University * Corresponding author: Gladys M. Musuva Telephone: Address:
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1 Characteristics of small holder tea farmers in Kiambu County and there effect on agricultural value chain financing Gladys Musuva 1*, Peter Lewa 1, George Achoki 1, Albino Luciani 2 1 Chandaria School of Business-United States International University 2 School of Public Health and Community Development-Maseno University * Corresponding author: Gladys M. Musuva Telephone: Address: gladys.musuva@gmail.com Key words Small holder farmer, value chain, value chain financing.
2 Background information Tea is the world s 2 nd most popular and lowest cost beverage drink with over three billion cups consumed worldwide In 2010, 1.7 million tonnes (43%) of the 3.9 million tonnes of tea were produced globally (EPC Kenya) were traded on the international market (Bordoloi, 2012). China (36%), India (25%), Kenya (10%), Sri Lanka (8%) and Turkey (5%) account for over 75% of global production and 71 % of global export (EPC Kenya, 2015; Bordoloi, 2012). Kenya is the biggest producer of standard-compliant tea at 40%, India (18%), Malawi (9%), Indonesia (8%), and China (6%)) by volume (SSI, 2014) and the leading global exporter of black tea (World Bank, 2013) Tea outputs contribute 11% of the 25% the agriculture sector contributes to the Gross Domestic Product (GDP) (Government of Kenya, 2013).
3 66% of the tea produced is grown in KTDA farms who have 550,000 smallholder tea farmers cultivating over 126,000 hectares of lands Tea industry directly and indirectly supports approximately 5M people (Tea Board of Kenya, 2014) Over 60 percent of Kenyan tea is produced by smallholder farmers (FAO, 2013) Agricultural value chain finance deals with funds flows to and within a value chain to meet the finance needs of farmers within the chain, to secure sales, to buy inputs or produce and to improve efficiency (Webber & Labaste, 2010).
4 Research Methodology 1. Study population, site and design A cross sectional study of 301 smallholder farmers in Kiambu County who supplied tea to 6 KTDA factorizes was conducted. Kiambu County lies between latitudes and South of the Equator and Longitude and East Borders Nairobi & Kajiado-South; Machakos-East, Murang a-north & North East, Nyandarua-North West, and Nakuru-West Average rainfall is 1,200 mm p.a with mean temperatures of 26 0 C
5
6 2. Sampling Design Systematic random sampling approach used 6 tea factories listed and systematically sampled the 10 th farmer. In cases where the 10 th farmer did not meet the inclusion criteria or declined to participate, the next respondent meeting the inclusion criteria was selected and the 10 th respondent interval restored. An average 25 respondents per factory were sampled (range of 23 to 27) to generate a sample size of 301 respondents KTDA Factories Number of Respondents Kambaa 51 Kagwe 48 Theta 49 Kuri 47 Gachege 54 Mataara 52
7 3. Data Collection Primary data was collected from Kiambu smallholder tea farmers at the KTDA factories through semi structured questionnaires. Key informant interviews conducted with Tea industry experts and bank officials Researcher observed
8 4. Data Analysis Univariate analysis used to describe farmer profiles. Bivariate analysis using Chi-Square tests done to determine any signification associations between smallholder farmer characteristics and access to agricultural value chain financing. Multivariate analysis using logistic regression tests done to determine signification associations within smallholder farmer characteristics and access to agricultural value chain financing Results with p < 0.05 value at 95% confidence interval was considered significant for all analysis.
9 1. UNIVARIATE RESULTS KEY RESULTS 276 individuals interviewed: 183 (66%) males and 93 (34%) females. Education 5% no education, 26% primary; 44% secondary; 20% certificate/diploma; 3% undergraduate and 2% post graduate degree Marital Status 86% married, 10% single and 4% separated/divorced Duration of tea farming and land ownership 14% < 5 years; 25% between 5-10 years and 61% > 10 years. Mean number of years of planting tea was 12.5 years (SD 6.3 years) 82% owned farming land while 18% leased Mean acreage per farmer was 2 acres (SD 0.66 acres).
