Agricultural Credit and Its Impact on Agricultural Productivity: A Study on Rural Areas of Dhaka

Abstract

The agricultural sector has been regarded as the prime sector of the economy of Bangladesh since the industrial sector took its roots from this sector, and the service sector is also passively influenced by the agricultural sector. Besides its economic importance, this sector also has some social (i.e., food supply, nutrition demand fulfilment, rural employment) and environmental (i.e., influence on climate, biodiversity) contributions. In any developing country, economic and financial activities largely depend on smooth financial intermediation. Banks, as financial institutions, can play a vital role in this regard. Hence, Banks in Bangladesh can contribute to the economic development process through effective and efficient lending. In view of this sectoral importance, Bangladesh Bank has announced agricultural credit as a priority sector lending and mandatorily incorporated all scheduled banks to lend in this sector to increase agricultural productivity. The purpose of this study is threefold: i) Detect the nature of the farmers’ agricultural credit constraint status, explore the problems associated with access to banks’ agricultural credit and find the intensity of banks’ agricultural credit diversion to non-agricultural purposes. ii) Identify the determinants of constraint, access to credit and credit fungibility status. iii) Estimate the impact of constraint, access to credit and credit fungibility status on agricultural productivity. A filed level survey was conducted over five sub-districts of Dhaka. Four hundred sampled farmer’s data were collected through a structured, close-ended questionnaire. Collected data were further analyzed with STATA 14.2 software in both descriptive (i.e., cross-tabulation, ratio, mean and percentage) and analytical frameworks (i.e., probit regression model, propensity score matching model) The outcome of descriptive statistics stated the condition of constraint status, access problems and extent of fund diversion. The probit regression model identifies marital status, gender, risk perception, cooperative membership, land ownership deed, total owned land and distance to bank variables that are found statistically significant to explain the constraint status of the farmers. While education, household size, household labor, krishi card, past access to bank credit, the purpose of farming and bank account variables are found statistically significant to predict access vii to credit status. On the other hand, we have found that chronic diseases, delay in disbursement, old debt, non-fixed assets, and household size variables significantly influence credit fungibility status. Then paired t-test confirms several socio-economic differences exist between farmers' group, i.e., constraint and unconstraint, accessed and non-accessed, fungible and non-fungible. Results of the mean productivity confirm that unconstraint, accessed and non-fungible farmers' input use, production and income are significantly higher than the constraint, non-accessed and fungible farmers. Finally, PSM estimates revealed that the farmers' constraint and fungible status negatively impact input use, production and income. While the access status of the farmers positively affects input use, production and income. Bangladesh Bank, the central monetary authority of Bangladesh, annually issues Agricultural and Rural Credit Policies and Programs for scheduled banks in Bangladesh. The empirical findings of this research can contribute to the modification of the agricultural credit policy of Bangladesh Bank. Moreover, other research findings, suggestions and recommendations can also incrementally contribute to taking policy measures by different relevant stakeholders. The novelty of this study lies in using a very extensive, unique and newer data set to decompose the determinants of banks’ agricultural credit constraints, access and diversion issues and their corresponding impacts on agricultural productivity. In Bangladesh, to the best of our knowledge, no work has been done on farmers' formal agricultural credit’s different status determination and impact assessment issues based on micro-level data. Thus, we expect this evidence from Bangladesh can contribute incrementally to the existing literature.