PL EN


Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników
2021 | z. 1 (59) | 29--38
Tytuł artykułu

Determinants of Agricultural Loan Decision Making Process for Rice (Oryza sativa) Farmers in Abuja, Nigeria. Applications of Heckman Two-Stage Model and Factor Analysis

Treść / Zawartość
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
This study focuses on determinants of the agricultural loan decision-making process of rice (Oryza sativa) farmers in Abuja, Nigeria, using the Heckman two-stage model and factor analysis. This study was designed specifically to achieve the following objectives: determine the socio-economic profiles or characteristics of rice farmers, analyze the costs and returns of rice production, evaluate factors influencing rice farmers' decision to obtain an agricultural loan, evaluate socio-economic factors influencing the amount of the agricultural loan, and determine the constraints or problems facing rice farmers. A multi-stage sampling design was employed. A total sample of one hundred (100) rice farmers was included, and primary data were utilized. Data were obtained through the use of a well-structured and well-designed questionnaire. Statistical and econometric tools used in analyzing data included descriptive statistics, gross margin analysis, financial analysis, the Heckman two-stage model, and principal component analysis. The results show that 63% of rice farmers were between the age of 31-50 years. The mean age was 41.90 years. About 65% of rice farmers were male, and 54% of them were married. Also, 93% of rice farmers had formal education and were literate. The household sizes were large, with an average of six persons per household. An average of 71,550 nairas was the loan amount granted to rice farmers by financial institutions. The average farm size amounted to 1.49 hectares. Factors influencing the decision of rice farmers to obtain agricultural loan included age (P < 0.01), marital status (P < 0.05), household size (P < 0.10), educational level (P < 0.05), farm size (P < 0.05), farm and non-farm income (P < 0.10), farm experience (P < 0.05), collateral property (P < 0.05), extension services (P < 0.10), and awareness of loan or credit facilities (P < 0.05). Rice production was profitable with a net farm income of 744,300 nairas. The gross margin ratio of 0.95 means that 95 kobos covered profits, taxes, expenses, interest, and depreciation for every naira invested in rice production activities. Socio-economic factors statistically and significantly influencing the amount of agricultural loan obtained by rice farmers included (P < 0.05) sex (P < 0.01), household size (P < 0.05) and educational level (P < 0.01). The constraints facing rice farmers in obtaining the agricultural loan and production activities included lack of collateral property, lack of fertilizer input, poor-quality feeder roads, lack of credit facilities, inadequate labor input, and complicated and costly administrative procedures to obtain a loan. It is recommended that agricultural loans be made available to rice farmers in sufficient amounts and at low-interest rates. Also, farm inputs, fertilizer inputs, improved seeds, and chemicals should be made available to rice farmers. (original abstract)
Słowa kluczowe
Rocznik
Numer
Strony
29--38
Opis fizyczny
Twórcy
  • University of Abuja, Nigeria
  • Forestry Research Institute of Nigeria, Nigeria
  • Forestry Research Institute of Nigeria, Nigeria
Bibliografia
  • Agbogo, E.A., Uduoso, A.B., Tiku, E.N. (2013). Analysis of Factors Affecting Rice Consumption in Cross River State, Nigeria. J. Agric. Vet. Sci., 4(2), 34-40.
  • Alabi, O.O., Lawal, A.F., Chiogor, H.O. (2016). Access to Formal Credit Facilities among Smallscale Crop Farmers in Gwagwalada Area Council, Abuja, Nigeria. Russ. J. Agric. Soc.-Econ. Sci., 1(49), 57-66.
  • Alabi, O.O., Oladele, A.O., Oladele, N.O. (2020). Socio-Economic Factors Influencing Perceptions and Adaptability of Rural Rice Farmers to Climate Change, Abuja, Nigeria: Applications of Heckman Two - Stage Model. Russ. J. Agric. Soc.-Econ. Sci., 8(104), 45-56.
  • Alabi, O.O., Adebayo, O., Akinyemi, A., Apene, E. (2004). Sources and Accessibility of Credit to Rural Women in Chikun Local Government Area of Kaduna State. Int. J. Econ. Dev. Iss. 4(1 & 2), 106-113.
