Does Financial Inclusion Influence Economic Efficiency of Rice Farming? Evidence from Ogun State, Nigeria

doi:10.1016/j.rsci.2024.10.001

Abstract

Shakirat B. Ibrahim, Raheem O. Aminu, Aisha O. Arowolo, Opeyemi O. Okanlawon, Afeez A. Adegbola. Does Financial Inclusion Influence Economic Efficiency of Rice Farming? Evidence from Ogun State, Nigeria[J]. Rice Science, 2024, 31(6): 638-642.

Figures/Tables 3

References 31

[1]	Abdisa T, Mehare A, Wakeyo M B. 2024. Analyzing gender gap in agricultural productivity: Evidence from Ethiopia. J Agric Food Res, 15: 100960.
[2]	Abiola M O, Omhonlehin R A, Sani T P. 2021. Technical efficiency of rice production in North Central. Nat Volat Essent Oils, 8(6): 4546-4561.
[3]	Aboaba K. 2020. Economic efficiency of rice farming: A stochastic frontier analysis approach. J Agribus Rural Dev, 58(4): 423-435.
[4]	Abraham T W. 2018. Estimating the effects of financial access on poor farmers in rural northern Nigeria. Financ Innov, 4(1): 25.
[5]	Akite I, Okello D M, Kasharu A, Mugonola B. 2022. Estimation of profit efficiency of smallholder rice farmers in Uganda: A stochastic frontier approach. J Agric Food Res, 8: 100315.
[6]	Alabi O O, Safugha G F, Aluwong J S. 2023. Cost efficiency and profitability analysis of rice (Oryza sativa) production among smallholder farmers in Federal Capital Territory, Nigeria. Aust J Sci Technol, 7(1): 1-9.
[7]	Arowolo A O, Ibrahim S B, Aminu R O, Olanrewaju A E, Ashimiu S M, Kadiri O J. 2022. Effect of financial inclusion on livelihood diversification among smallholder farming households in Oyo State, Nigeria. Niger Agric J, 51(3): 67-75.
[8]	Battese G E, Coelli T J. 1988. Prediction of firm-level technical efficiencies with a generalized frontier production function and panel data. J Econom, 38(3): 387-399.
[9]	Chikezie C, Benchendo G N, Ibeagwa O B, Oshaji I O, Onuzulu O A. 2020. Analysis of technical efficiency among rice farmers in Ebonyi State of Nigeria: A stochastic frontier approach. J Agric Food Sci, 18(1): 40-49.
[10]	Dery I. 2016. Access to and control over land as gendered: Contextualising women’s access and ownership rights of land in rural Ghana. Afric J Dev Stud, 45(2): 28-48.
[11]	EFInA. 2021. Access to financial services in Nigeria survey 2020. [2023-12-19]. https://efina.org.ng/wp-content/uploads/2021/10/A2F-2020-Final-Report.pdf.
[12]	FAOSTAT. 2023. Rice production quantity, crops and livestock products. [2023-12-19]. https://www.fao.org/faostat/en/#data/QCL.
[13]	FMARD. 2023. National Rice Development Strategy II (2020-2030). [2023-12-19]. https://riceforafrica.net/wp-content/uploads/2022/02/ nigeria_nrds2.pdf.
[14]	Fowowe B. 2020. The effects of financial inclusion on agricultural productivity in Nigeria. J Econ Dev, 22(1): 61-79.
[15]	Houngue V, Nonvide G M A. 2020. Estimation and determinants of efficiency among rice farmers in Benin. Cogent Food Agric, 6(1): 1819004.
[16]	Ibrahim S B, Aminu R O, Arowolo A O, Oyedele A M. 2023. Effects of financial inclusion on ownership of productive assets among Cassava Processors in Oyo State, Nigeria. Niger Agric J, 54(1): 11-19.
[17]	Kamara A Y, Kamai N, Omoigui L O, Togola A, Ekeleme F, Onyibe J E. 2020. Guide to Maize Production in Northern Nigeria. Ibadan, Nigeria: International Institute of Tropical Agriculture.
[18]	Kara A H, Shamsudin M N, Mohamed Z, Latiff I B, Seng K W K. 2019. Technical efficiency and production risk of rice farms under anchor borrowers programme in kebbi state, Nigeria. Asian J Agric Ext Econ Sociol, DOI: 10.9734/ajaees/2019/v31i430141.
[19]	Kodde D A, Palm F C. 1986. Wald criteria for jointly testing equality and inequality restrictions. Econometrica, 54(5): 1243-1248.
[20]	KPMG. 2019. Rice industry review. [2023-12-19]. https://assets.kpmg.com/content/dam/kpmg/ng/pdf/audit/rice-industry-review.pdf.
[21]	Linn T, Maenhout B. 2019. Measuring the efficiency of rice production in Myanmar using data envelopment analysis. Asian J Agric Dev, 16(2): 1-24.
[22]	Masuku M M, Mthembu Z, Mlambo V H. 2023. Gendered effects of land access and ownership on food security in rural settings in South Africa. Front Sustain Food Syst, 7: 1158946.
[23]	Mdoda L, Christian M, Agbugba I. 2024. Use of information systems (mobile phone app) for enhancing smallholder farmers’ productivity in eastern cape province, South Africa: Implications on food security. J Knowl Econ, 15(1): 1993-2009.
[24]	Mohammed F, Barrowclough M J, Kibler M L, Boerngen M A. 2020. Measuring usage of formal financial services as a proxy for financial inclusion. Agric Finance Rev, 80(4): 471-489.
[25]	Obianefo C A, Ng’ombe J N, Mzyece A, Masasi B, Obiekwe N J, Anumudu O O. 2021. Technical efficiency and technological gaps of rice production in anambra state, Nigeria. Agriculture, 11(12): 1240.
[26]	Ojo T O, Ogundeji A A, Babu S C, Alimi T. 2020. Estimating financing gaps in rice production in Southwestern Nigeria. J Econ Struct, 9(1): 12.
[27]	Okello D M, Bonabana-Wabbi J, Mugonola B. 2019. Farm level allocative efficiency of rice production in Gulu and Amuru districts, Northern Uganda. Agric Food Econ, 7(1): 19.
[28]	Oseghale A I. 2022. Effect of agrochemical use on rice farmers health in Niger and Ogun States, Nigeria. J Trop Agric, 59(2): 145-154.
[29]	Sudrajat I S, Rahayu E S, Supriyadi, Kusnandar. 2018. Effect of Institution on Production Cost Efficiency of Organic Rice Farming in Indonesia. DLSU Bus Econ Rev, 28(1): 166-175.
[30]	Tesema T. 2021. Determinants of allocative and economic efficiency in crop-livestock integration in western part of Ethiopia evidence from Horro district: Data envelopment approach. Heliyon, 7(7): e07390.
[31]	Udoka C O, Mbat P D O, Duke S B. 2016. The effect of Commercial Banks’ Credit on agricultural production in Nigeria. J Financ Account, 4(1): 1-10.

