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Do credit constraints affect the technical efficiency of Boro rice growers? Evidence from the District Pabna in Bangladesh

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Abstract

This study analyzes the effects of credit constraints on technical efficiency of Boro rice growers in the district of Pabna in Bangladesh. Using a simple random sampling technique, the data was collected from 570 Boro rice growers from the Pabna district of Bangladesh. Before conducting a field survey, a theoretical model was designed to identify credit-constrained and non-constrained rice growers. We have analyzed the collected data in two phases: first, we investigated the technical efficiency of Boro rice growers using the stochastic frontier model (SFA); and second, we used an inefficiency effect model to estimate the influence of credit constraints on technical efficiency. Findings indicate that credit-constrained rice growers (CCRG) are 6.7% less technically efficient than credit non-constrained rice growers (CNRG). Findings further indicate that the education level of the household head, family size, certified seed, sowing time, access to extension services, off-farm income, and household savings have significant effects on the technical efficiency of both groups of rice growers. Furthermore, credit size has a significantly positive impact, whereas the interest rate imposed on the principal amount has a significantly negative impact.

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Acknowledgements

The authors are extremely thankful to the Professor Dr. Jianchao Luo, College of Economics and Management, Northwest A& F University, Yangling, Shaanxi, 712100, P. R. China, for providing necessary facilities during research work.

Funding

The study is supported by “Research on the Effectiveness Evaluation Risk Control and System Construction of the Agricultural Credit Guarantee Policy,” the National Natural Science Foundation of China (NSFC), January 2019–2022, No. 71873100. Sponsor and host: Jianchao Luo. This research is also supported by “Research on the Effect Evaluation, Operational Pattern, Supporting Policy of the contracted Management of Farmland Mortgage Finance,” The National Natural science Foundation of China (NSFC), Jan 2016–Dec 2019, No. 71573210. Sponsor and host Jianchao Luo.

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Contributions

MGR and LJC conceived and designed the research work; acquisition of data performed by FH and MGR; MGR, RR, MSH, KZH, and TS analyzed the data; MGR, YM, and AAK interpret the data; drafting the article by MGR, YM; MGR, MSH, RR, YM, and FH wrote and revised the manuscript; critical revision of the article conducted by LJC, FH, and YM. All authors have read and approved the final manuscript.

Corresponding author

Correspondence to Jianchao Luo.

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This is an observational study. We confirmed that no ethical approval is required.

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The authors declare no competing interests.

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Responsible Editor: Nicholas Apergis

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Appendix

Appendix

Table 4 Descriptive statistics of output and inputs variables used in SFA analysis
Table 5 Descriptive statistics of explanatory variables used in the inefficiency effects model

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Rabbany, M.G., Mehmood, Y., Hoque, F. et al. Do credit constraints affect the technical efficiency of Boro rice growers? Evidence from the District Pabna in Bangladesh. Environ Sci Pollut Res 29, 444–456 (2022). https://doi.org/10.1007/s11356-021-15458-1

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  • DOI: https://doi.org/10.1007/s11356-021-15458-1

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