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Kwamena Quagrainie Purdue University, USA Charles Ngugi and John Makambo Moi University, Kenya.

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Presentation on theme: "Kwamena Quagrainie Purdue University, USA Charles Ngugi and John Makambo Moi University, Kenya."— Presentation transcript:

1 Kwamena Quagrainie Purdue University, USA Charles Ngugi and John Makambo Moi University, Kenya

2  Small-scale and medium-scale production of tilapia (Oreochromis niloticus) and catfish (Clarias gariepinus)  Total production about 1,000 mt/year  Farms concentrated in western & rift valley regions

3  Many farmers are literate, retired civil servants, etc.  Commercial banks providing credit services for fish farming.  Government support and favorable policies towards aquaculture.

4  Need for investments in fish farming to move from subsistence to commercial production.  Examine attitudes to credit & factors that influence use of credit.

5  Questionnaire solicited information on:  Demographics  General Farm operations  Fish Farm operations

6  Responses = 131  Males – 85%  Average age 50yrs

7  Average # of ponds = 6  Average acreage = 616m 2

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9  Simple Binary Probit Analysis  Dependent variable: Whether or not credit is used to purchase inputs Explanatory variables  Region; western=1, otherwise=0  Age  Educational level; primary, secondary or adult=1, otherwise=0  Total pond acreage  Value of tilapia sales in past 6 months (KSH)  Value of catfish sales in past 6 months (KSH)  Type of market outlets; multiple=1, otherwise=0  Fulltime labor cost per day (KSH)

10 Variable Coefficien tp-value Constant-1.0890.089 Western region0.8710.013 Age0.0050.664 Some education-0.3180.366 Pond acreage-0.0010.042 Tilapia sales0.2610.006 Catfish sales0.0860.080 Direct to Customers-0.0820.782 Fulltime labor cost-0.0060.009 Pseudo R-squared0.20 % Correct Predicted78.62

11 VariableCoefficientp-value Western region0.1900.003 Age0.0010.662 Some education-0.0880.396 Pond acreage0.0000.022 Tilapia sales0.0670.005 Catfish sales0.0220.083 Direct to Customers-0.0210.783 Fulltime labor cost-0.0010.006  How do variables affect the probability of credit use?

12 Interpretation of Results  Farmers in the Western region have 19% higher probability to use credit than farmers from other regions.  A m 3 increase in pond acreage and a KSH increase in fulltime labor cost, increase the probability of credit use by 0.02% and 0.14% respectively.  A KSH increase in tilapia and catfish sales increase the probability of credit use by 7% and 2% respectively.

13  In general, there is a low probability of credit use by fish farmers.  More education is needed about the use of credit to expand aquaculture operations and improve commercialization.  Focus should be in the Western region where there is a greater % of aquaculture operations.

14 Acknowledgement This study was sponsored by the Aquaculture & Fisheries Collaborative Research Support Program (AquaFish CRSP) funded under USAID Grant No. EPP-A-00-06-00012-00 and by Purdue University, USA and Moi University, Kenya.

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