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FARMERS’WILLINGNESS TO PAY FOR IRRIGATION WATER
SYSTEM AS A MECHANISM FOR SUSTAINABLE WATERSHED
MANAGEMENT AND ENHANCED FO...
Outline
 Background Information
 Research issue/ Statement of the Problem
 Objectives of the study
 Study area
 Metho...
Background Information
 Water is a vital resource in enhancing agricultural
production in Kenya
 However, given the unre...
Background Information
 Kenya is classified as a water deficit country with water
resources unevenly distributed in space...
Background Information
 Irrigation in Kenya is mainly carried out in irrigation
schemes with smallholder schemes accounti...
Irrigation potential in Kenyan basins
0
50,000
100,000
150,000
200,000
250,000
Tana Athi Lake Victoria Kerio Valley Ewaso ...
Policy efforts
 In the past a lot of efforts and funds were directed in
expanding smallholder irrigation schemes, however...
Water Policy:
Treating water as an economic good
 Dublin Principles and IWRM—approach recommended
for MDGs
 2002 World S...
What do we mean by ‘economic
value?’
A commodity has an economic value when people are willing to pay
for it, rather than ...
What do we mean by ‘economic
value?’
Water’s value is the willingness to pay
for water
It is observed when people make a
c...
Most commonly used water valuation
techniques
Kiprop et al 2015
Frequency of
water valuation
studies Most common methods u...
Research Issue
 Elgeyo Marakwet County has a long history of
traditional furrow irrigation being practiced on the Kerio
b...
Research Issue
 Being a new system little is documented on how farmers
will react to introduction of water pricing
.
Kipr...
Transition from Traditional Irrigation system to
Modern system
Kiprop et al 2015
Research objectives
General objective
 To contribute to the sustainable management of
irrigation water in community manag...
Conceptual framework
Institutional factors
• Access to credit
• Membership in IWUA
• Land tenure system
• Access to extens...
Methodology
Study area
 The study was undertaken in Elgeyo Marakwet County.
 216 smallholder irrigation farmers were sam...
Map of the Study Area
Source: www.wri .org
Kiprop et al 2015
Analytical framework
 Objective 1: To identify the factors which influence
farmers’ willingness to pay for irrigation wat...
Analytical framework
 Objective 2: To determine the farmers’ mean willingness
to pay for irrigation water in the Kerio Va...
 If the respondent replies “no’’ for the first bid, then
further discussions on the payment are terminated.
 On the othe...
 The probabilities of the outcomes can be represented by
p (yy); p (nn); P (yn); and p (ny) for “yes”, “yes’’, “no”,
“no’...
 When a no is followed by a yes response the probability is :
Pny(Bi
I,Bi
L) = P (Bi
I >Max.WTP≥ Bi
L ) =G(Bi
I, ɵ) − G(B...
Variable Variable
Code
Types of
variable
Unit of Measurement of the Expected
sign
Dependent variables
Willingness to pay f...
Results
 Approximately 91.4% of the smallholder
farmers were willing to pay for irrigation water
with a mean Willingness ...
Factors Influencing farmers decision on WTP
Variables Coefficient Std. Err. z
Education level 2.88 1.34 2.14**
Age of farm...
Factors influencing farmers mean willingness to pay for
irrigation water
Variable Coefficient Std. Err. z
Age of farmer -3...
Conclusions and Recommendations
 More capacity building initiatives such
as training and field days should be
undertaken ...
Conclusions and Recommendations
 The water users associations should be
strengthened through training of technical
staff ...
Conclusions and Recommendations
 Implementing an irrigation water
management system that ensures
equitable water distribu...
Acknowledgements
 African Economic Research Consortium
(AERC) for their funding the research
through the CMMAE program
 ...