Variable	Definition	Mean	Standard deviation	Minimum	Maximum
Socio-economic characteristics
Age (year)	Farmer’s age in years	57.3	10.63	42	83
Gender	Dummy for gender of the farmer (1, Male; 0, Female)	0.95	0.22	0	1
Household size	Number of persons living in the household	4.98	1.94	2	10
Education (year)	Years of formal education of the farmer	6.85	2.89	0	12
Marital status	Dummy for marital status of the farmer (1, Married; 0, Otherwise)	0.63	0.48	0	1
Extension service	Dummy for farmer’s access to extension service (1, Yes; 0, Otherwise)	0.48	0.50	0	1
Farming experience (year)	Years of farming experience	19.13	13.42	0	50
Financial inclusion indicator
Ownership of bank account	Dummy for ownership of a bank account (1, Yes; 0, Otherwise)	0.52	0.50	0	1
Save money in the bank	Dummy for saving money in the bank (1, Yes; 0, Otherwise )	0.79	0.41	0	1
Credit access	Dummy for having access to credit (1, Farmer has access to credit; 0, Otherwise)	0.83	0.37	0	1

Variable	Definition	Mean	Standard deviation	Minimum	Maximum
Socio-economic characteristics
Age (year)	Farmer’s age in years	57.3	10.63	42	83
Gender	Dummy for gender of the farmer (1, Male; 0, Female)	0.95	0.22	0	1
Household size	Number of persons living in the household	4.98	1.94	2	10
Education (year)	Years of formal education of the farmer	6.85	2.89	0	12
Marital status	Dummy for marital status of the farmer (1, Married; 0, Otherwise)	0.63	0.48	0	1
Extension service	Dummy for farmer’s access to extension service (1, Yes; 0, Otherwise)	0.48	0.50	0	1
Farming experience (year)	Years of farming experience	19.13	13.42	0	50
Financial inclusion indicator
Ownership of bank account	Dummy for ownership of a bank account (1, Yes; 0, Otherwise)	0.52	0.50	0	1
Save money in the bank	Dummy for saving money in the bank (1, Yes; 0, Otherwise )	0.79	0.41	0	1
Credit access	Dummy for having access to credit (1, Farmer has access to credit; 0, Otherwise)	0.83	0.37	0	1

