@article{10.11648/j.ijae.20230804.11,
  author = {M’Muruku Salesio Miriti and Mwirigi Rael Nkatha and Gathungu Geofrey Kingori},
  title = {Lender Behavioural Characteristics Affecting Agribusiness Loans Default Rate in Agricultural Finance Corporation, Mount Kenya Region},
  journal = {International Journal of Agricultural Economics},
  volume = {8},
  number = {4},
  pages = {122-132},
  doi = {10.11648/j.ijae.20230804.11},
  url = {https://doi.org/10.11648/j.ijae.20230804.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijae.20230804.11},
  abstract = {Farming communities who borrow agribusiness credit from Agricultural Finance Corporation (AFC) require efficient access to credit. Lender behaviour and decisions exhibited in credit supply dynamics influence agribusiness loan default rate. Mount Kenya region has registered a high default rate of 20.33% compared to a standard of 10% for all types of loans in Kenya. Using descriptive research design this, study sought to assess the effect of lender behavioural characteristics on agribusiness loans default rate in the region’s 11 branches and a population of 3,002 agribusiness borrowers. Systematic random sampling technique with an interval of 10 was used to sample 300 respondents. Primary data on lender behavioural characteristics was collected using a structured questionnaire. Statistical Packages for Social Sciences (SPSS V.27) and Stata version 15 were used to analyse data. To estimate the effect of variables in predicting default rate, regression analysis was used. In obtainment of the F-statistic for measuring the adequacy of the regression model, ANOVA was performed. Probit regression model was used to specify the statistical relationship between the variables. The four indicators used in the model explicated 48.80% of the dependent variable. Lender behavioural characteristics that were considered in the study had significantly affected AFC loan default rate at 1% level. The p-values of the pointers of lender behavioural characteristics for farm visit, disbursement timeliness, political lending and adequate funding (0.003,0.000,0.000,0.000) respectively were less than the p-value of 0.01. The negative coefficient (-0.355) of farm visit meant that lenders effort in visiting farmers would reduce default rate in AFC loans. However, the coefficient of disbursement timeliness, political lending and adequate funding had a positive coefficient implying a negative effect that increased AFC loans default rate. To mitigate default, credit officers need to disburse adequate loan expeditiously, refuse to yield to political interference and adhere to stipulations of lending policy. The study recommends that AFC should adequately and timely fund supervised borrower projects and own those projects by extending advisory and training inputs even as they embrace a neutral working environment that is free from political manipulation, compromise and influence.},
 year = {2023}
}

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TY  - JOUR
T1  - Lender Behavioural Characteristics Affecting Agribusiness Loans Default Rate in Agricultural Finance Corporation, Mount Kenya Region
AU  - M’Muruku Salesio Miriti
AU  - Mwirigi Rael Nkatha
AU  - Gathungu Geofrey Kingori
Y1  - 2023/07/06
PY  - 2023
N1  - https://doi.org/10.11648/j.ijae.20230804.11
DO  - 10.11648/j.ijae.20230804.11
T2  - International Journal of Agricultural Economics
JF  - International Journal of Agricultural Economics
JO  - International Journal of Agricultural Economics
SP  - 122
EP  - 132
PB  - Science Publishing Group
SN  - 2575-3843
UR  - https://doi.org/10.11648/j.ijae.20230804.11
AB  - Farming communities who borrow agribusiness credit from Agricultural Finance Corporation (AFC) require efficient access to credit. Lender behaviour and decisions exhibited in credit supply dynamics influence agribusiness loan default rate. Mount Kenya region has registered a high default rate of 20.33% compared to a standard of 10% for all types of loans in Kenya. Using descriptive research design this, study sought to assess the effect of lender behavioural characteristics on agribusiness loans default rate in the region’s 11 branches and a population of 3,002 agribusiness borrowers. Systematic random sampling technique with an interval of 10 was used to sample 300 respondents. Primary data on lender behavioural characteristics was collected using a structured questionnaire. Statistical Packages for Social Sciences (SPSS V.27) and Stata version 15 were used to analyse data. To estimate the effect of variables in predicting default rate, regression analysis was used. In obtainment of the F-statistic for measuring the adequacy of the regression model, ANOVA was performed. Probit regression model was used to specify the statistical relationship between the variables. The four indicators used in the model explicated 48.80% of the dependent variable. Lender behavioural characteristics that were considered in the study had significantly affected AFC loan default rate at 1% level. The p-values of the pointers of lender behavioural characteristics for farm visit, disbursement timeliness, political lending and adequate funding (0.003,0.000,0.000,0.000) respectively were less than the p-value of 0.01. The negative coefficient (-0.355) of farm visit meant that lenders effort in visiting farmers would reduce default rate in AFC loans. However, the coefficient of disbursement timeliness, political lending and adequate funding had a positive coefficient implying a negative effect that increased AFC loans default rate. To mitigate default, credit officers need to disburse adequate loan expeditiously, refuse to yield to political interference and adhere to stipulations of lending policy. The study recommends that AFC should adequately and timely fund supervised borrower projects and own those projects by extending advisory and training inputs even as they embrace a neutral working environment that is free from political manipulation, compromise and influence.
VL  - 8
IS  - 4
ER  - 

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