THANK YOU
Kiprop et al 2015
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FARMERS’ WILLINGNESS TO PAY FOR IRRIGATION WATER SYSTEM AS A MECHANISM FOR SUSTAINABLE WATERSHED MANAGEMENT AND ENHANCED FOOD PRODUCTION IN KERIO VALLEY BASIN KENYA

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FARMERS’ WILLINGNESS TO PAY FOR IRRIGATION WATER SYSTEM AS A MECHANISM FOR SUSTAINABLE WATERSHED MANAGEMENT AND ENHANCED FOOD PRODUCTION IN KERIO VALLEY BASIN KENYA

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FARMERS’ WILLINGNESS TO PAY FOR IRRIGATION WATER SYSTEM AS A MECHANISM FOR SUSTAINABLE WATERSHED MANAGEMENT AND ENHANCED FOOD PRODUCTION IN KERIO VALLEY BASIN KENYA

  1. 1. FARMERS’WILLINGNESS TO PAY FOR IRRIGATION WATER SYSTEM AS A MECHANISM FOR SUSTAINABLE WATERSHED MANAGEMENT AND ENHANCED FOOD PRODUCTION IN KERIO VALLEY BASIN KENYA By Jonah Kipsaat Kiprop, Job Lagat and Patience Mshenga 9 th EGERTON UNIVERSITY INTERNATIONAL CONFERENCE 25 th -27 th March 2015 EGERTON UNIVERSITY, KENYA Kiprop et al .,2015
  2. 2. Outline  Background Information  Research issue/ Statement of the Problem  Objectives of the study  Study area  Methodology  Results  Conclusions and Recommendations Kiprop et al 2015
  3. 3. Background Information  Water is a vital resource in enhancing agricultural production in Kenya  However, given the unreliable rains, irrigation is critical in increasing and sustaining agricultural productivity  With climate change projected to account for 20 percent of the global increase in water scarcity (FAO-COAG, 2007). There is need to formulate policies that ensures efficient allocation of water. Kiprop et al 2015
  4. 4. Background Information  Kenya is classified as a water deficit country with water resources unevenly distributed in space and time (ASDS, 2010-2020)  Only 17 % of the land area is high potential thus receiving adequate rainfall the remaining land is arid and semi-arid and cannot support crop production without irrigation  The Government has acknowledged the relevance of irrigated agriculture, in this regard it is a key component of Agricultural Sector Development Strategy of 2010- 2020 towards achieving Vision 2030. Kiprop et al 2015
  5. 5. Background Information  Irrigation in Kenya is mainly carried out in irrigation schemes with smallholder schemes accounting for 42% while government managed schemes account for 18% (RoK, 2010)  Only a small fraction 1.8% of crop land in Kenya is under irrigation while there lies a great potential of 1.3 million hectares (NIB, 2012) as illustrated in the figure below. Kiprop et al 2015
  6. 6. Irrigation potential in Kenyan basins 0 50,000 100,000 150,000 200,000 250,000 Tana Athi Lake Victoria Kerio Valley Ewaso Ngiro AreainHa Kenyan basins Source: National Irrigation Board (NIB), 2012 Kiprop et al 2015
  7. 7. Policy efforts  In the past a lot of efforts and funds were directed in expanding smallholder irrigation schemes, however most schemes failed due to lack of self-sustaining systems  The Draft Water Policy of 2010 emphasized the need for enhancing the capacity of farmers to own, manage, and finance irrigation schemes through formation of Irrigation water users’ associations (IWUA’S)  Water pricing as an economic instrument that has been used worldwide to improve water allocation and to enhance sustainability in management of irrigation schemes (Bazza, 2002). Kiprop et al 2015
  8. 8. Water Policy: Treating water as an economic good  Dublin Principles and IWRM—approach recommended for MDGs  2002 World Summit on Sustainable Development in Johannesburg  2003 Third World Water Forum  2006 World Water Development Report  Human Development Report 2006 Beyond scarcity: power, poverty and the global water crisis Kiprop et al 2015
  9. 9. What do we mean by ‘economic value?’ A commodity has an economic value when people are willing to pay for it, rather than go without it is a monetary measure of the intensity of individual preferences (needs, wants, desires)  Market goods ◦ Observed equilibrium market prices represent the willingness-to- pay  Non-market goods ◦ Benefits are based on individual values in the form of willingness-to-pay (WTP) and their aggregation across all affected individuals ◦ Costs are the value of the opportunities forgone because of the commitment of resources to a project, or the willingness-to-pay to avoid detrimental effects (damages). Kiprop et al 2015
  10. 10. What do we mean by ‘economic value?’ Water’s value is the willingness to pay for water It is observed when people make a choice between different products • How much will a household pay for drinking water? • How much will a farmer pay for irrigation water? • How much will a factory pay for clean water? Kiprop et al 2015