Cost function
	Variable	Coefficient	z value
	Land cost	0.1156*** (0.0069)	16.53
	Fertiliser cost	0.0363*** (0.0069)	5.24
	Insecticide cost	0.0632*** (0.0243)	2.69
	Herbicide cost	0.0238 (0.0191)	1.25
	Labour cost	0.0133 (0.0300)	0.44
	Output (kg)	0.1399*** (0.0455)	3.08
	Constant	8.4052*** (0.2515)	33.42
Inefficiency function
	Inefficiency determinant	Average marginal effect	z value
	Age	0.0209***	3.03
	Gender (Base category: Female)
	Male	-0.3967**	-2.32
	Household size	0.0166	0.76
	Years of education	-0.0417**	-2.16
	Marital status (Base category: Married)
	Single	0.0157	0.16
	Access to extension service	-0.2727***	-2.48
	Years of farming experience	-0.0039	-1.19
	Ownership of bank account	-0.3375***	-2.49
	Save money in the bank	-0.1613	-1.44
	Credit access	-0.3289**	-2.26
	U. Sigma
	Constant	-0.1984 (0.3552)	-0.56
	V. Sigma
	Constant	-2.5999*** (0.2813)	-9.24
	Sigma_u	0.9056*** (0.1608)	5.63
	Sigma_v	0.2725*** (0.0383)	7.11
	Lambda	3.3228*** (0.1641)	20.24
	Number of observations	240
	Wald Chi-square (6)	617.02
	Log-likelihood	-174.175
	Prob > Chi-square	0.0000
	Overall mean economic efficiency (%)	61.83
	Likelihood Ratio test of inefficiency	98.488

Cost function
	Variable	Coefficient	z value
	Land cost	0.1156*** (0.0069)	16.53
	Fertiliser cost	0.0363*** (0.0069)	5.24
	Insecticide cost	0.0632*** (0.0243)	2.69
	Herbicide cost	0.0238 (0.0191)	1.25
	Labour cost	0.0133 (0.0300)	0.44
	Output (kg)	0.1399*** (0.0455)	3.08
	Constant	8.4052*** (0.2515)	33.42
Inefficiency function
	Inefficiency determinant	Average marginal effect	z value
	Age	0.0209***	3.03
	Gender (Base category: Female)
	Male	-0.3967**	-2.32
	Household size	0.0166	0.76
	Years of education	-0.0417**	-2.16
	Marital status (Base category: Married)
	Single	0.0157	0.16
	Access to extension service	-0.2727***	-2.48
	Years of farming experience	-0.0039	-1.19
	Ownership of bank account	-0.3375***	-2.49
	Save money in the bank	-0.1613	-1.44
	Credit access	-0.3289**	-2.26
	U. Sigma
	Constant	-0.1984 (0.3552)	-0.56
	V. Sigma
	Constant	-2.5999*** (0.2813)	-9.24
	Sigma_u	0.9056*** (0.1608)	5.63
	Sigma_v	0.2725*** (0.0383)	7.11
	Lambda	3.3228*** (0.1641)	20.24
	Number of observations	240
	Wald Chi-square (6)	617.02
	Log-likelihood	-174.175
	Prob > Chi-square	0.0000
	Overall mean economic efficiency (%)	61.83
	Likelihood Ratio test of inefficiency	98.488

Efficiency category	Frequency	Percentage (%)
0 to 29%	34	14.17
30% to 49%	36	15.00
50% to 69%	54	22.50
70% to 89%	106	44.17
90% to 100%	10	4.17
Total	240	100.00
Mean (%)	62
Minimum (%)	6
Maximum (%)	92

Does Financial Inclusion Influence Economic Efficiency of Rice Farming? Evidence from Ogun State, Nigeria

RichHTML

PDF

Knowledge

Abstract

Cite this article

share this article

Figures/Tables 3

References 31

Related Articles 0

Recommended Articles

Metrics