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  1. Welcome

  2. Farmers’ benchmark study Third Round of Data Collection: Kenya Andrew Karlyn Director of Strategy and Learning

  3. Methodology

  4. FARMERS’ BENCHMARK STUDY: KENYA THIRD round of data collection Nationally representative survey of smallholder farmers B C A Booster Sample 1 Random Sample Booster Sample 2 Booster sample for Central and Western N= 620 Booster sample for Meru and Tharaka Nithi( Sorghum) and Migori (Soya beans) N=180 National representative sample N=1200 Total Target Sample=2,000

  5. FARMERS’ BENCHMARK STUDY: KENYA THIRD round of data collection Defining Smallholder Farmers Selection Criteria Land size cultivated in the last 12 months is between 0.1 and 10 acres Land Size • Households involved in any of the below activities: • Crop farming • Livestock farming • Both crop and livestock farming • Buying and selling farm produce Activities Agriculture provides a meaningful contribution to the households’ livelihood, income or consumption ( Self Identified) Contribution to Household Income • Individual respondents were selected randomly in households qualifying as smallholder farmers. The criteria for selection of individual respondents were: • 18 years and above • Involved in making financial decisions • Involved in making agricultural decisions

  6. FARMERS’ BENCHMARK STUDY: KENYA THIRD round of data collection Defining Digital Financial Inclusion 2 3 1 Fulfillment of any of the above criteria was considered in identifying respondents who are Digitally Financially Included

  7. Farmers’ Profile

  8. FARMERS’ BENCHMARK STUDY: KENYA THIRD round of data collection Demographics Education level Gender and Age of Respondents Marital status and Income levels Marital Status Gender Segregation Age Segregation Income Levels

  9. FARMERS’ BENCHMARK STUDY: KENYA THIRD round of data collection Age and Gender appear to be important determinants of the size of land under cultivation • Female and Youth farmers tend to have cultivated slightly smaller parcels of land in the past 12 months prior to the survey. • Over 90% of the interviewed farmers cultivated one parcel of land in the last 12 months with an average size of 1.44 acres

  10. FARMERS’ BENCHMARK STUDY: KENYA THIRD round of data collection Household decision making appears more jointly between household head and female spouse N=2005

  11. FARMERS’ BENCHMARK STUDY: KENYA THIRD round of data collection Over 90% of interviewed smallholder farmers engage in multiple value chains N=1928

  12. FARMERS’ BENCHMARK STUDY: KENYA THIRD round of data collection Smallholder farmers do crop farming for own consumption and sale N=1928

  13. FARMERS’ BENCHMARK STUDY: KENYA THIRD round of data collection Travelling merchants at farm gate are preferred buyers because they pay at hand N=1928

  14. FARMERS’ BENCHMARK STUDY: KENYA THIRD round of data collection Smallholder farmers are predominantly paid in cash N=1928 • Digital payments are mainly made by processors and Brokers at aggregation points- mainly for cash crops like Tea and Coffee.

  15. FARMERS’ BENCHMARK STUDY: KENYA THIRD round of data collection Smallholder farmers spend more on farm inputs

  16. FARMERS’ BENCHMARK STUDY: KENYA THIRD round of data collection Farm expenses are mainly paid in cash • Although payments are made in cash, the farmers tend to take farm inputs on credit mostly from the buyers of their produce and repay at a later date • Credit implies paying later and cash means paying immediately. N=1928

  17. Preparedness for Digital Inclusion

  18. FARMERS’ BENCHMARK STUDY: KENYA THIRD round of data collection 90% of the interviewed smallholder farmers were able to get at least one mathematical calculation right N=2005

  19. FARMERS’ BENCHMARK STUDY: KENYA THIRD round of data collection Over 50% of the interviewed smallholder farmers are able to read and understand statements presented to them N=2005

  20. FARMERS’ BENCHMARK STUDY: KENYA THIRD round of data collection Smallholder farmers exhibit good financial behavior despite the fact that they lack emergency funds which are a good opportunity for loans N=2005

  21. FARMERS’ BENCHMARK STUDY: KENYA THIRD round of data collection Over 50% of the interviewed farmers make plans on how to spend their income although they rarely stick to those plans N=2005

  22. FARMERS’ BENCHMARK STUDY: KENYA THIRD round of data collection 88% of the interviewed smallholder farmers own mobile phones N=2005

  23. FARMERS’ BENCHMARK STUDY: KENYA THIRD round of data collection Less than 50% of the smallholder farmers make digital payments using their mobile phones N=1959

  24. FARMERS’ BENCHMARK STUDY: KENYA THIRD round of data collection A slight increase in the number of smallholder farmers using internet through their phones in 2017

  25. Digital Financial Inclusion of Smallholder farmers

  26. FARMERS’ BENCHMARK STUDY: KENYA THIRD round of data collection 68% of the interviewed smallholder farmers are digitally included. N=2005 • Less youth farmers are digitally included as compared to the elderly farmers(31+ years) • Among males and females interviewed, there seems to be the same level of financial inclusion

  27. FARMERS’ BENCHMARK STUDY: KENYA THIRD round of data collection Distribution of Digitally Included Farmers • Central province recorded the highest number of smallholder farmers that are digitally included ( 84%) particularly in Kiambu county • Coast province recorded the lowest percentage of digitally included smallholder farmers; this could be because of low sample size for coast • A high number of the digitally included farmers use mobile money for sending money. • Both digitally included and excluded smallholder farmers tend to grow the same type of crops with Maize being the main crop grown but the digitally included tend to sell more quantities as compared to digitally excluded farmers.