  11. 11. Most commonly used water valuation techniques Kiprop et al 2015 Frequency of water valuation studies Most common methods used Residual value (and variations) Production function CVM, programming models Manufacturing Uncommon Production function, programming Hydroelectric power Common Programming models, opportunity cost Waste assimilation services Common Cost of prevention, Benefits from damages averted Agriculture Most common application
  12. 12. Research Issue  Elgeyo Marakwet County has a long history of traditional furrow irrigation being practiced on the Kerio basin dating back to 400 years ago (Kipkorir, 1983).  Despite the traditional system bringing development in the past, it was inefficient in water use (Chepkonga et al., (2002).  Currently the traditional systems are being upgraded to modern systems, under this new arrangement water users will pay a fee under the management of the irrigation water users associations. Kiprop et al 2015
  13. 13. Research Issue  Being a new system little is documented on how farmers will react to introduction of water pricing . Kiprop et al 2015
  14. 14. Transition from Traditional Irrigation system to Modern system Kiprop et al 2015
  15. 15. Research objectives General objective  To contribute to the sustainable management of irrigation water in community managed smallholder irrigation schemes, by establishing an effective water pricing mechanism Specific objectives 1. To determine the socio-economic factors which influence the farmers’ willingness to pay for irrigation water in the Kerio valley basin 2. To assess how much farmers’ are willing to pay for irrigation water in the Kerio valley basin Kiprop et al 2015
  16. 16. Conceptual framework Institutional factors • Access to credit • Membership in IWUA • Land tenure system • Access to extension service Farm and farmers characteristics’ • Age of farmer • Education level • Farm size • Occupation • income Attributes of the new system of irrigation •Minimal repair costs •Irrigation land coverage Outcome •Improved management of water resources. •Reduced water conflicts •Reduced water wastage •Increased land under irrigation •Enhanced food production Not willing to pay Farmers’ willingness to pay for irrigation water Farmers’ perceptions on paying for irrigation water Kiprop et al 2015
  17. 17. Methodology Study area  The study was undertaken in Elgeyo Marakwet County.  216 smallholder irrigation farmers were sampled from Arror irrigation scheme  The major crops food grown are maize, mangoes bananas, sorghum, millet and cowpeas. Cotton is grown cash crop Kiprop et al 2015
  18. 18. Map of the Study Area Source: www.wri .org Kiprop et al 2015
  19. 19. Analytical framework  Objective 1: To identify the factors which influence farmers’ willingness to pay for irrigation water.  The classical Probit model was used to identify the socio-economic factors that influence farmers’ decision to pay or not to pay for irrigation water.  The outcome equation was; Willingness to pay(Yi) = β0+ β1Agehh+ β2Edulevelhh+ β3Farmsize+ β4Croptype+ β5Perc-mai+ β6Distmkt+ β7Famlysize+ β8Tlu-own+ β9Crd-acc+ β10Ext-ctc+ β11Income-irr+ β12Tot-income+ β13Traing+ β14Expr- irr+ β15Memb-iwua+ β16Prox-water+ β17Perc_mai+ ε Kiprop et al 2015
  20. 20. Analytical framework  Objective 2: To determine the farmers’ mean willingness to pay for irrigation water in the Kerio Valley basin.  The double bounded contingent valuation method was used to value the water resource since there is no market for irrigation water in the area.  Once the farmer made the choice to pay, the next decision was to determine the amount of payment (intensity) in Kenyan Shillings. Kiprop et al 2015
  21. 21.  If the respondent replies “no’’ for the first bid, then further discussions on the payment are terminated.  On the other hand if the respondent’s choice is ‘’yes’’ then a second question is posed with a starting bid value. If the payment choice for Kshs, is ‘’yes’’ then the respondent will face another level of bid choice, which would be higher or lower amount, respectively.  This second amount (bid) is based on the response of the first bid (if the response for the first is yes, then the following bid will be double the first one and half if otherwise). Kiprop et al 2015
  22. 22.  The probabilities of the outcomes can be represented by p (yy); p (nn); P (yn); and p (ny) for “yes”, “yes’’, “no”, “no’’, “yes”, “no’’ and “no”, “yes’ ’outcomes respectively. Following Hanemann et al. (1991), these likelihoods can be represented mathematically as;  The probability of “ no, no” outcome is represented as: Pnn(Bi 1,Bi 1) = P (Bi L >Max.WTP and Bi L >Max.WTP) = G(Bi L,ɵ)  The probability of “yes, yes” will be: Pyy(Bi 1,Bi U) = P (Bi L >Max.WTP and Bi U >Max.WTP) = G(Bi U,ɵ)  When a “yes” is followed by “no” we have: Pyn(Bi 1,Bi U) = P (Bi L <Max.WTP ≤ Bi U ) =G(Bi U, ɵ) − G(Bi L, ɵ) Kiprop et al 2015
