). Impact of financial literacy and financial confidence on the savings behaviour of the farmers: the Indian scene. Agricultural Finance Review, 83(4/5): 845-861.
21. Delaporte, I. and Maurel, M. (2018). Adaptation to Climate Change in Bangladesh. Climate policy, 18(1): 49-62.
22. Dercon, S. and Christiaensen, L. (2011). Consumption risk, technology adoption and poverty traps: Evidence from Ethiopia. Journal of Development Economics, 96(2): 159–173.
23. Feder, G., Lau, L. J., Lin, J. Y. and Luo, X. (1990). The relationship between credit and productivity in Chinese agriculture: A microeconomic model of disequilibrium. American Journal of Agricultural Economics, 72(5): 1151-1157.
24. Field, E., Pande, R., Papp, J. and Rigol, N. (2013). Does the classic microfinance model discourage entrepreneurship among the poor? Experimental evidence from India. American Economic Review, 103(6): 2196–2226.
25. Giné, X. (2011). Access to capital in rural Thailand: An estimated model of formal vs. informal credit. Journal of Development Economics, 96(1): 16-29.
26. Giné, X. and Klonner, S. (2005). Credit Constraints as a Barrier to Technology Adoption by the Poor: Lessons from South-Indian Small-Scale Fishery. World Bank Policy Research Working Paper, No. 3665.
27. Ginting, A., Purba, E., Chalil, D. and Hanafi, N. D. (2026). Unraveling farmer empowerment: The role of socioeconomic and institutional factors in sustainable agriculture. Journal of Tekirdag Agricultural Faculty, 23(1): 169-186.
28. Grohmann, A., Klühs, T. and Menkhoff, L. (2018). Does financial literacy improve financial inclusion? Cross country evidence. World Development, 111: 84-96.
29. Guiso, L., Sapienza, P. and Zingales, L. (2004). The role of social capital in financial development. American Economic Review, 94(3): 526-556.
30. Hill, R. V. and Viceisza, A. (2012). A field experiment on the impact of weather shocks and insurance on risky investment. Experimental Economics, 15(2): 341–371.
31. Hussain, J., Ali, M. and Ahmad, Z. (2023). Financial literacy and farmers' access to credit: Evidence from rural Pakistan. Journal of Rural Studies, 98, 102–112.
32. Idrees, M., Junaid, Z. B., Irfan, M., Hassan, S. M., Mahmud, S. and Nazir, A. (2025). Digital technologies in maritime sector: enhancing efficiency, safety, and environmental sustainability. Spectrum of Engineering Sciences, 3(12): 726-741.
33. Imai, K. S., Gaiha, R., Thapa, G. and Annim, S. K. (2010). Microfinance and poverty—a macro perspective. World Development, 38(4): 533–541.
34. Islam, A. and Maitra, P. (2012). Health shocks and consumption smoothing in rural households: Does microcredit have a role to play? Journal of Development Economics, 97(2): 232–243.
35. Islam, A., Nguyen, C. and Smyth, R. (2015). Does microfinance change informal lending in village economies? Evidence from Bangladesh. Journal of Banking & Finance, 50: 141–156.
36. Jack, W. and Suri, T. (2014). Risk sharing and transactions costs: Evidence from Kenya's mobile money revolution. American Economic Review, 104(1): 183–223.
37. Jimi, N. A., Kassie, M. and Marenya, P. P. (2020). The impacts of credit access on farm productivity: Evidence from Malawi. World Development, 136: 105123.
38. Kandie, D. and Islam, K. J. (2022). A new era of microfinance: The digital microcredit and its impact on poverty. Journal of International Development, 34(3): 469-492.
39. Kar, S. (2018) Financializing Poverty: Labor and Risk in Indian Microfinance. Stanford, CA: Stanford University Press, U. S. A.
40. Karlan, D. and Morduch, J. (2010). Access to Finance. In: Handbook of Development Economics, Vol. 5, Ed(s): Rodrik, D. and Rosenzweig, M., Elsevier.
41. Karlan, D. and Zinman, J. (2011). Microcredit in theory and practice: Using randomized credit scoring for impact evaluation. Science, 332(6035): 1278–1284.
42. Karlan, D., Ratan, A. L. and Zinman, J. (2014). Savings by and for the poor: A research review and agenda. Review of Income and Wealth, 60(1): 36–78.
43. Khan, A. R., Ullah, A. and Jan, A. (2020). Does microfinance enhance agricultural productivity? Evidence from Khyber Pakhtunkhwa, Pakistan. Sarhad Journal of Agriculture, 36(2): 641–650.
44. Khandker, S. R. and Samad, H. A. (2014). Dynamic effects of microcredit in Bangladesh. World Bank Economic Review, 28(3): 529–548.
45. Kim, M. and Duvendack, M. (2025). Digital credit for all? An empirical analysis of mobile loans for financial inclusion in Kenya. Information Technology for Development, 31(3): 559-576.
46. Kipkogei, S., Han, J., Mwalupaso, G., Tanui, J. and Brenya, R. (2025). The synergistic effects of microcredit access and agricultural technology adoption on maize farmer’s income in Kenya. PLoS One, 20(1): e0316014.
47. Kolapo, A. and Didunyemi, A. J. (2024). Effects of exposure on adoption of agricultural smartphone apps among smallholder farmers in Southwest, Nigeria: implications on farm-level-efficiency. Agriculture & Food Security, 13(1): 31.
48. Kou, M., Yang, Y. and Chen, K. (2020). The impact of external R&D financing on innovation process from a supply-demand perspective. Economic Modelling, 92: 375-387.
49. Lane, G. (2024). Adapting to climate risk with guaranteed credit: Evidence from Bangladesh. Econometrica, 92(2): 355-386.