  28. FARMERS’ BENCHMARK STUDY: KENYA THIRD round of data collection Digitally included farmers supplement their farm income with income from casual jobs N=2005

  29. FARMERS’ BENCHMARK STUDY: KENYA THIRD round of data collection 66% of the interviewed farmers own a basic phone • High number of smart phone owners are digitally included

  30. FARMERS’ BENCHMARK STUDY: KENYA THIRD round of data collection Male youth farmers make more electronic payments as compared to older farmers N=1959

  31. Agricultural Advisory services

  32. FARMERS’ BENCHMARK STUDY: KENYA THIRD round of data collection 57% of the smallholder farmers have access to Agricultural advisory services N=2005 • A slightly higher number of digitally included farmers have access to Agricultural advisory services

  33. FARMERS’ BENCHMARK STUDY: KENYA THIRD round of data collection Number of smallholder farmers accessing Agricultural advisory services has been increasing over the last three years • Farmer to farmer extension has remained to be most important channel for passing information among smallholder farmers

  34. FARMERS’ BENCHMARK STUDY: KENYA THIRD round of data collection Farmer to farmer extension is a common channel for sharing information among the smallholder farmers

  35. FARMERS’ BENCHMARK STUDY: KENYA THIRD round of data collection Other useful channels for sharing information with smallholder farmers N=2005 • More farmers are listening to Agricultural radio programs though very few • ( 4%) consider radio programs as a source of Agricultural advise

  36. Financial Services

  37. FARMERS’ BENCHMARK STUDY: KENYA THIRD round of data collection More than 50% of the interviewed smallholder farmers have savings N=2005 • 50% of those who have a saving product are digitally included farmers • A higher number of old farmers are saving as compared to youth farmers

  38. FARMERS’ BENCHMARK STUDY: KENYA THIRD round of data collection The number of smallholder farmers saving is decreasing over the years for Central and Western provinces • It is important to note that each year different farmers are randomly selected to participate in the survey.

  39. FARMERS’ BENCHMARK STUDY: KENYA THIRD round of data collection Digitally included farmers prefer to save with M-Pesa because of ease to access own savings N=1156

  40. FARMERS’ BENCHMARK STUDY: KENYA THIRD round of data collection There is a slight increase in the number of smallholder farmers saving with Equitel and Microfinance Bank in Central and Western provinces N=1156

  41. FARMERS’ BENCHMARK STUDY: KENYA THIRD round of data collection In addition to lack of additional income, lack of information about saving products appears as a barrier to saving in Kenya N=849 N=1156

  42. FARMERS’ BENCHMARK STUDY: KENYA THIRD round of data collection 20% of the interviewed farmers are currently servicing a loan N=2005

  43. FARMERS’ BENCHMARK STUDY: KENYA THIRD round of data collection Slightly less number of smallholder farmers are saving currently as compared to the previous two years (Central and Western provinces)

  44. FARMERS’ BENCHMARK STUDY: KENYA THIRD round of data collection ‘Chamas’ are a preferred source of credit because of accessibility and loan terms • A high number of female respondents preferred loans from Chamas while men highly preferred bank loans • M-Shwariseems to be a preferred source of loan for the few youths currently servicing loans/ credit

  45. FARMERS’ BENCHMARK STUDY: KENYA THIRD round of data collection Number of loans from M-Shwari and KCB M-Pesa have slightly increased in Central Province

  46. FARMERS’ BENCHMARK STUDY: KENYA THIRD round of data collection There are many avenues to access and repayment of loans N=401

  47. FARMERS’ BENCHMARK STUDY: KENYA THIRD round of data collection High interest rates and lack of adequate information about credit facilities are the main reasons for low uptake of loan N=1604

  48. FARMERS’ BENCHMARK STUDY: KENYA THIRD round of data collection Pests and diseases and changing weather conditions are the main challenges facing smallholder farmers N=2005

  49. FARMERS’ BENCHMARK STUDY: KENYA THIRD round of data collection Smallholder farmers mainly depend on their savings to cope with uncertainties N=2005

  50. FARMERS’ BENCHMARK STUDY: KENYA THIRD round of data collection There is very low uptake of insurance as a strategy to cope with risks N=2005 • Low number of youths and female farmers have insurance cover of any type • Medical insurance forms a higher percentage under ‘other insurance’.