  • Alabi, O.O. (2008). Impact of Microcredit Scheme of Nigerian Agricultural Cooperative and Rural Development Bank on Annual Crop Farmers in Bakori Local Government Area of Katsina State. Int. J. Sust. Tropic. Agric. Res., 28, 22-26.
  • Bamiro, O.M., Otunaiya, A.O., Idowu, A.O. (2012). Economics of Horizontal Integration in Poultry Industry in South West Nigeria. Int. J. Poul. Sci., 11, 39-46.
  • Bashir, M.K., Mehmood, Y., Hassan, S. (2010). Impact of Agricultural Credit on Productivity of Wheat Crop: Evidence from Lahore, Punjab, Pakistan. Pak. J. Agric. Sci., 47(4), 405-409.
  • Ben-Chendo, G.N., Lawal, N., Osuji, M.N., Osugiri, I.I., Ibeagwa, B.O. (2015). Cost and Returns of Paddy Rice Production in Kaduna State of Nigeria. Int. J. Agric. Market., 2(5), 084-089.
  • Eboh, E.C., Nwafor, M., Chukwu, J.O., Amuka, J.I. (2011). Cost-Effective Agriculture Growth Options for Poverty Reduction in Nigeria: Evidence and Policy Implications. African Institute for Applied Economics, Research Paper 6.
  • Essien, U.A., Arene, C.J., Nweje, N.J. (2013). What Determine the Frequency of Loan Demand in Credit Markets among Agro Based Enterprises in the Niger Delta Region of Nigeria? An Empirical Analysis.
  • Ettah, O.I., Ebu, B.O. (2018). Determinants of Agricultural Loan Access from Formal Sources in Cross River State Central Agricultural Zone, Nigeria. Int. J. Research-GRANTH., 6(5), 1-8.
  • FAOSTAT (2005). Food and Agricultural Organization. Statistical Data Base. Rome: FAO.
  • FMARD (Federal Ministry of Agriculture and Rural Development). (2014). Report of the 2013 Wet Season Farm Output/Agricultural Production Survey (APS).
  • Fikadu, G.F. (2016). Determinants of Access to Credit and Credit Sources Choice by Micro, Small and Medium Enterprises in Nekemte, Ethiopia. Int. J. Afr. Asian Stud., 28, 11-27.
  • IRRI (International Rice Research Institute). (2001). Report 2001.
  • Isibor, A.C., Nkamigbo, D.C. (2019). Economic Determinants of Loan Repayment to Large and Smallscale Farmers Beneficiaries of Bank of Agriculture Loans from 2010-2016 in Anambra State, Nigeria. Int. J. Agric. Pol. Res., 7(4), 91-99.
  • Lawal, A.F., Alabi, O.O. (2011). Factors Affecting Adoption of New Rice For Africa (NERICA) and Complimentary Technology in Southern Guinea Savannah, Niger State, Nigeria. Int. J. Agric. Dev. Econ. (IJADE), 1(2), 121-128.
  • Nimoh, F., Tham-Agyekum, E.K., Awuku, M.S. (2013). Factors Influencing Access of Poultry Farmers to Credit: The Case of the Agricultural Development Bank (ADB) in Ga East Municipal, Ghana. Management, 3(1), 54-58
  • Nkamigbo, D.C., Ugwumba, C.O.A., Okeke, U. (2009). Market Structure, Conduct, and Volume of Trade among Channels of Watermelon Marketing in Anambra State, Nigeria. Int. J. Agric. Biosci., 8(2), 112-116.
  • NPC (2006). National Population Commission of Nigeria, Population Census 2006.
  • Nwaru, J.C. (2011). Determinants of Informal Credit Demand and Supply among Food Crops. Farmers in Akwa Ibom State, Nigeria. J. Rural Comm. Dev., 13(1), 200-211.
  • Olagunju, F.I., Adeyemo, R. (2007). Determinants of Repayment Decision among Smallholder Farmers in Southwest Nigeria. Pak. J. Soc. Sci., 4(5), 677-686.
  • Olukosi, J.O., Erhabor, P.O. (2005). Introduction to Farm Management Economics: Principles and Applications (pp. 77-83). Zaria, Kaduna, Nigeria: Agitab Publishers Limited.
  • Otunaiya, A.O., Ologbon, O.A.C., Akerele, E.O. (2014). Analysis of Agricultural Loan Use Decision among Poultry Farmers in Oyo State, Nigeria. Inte. J. Poul. Sci., 13(2), 108-113.
  • Saboor, A., Hussaini, A., Taqi, M. (2014). Impact of Agricultural Credit on Agricultural Productivity in Pakistan: An Empirical Analysis. Int. J. Adv. Res. Manag. Soc. Sci., 3(4), 125-139.
  • Saqib, S.E., Kuwornu, J.K.M., Panezia, S., Ali, U. (2018). Factors Determining Subsistence Farmers' Access to Agricultural Credit in Flood-Prone Areas of Pakistan. Kaset. J. Soc. Sci., 39, 262-268.
Typ dokumentu
Bibliografia
Identyfikatory
Identyfikator YADDA
bwmeta1.element.ekon-element-000171631400

Zgłoszenie zostało wysłane

Zgłoszenie zostało wysłane

Musisz być zalogowany aby pisać komentarze.
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.