Top Banner
THE USE OF CREDIT IN FISH PRODUCTION IN KENYA Kwamena Quagrainie Purdue University, USA Charles Ngugi and John Makambo Moi University, Kenya
15

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

Dec 19, 2015

Download

Documents

Welcome message from author
This document is posted to help you gain knowledge. Please leave a comment to let me know what you think about it! Share it to your friends and learn new things together.
Transcript
Page 1: Kwamena Quagrainie Purdue University, USA Charles Ngugi and John Makambo Moi University, Kenya.

THE USE OF CREDIT IN FISH PRODUCTION IN

KENYA

Kwamena QuagrainiePurdue University, USA

Charles Ngugi and John MakamboMoi University, Kenya

Page 2: Kwamena Quagrainie Purdue University, USA Charles Ngugi and John Makambo Moi University, Kenya.

Kenya Aquaculture

Small-scale and medium-scale

production of tilapia

(Oreochromis niloticus) and

catfish (Clarias gariepinus)Total production about 1,000

mt/yearFarms concentrated in western &

rift valley regions

Page 3: Kwamena Quagrainie Purdue University, USA Charles Ngugi and John Makambo Moi University, Kenya.

Background

Many farmers are literate, retired

civil servants, etc.Commercial banks providing

credit services for fish farming.Government support and

favorable policies towards

aquaculture.

Page 4: Kwamena Quagrainie Purdue University, USA Charles Ngugi and John Makambo Moi University, Kenya.

Purpose of Study

Need for investments in fish

farming to move from

subsistence to commercial

production.

Examine attitudes to credit &

factors that influence use of

credit.

Page 5: Kwamena Quagrainie Purdue University, USA Charles Ngugi and John Makambo Moi University, Kenya.

Survey

Questionnaire solicited information on:

Demographics

General Farm operations

Fish Farm operations

Page 6: Kwamena Quagrainie Purdue University, USA Charles Ngugi and John Makambo Moi University, Kenya.

Results - Demographics

Responses = 131Males – 85%Average age 50yrs

Western, 69%

Rift Valley, 20%

Central, 6% Eastern, 5%

Regional Response

Page 7: Kwamena Quagrainie Purdue University, USA Charles Ngugi and John Makambo Moi University, Kenya.

Primary35%

Secondary39%

Adult Ed4%

PostSecondary17%

Other Ed5%

Educational Level

Results - Demographics

Average # of ponds = 6 Average acreage = 616m2

Page 8: Kwamena Quagrainie Purdue University, USA Charles Ngugi and John Makambo Moi University, Kenya.

Results

Other producers

Direct to cosumers

Fish vendors Other Multiple outlets

11%

60%

3% 7% 9%

Market Outlet

Page 9: Kwamena Quagrainie Purdue University, USA Charles Ngugi and John Makambo Moi University, Kenya.

Economic Analysis of Credit Use

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)

Page 10: Kwamena Quagrainie Purdue University, USA Charles Ngugi and John Makambo Moi University, Kenya.

Parameter Estimates

VariableCoefficie

nt p-valueConstant -1.089 0.089Western region 0.871 0.013Age 0.005 0.664Some education -0.318 0.366Pond acreage -0.001 0.042Tilapia sales 0.261 0.006Catfish sales 0.086 0.080Direct to Customers -0.082 0.782Fulltime labor cost -0.006 0.009 Pseudo R-squared 0.20% Correct Predicted 78.62

Page 11: Kwamena Quagrainie Purdue University, USA Charles Ngugi and John Makambo Moi University, Kenya.

Marginal Effects

VariableCoefficie

nt p-valueWestern region 0.190 0.003Age 0.001 0.662Some education -0.088 0.396Pond acreage 0.000 0.022Tilapia sales 0.067 0.005Catfish sales 0.022 0.083Direct to Customers -0.021 0.783Fulltime labor cost -0.001 0.006

How do variables affect the probability of credit use?

Page 12: Kwamena Quagrainie Purdue University, USA Charles Ngugi and John Makambo Moi University, Kenya.

Interpretation of Results

Farmers in the Western region have 19% higher probability to use credit than farmers from other regions.

A m3 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.

Page 13: Kwamena Quagrainie Purdue University, USA Charles Ngugi and John Makambo Moi University, Kenya.

Implications of Results

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.

Page 14: Kwamena Quagrainie Purdue University, USA Charles Ngugi and John Makambo Moi University, Kenya.

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.

Page 15: Kwamena Quagrainie Purdue University, USA Charles Ngugi and John Makambo Moi University, Kenya.