  23. 23.  When a no is followed by a yes response the probability is : Pny(Bi I,Bi L) = P (Bi I >Max.WTP≥ Bi L ) =G(Bi I, ɵ) − G(Bi L, ɵ)  With a sample of N observations where B is the various bid values the outcome equation is;  L(ɵ) = Ʃ di yy .Pyy (Bi 1,Bi U) +di nn.Pnn(Bi I,Bi L) + di yn .Pyn (Bi 1,Bi U) +di ny.Pny(Bi I,Bi L) Kiprop et al 2015
  24. 24. Variable Variable Code Types of variable Unit of Measurement of the Expected sign Dependent variables Willingness to pay for irrigation water WTP Dummy 1 for those willing to participate and 0 other wise Independent variables Education level of household head EDULHH Continuous Years - Age of household head AGEHH Continuous Years - Type of crop Grown CROP-TYP Dummy 1 if cash crops are produced,0 otherwise + Perception about operation and maintenance PERC-MAI Dummy 1 if perceived,0 otherwise + Distance from the market DIST-MKT Continuous Kilometre - Household family size FAMSIZE Continuous Number of persons in a household +/- Livestock ownership TLU-OWN Continuous Number of livestock owned +/- Access to credit service CRD-ACC Dummy 1 if accesibles,0 otherwise +/- Access or contact with extension service EXT-CTC Dummy 1 if accessible , 0 otherwise + Income from irrigated farm INCOME- IRR Continuous Kenyan Shillings + Access to training TRAING Dummy 1 Trained,0 otherwise + Membership in irrigation water users association MEMB- IWUA Dummy 1 Member, 0 otherwise + Proximity to water source PROX-WS Continuous Kilometre - Perception and observation about maintenance problem PERC_MAI Dummy 1 if perceived, 0 otherwise +/- Description of variables and the expected Signs to be used in the models Kiprop et al 2015
  25. 25. Results  Approximately 91.4% of the smallholder farmers were willing to pay for irrigation water with a mean Willingness to pay of Ksh 938 per production season.  This represents about 9.6% of the average total farm income. Kiprop et al 2015
  26. 26. Factors Influencing farmers decision on WTP Variables Coefficient Std. Err. z Education level 2.88 1.34 2.14** Age of farmer -0.017 0.023 -0.74 Participation in construction 1.50 0.75 2.01** Household size 0.25 0.18 1.42 Gender of household head -0.74 0.71 -1.03 Distance to the market -0.35 0.12 -2.76 Total livestock ownership 0.008 0.015 0.54 Access to credit service -0.064 0.90 -0.07 Access to extension service -1.64 0.83 -1.97** Total income from irrigated farm 5.80 1.53 3.79** Access to agricultural training 1.88 0.71 2.62 Membership in (IWUA) 1.72 0.81 2.10** Distance to water source -0.352 0.12 -2.88* Constant 4.18 1.62 2.58* N 216 LR χ2 95.10 Prob> χ2 0.000 Pseudo R2 0.7707 Log likelihood -14.143*, **, *** significant at 10, 5 and 1 percent level, respectively Kiprop et al 2015
  27. 27. Factors influencing farmers mean willingness to pay for irrigation water Variable Coefficient Std. Err. z Age of farmer -30.27558 6.061803 -4.99** Household size 109.3838 33.70524 3.25* Membership in IWUA 76.38428 238.9641 0.32 Access to credit 2.598333 174.4956 0.01 Access to extension -423.3809 230.2513 -1.84 Access to training -136.5829 186.0542 -0.73 Participation in construction 282.9909 220.926 1.28 Distance to water source -97.71583 38.67595 -2.53** Distance to the market -68.43047 28.59172 -2.39 Total livestock owned 0 .0151607 2.556768 0.01 Income from irrigation 53064 .0020247 2.62* Constant 938.4346 560.7905 1.67*** Number of observations 197 F(14, 120) 15.78 Prob >F 0.000 R-squared 0.6461 Adjusted R-squared 0.6081 *, **, *** significant at 10, 5 and 1 percent level, respectively Kiprop et al 2015
  28. 28. Conclusions and Recommendations  More capacity building initiatives such as training and field days should be undertaken to enhance the farmers’ willingness to pay  Establishing a feasible water charging system in the schemes such as the volumetric basis of water charging will be helpful. Kiprop et al 2015
  29. 29. Conclusions and Recommendations  The water users associations should be strengthened through training of technical staff such as plumbers who will ensure water systems are properly maintained  Adequate extension support should be delivered more specifically on irrigation farming so that farmers would be able to make efficient use of their irrigated land Kiprop et al 2015
  30. 30. Conclusions and Recommendations  Implementing an irrigation water management system that ensures equitable water distribution and effective enforcement of existing rules and regulations, would not only enhance the farmers’ willingness to pay but also the amount they would commit Kiprop et al 2015
  31. 31. Acknowledgements  African Economic Research Consortium (AERC) for their funding the research through the CMMAE program  Department of Agricultural Economics and Agribusiness Management Egerton University  KVDA field staff Kiprop et al 2015
  32. 32. THANK YOU Kiprop et al 2015

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