50. Li, X., Liu, J. and Huo, X. (2021). Impacts of tenure security and market-oriented allocation of farmland on agricultural productivity: Evidence from China’s apple growers. Land Use Policy, 102: 105233.
51. Lusardi, A. and Mitchell, O. S. (2014). The economic importance of financial literacy: Theory and evidence. American Economic Journal: Journal of Economic Literature, 52(1): 5-44.
52. Lusardi, A., Michaud, P. C. and Mitchell, O. S. (2020). Assessing the impact of financial education programs: A quantitative model. Economics of Education Review, 78: 101899.
53. Maji, S. K. and Laha, A. (2023). Financial literacy and its antecedents amongst the farmers: evidence from India. Agricultural Finance Review, 83(1): 124-143.
54. Mukaila, R. (2024). Microcredit via digital innovation platforms: its drivers and impact on fish farms' yield and income in Nigeria. Agricultural Finance Review, 84(4/5): 342-365.
55. Munyegera, G. K. and Matsumoto, T. (2018). ICT for financial access: Mobile money and the financial behavior of rural households in Uganda. Review of Development Economics, 22(1): 45-66.
56. Namayengo, F. M. M., Antonides, G. and Van Ophem, J. (2025). Impact of microcredit on performance of women‐owned non‐farm microenterprises. Review of Development Economics, 29(3): 1940-1951.
57. Nunnally, J. C. (1978). An Overview of Psychological Measurement. Clinical Diagnosis of Mental Disorders: A Handbook, Springer, Boston, U. S. A., 97-146.
58. Nuruzzaman, A. K. M., Graham, S. and Barnett, J. (2025). Reducing social vulnerability to climate change: the role of microfinance organisations. Climate Policy, 25(1): 44-58.
59. Oduntan, O. (2025). Evaluating the total factor productivity of smallholder cassava farmers based on socio-economic variables, cost and revenue in Southwest, Nigeria. Journal of Tekirdag Agricultural Faculty, 22(3): 693-703.
60. Ogunleye, A., Kehinde, A., Ogundeji, A. and Orimogunje, R. (2024). Does microcredit have any impact on profit efficiency? Evidence from smallholder poultry farmers in Nigeria. Environment, Development and Sustainability, 27: 13611–13637.
61. Phan, C. T., Vo, T. T. and Vo, D. T. H. (2023). Can microcredit reduce vulnerability to poverty? Evidence from rural Vietnam. Review of Development Economics, 27(1): 608-629.
62. Rahim, A., Tanggamani, V., Bani, H. and Alias, N. A. (2024). Microcredit clients’ financial literacy towards financial inclusion and sustainability. Information Management and Business Review, 16(1): 274-278.
63. Rayhan, S. J., Rahman, M. S. and Lyu, K. (2023). The role of rural credit in agricultural technology adoption: The case of Boro rice farming in Bangladesh. Agriculture, 13(12): 2179.
64. Raza, A., Tong, G., Sikandar, F., Erokhin, V. and Tong, Z. (2023). Financial literacy and credit accessibility of rice farmers in Pakistan: Analysis for Central Punjab and Khyber Pakhtunkhwa regions. Sustainability, 15(4): 2963.
65. Rosenbaum, P. R. (2002). Observational Studies. Springer Series in Statistics. 2nd Edition, Springer-Verlag, New York, U. S. A.
66. Rosenbaum, P. R. and Rubin, D. B. (1983). The central role of the propensity score in observational studies for causal effects. Biometrika, 70(1): 41-55.
67. Sahu, T. N., Agarwala, V. and Maity, S. (2024). Effectiveness of microcredit in employment generation and livelihood transformation of tribal women entrepreneurs: evidence from PMMY. Journal of Small Business & Entrepreneurship, 36(1): 53-74.
68. Shah, N. A. and Zaidi, A. (2023). Digital financial inclusion: Evidence from Pakistan’s fintech sector. Journal of Financial Services Marketing, 28(3): 112–125.
69. Song, K., Tang, Y., Zang, D., Guo, H. and Kong, W. (2022). Does digital finance increase relatively large-scale farmers’ agricultural income through the allocation of production factors? Evidence from China. Agriculture, 12(11): 1915.
70. Stiglitz, J. E. and Weiss, A. (1981). Credit rationing in markets with imperfect information. American Economic Review, 71(3):393-410.
71. Ullah, A., Verner, V., Madaki, M. Y., Adams, F. and Bavorova, M. (2024). Factors influencing informal credit access and utilization among smallholder farmers: insights from Mountainous Regions of Pakistan. Agriculture, 14(10): 1764.
72. World Bank Report (2012). ICT for Greater Development Impact: World Bank Group Strategy for Information and Communication Technology; World Bank: Washington, DC, USA, Available online: https://openknowledge.worldbank.org/bitstream/handle/10986/
73. Xu, D., Peng, L., Liu, S., Su, C., Wang, X. and Chen, T. (2017). Influences of sense of place on farming households’ relocation willingness in areas threatened by geological disasters: Evidence from China. International Journal of Disaster Risk Science, 8(1):16-32.
74. Younas, M., Khan, M. and Khalid, R. (2024). Climate shocks, adaptive capacity, and agricultural productivity in Pakistan. Climate and Development, 16(1): 43–56.
75. Yu, Y., Wang, F., Qin, G. and Li, T. (2025). How does targeted microcredit empower the economic resilience of rural households in the context of natural disasters? Frontiers in Sustainable Food Systems, 9: 1582487.
76. Zhai, S., Peng, C. and Sheng, Y. (2023). Assessing the impact of digital financial inclusion on agricultural total factor productivity in China. International Food and Agribusiness Management Review, 26(3): 519-534.