10 Age Age Distribution Above 61 yrs 8% yrs 6% yrs 17% yrs 31% yrs 38%
11 Residence 91% lived in own personal houses and 9% in rented houses. 30% of those in own personal houses stayed in a permanent house, 43% in a semi-permanent house and 27% in mud/timber walled structures. Income source 88% tea as main source of income; 11% formal employment and 1% coffee Loan application 77% had taken a loan before for farming purposes while 23% had not. Median loan amount was KES 50,000 (IQR KES 20,000 KES 100,000). Median time to get loans after application was 5 weeks (IQR 2-7 weeks). Preferred lenders were SACCOs: 64%; banks: 57%; chamas: 45%; 5%: NGOs and shylocks: 7%
12 2. BIVARIATE ANALYSIS Predictor variable Outcome variable: Ever received credit facility? Frequency (%) Yes No A. Sex of respondents Male 158 (86) 25 (14) Female 74 (80) 19 (20) B. Age of respondents years 11 (69) 5 (31) years 77 (90) 9 (10) years 94 (90) 11 (10) years 36 (78) 10 (22) Above 60 years 13 (56) 10 (44) D.F Chi- Square. P-values (95% CI)
13 Predictor variable C. Marital Status Outcome variable: Ever received credit facility? Frequency (%) Yes No Married 23 (82) 5 (18) Single 199 (84) 38 (16) Separated/Divorced 9 (82) 2 (18)* D. Education None 7 (50) 7 (50) Primary 63 (88) 9 (12) Secondary 107 (88) 15 (12) Certificate/Diploma 44 (79) 12 (21) Undergraduate 6 (86) 1 (14)* Post graduate 5 (100)* 0 (0)* D.F Chi- Square. P-values (95% CI)
14 Predictor variable Outcome variable: Ever received credit facility? Frequency (%) D.F Chi- Square. P-values (95% CI). Yes No E. Acreage owned by borrower Less than 1 acre 87 (88) 12 (12) 1-3 acres 112 (79) 30 (21) More than 3 acres 30 (86) 5 (14) F. Income Source Employment 17 (55) 14 (45) Tea farming 213 (88) 30 (12) <0.001 Coffee farming 2 (100) 0 (0)*
15 3. MULTIVARIATE ANALYSIS Variable Levels Exp(β) 95% CI for Exp(β) P-value Lower Upper Age years Ref years years years <0.001 Above 60 years Education level None Primary Secondary Certificate/Diploma Undergraduate Post graduate Ref Acreage Less than 1 acre acres More than 3 acres Ref Source of income Employed Tea farming Coffee farming Ref - - -
16 DISCUSSION A quarter of global land under farming is in Africa yet: it generates only 10% global crop output (UNDP, 2012), leading to inherent non-profitability since most African farmers are small holders with limited or no access to financial services, farm inputs, right knowledge and skills set to optimize their productivity and increase their earnings (Hazellet al, 2007).
17 Cont. Kimathi et al (2008), describe rural farming as characterized by: higher transaction costs for both the financial institutions and farmers inadequate value chain finance, higher systemic risks, more volatile cash flows; as well as lower risk-bearing ability and higher vulnerability due to higher incidences as well wide spread and depth of poverty
18 Cont. Kiprono also cited Adeyemo et al (2010) as having 53% of respondents as being above 50 years in a study of economic efficiency of small scale farmers in Nigeria. This trend points to rural farming being a preserve for individuals who were just beyond their youth (age 35 years and below) and either approaching or in their retirement age (50 years and above). In this study, the most frequent age group was years (38%) and 86% of the respondents were married
19 Cont. Other studies such as Dzadze (2012) while investigating the factors determining access to formal credit among smallholder farmers in Ghana, reported that the education level had significant positive influence on farmers access to formal credit.
20 Cont. Whilst this study s findings concur with that of Ekasiba et al that age was significantly associated with the outcome of credit application, it differs with that study on the exact age group. This study lists years and years while Ekasiba et al list years and years implying that their study credit outcome was 10 years lesser than the current study.
21 CONCLUSIONS The study concluded that : Access to adequate, cost-effective, and timely financial services for smallholder farmers remains a challenge, Had a significant effect on the profitability of tea production farmer age, education level, acreage and primary source of income were associated with the success of credit application processes
22 Cont. Educational level was found to affect both the loan amount and profitability of tea production The acreage under tea affected the amount of loans awarded by the financial institution There is need for financial institutions, serving smallholder tea farmers, to improve loan effectiveness and efficiency through customized financial services and products.
23 Cont. There is need for increased education and training of smallholder farmers to equip them with the necessary information and expertise on agricultural value chain financing. A holistic capacity building approach of farmers will lead to improved productivity, increased adaptability in the face of climate change and market dynamics, and facilitates diversification of livelihoods to manage risks associated with the tea subsector.
24 Cont. The government in conjunction with banks should develop tailored credit facilities that do not only address the larger agricultural sector but those that are specific to small holder farmer needs like non-collateral based loans through signing agreements with tea factories to pay the banks directly after tea processing while providing for a grace period before payment amongst other initiatives that would encourage smallholder credit uptake
25 RECOMMENDATIONS Smallholder farmers should be equipped with information and expertise on agricultural value chain financing through a coordinated training and/or sensitization plan by government and key stakeholders Additional research to determine actual effectiveness of value chain financing and gain a more accurate understanding of the concept among smallholder tea farmers is needed. There is emerging use of Chama or over the table banking which is mostly carried out by women. A further study needs to be done on the effectiveness of this mode of financing. The government in conjunction with banks should develop tailored credit facilities that are specific to smallholder farmer needs like non-collateral based loans through signing agreements with tea factories
26 Author s Contributions Mrs. Musuva conceptualized and designed the study, conducted literature review, did data cleaning and drafted the manuscript. Prof. Lewa and Prof. Achoki provided guidance on study design, reviewed the analysis and manuscript and provided key comments on manuscript revision. Luciani conducted data analysis and reviewed my final manuscript. All authors read and approved the final manuscript.
27 Acknowledgements We would like to thank the study participants for their participation and Willis Odhiambo and Mercy Muhonja from KTDA for their support with sampling of farmers and availing secondary data. This paper was published with the permission of the Dean, Chandaria School of Business.
28 Any questions???
29 Thank You
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