The Future of Smallholder Farming in Eastern Africa - Uganda ...

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4.1.10 Farm Sizes The two districts had different average farm sizes, with Laikipia having relatively larger farms averaging 7.5 acres compared to Suba’s 4.1 acres. The average farm size for both districts was 5.9 acres. The modal farm sizes were 5 acres for Laikipia and 2 acres for Suba, with greater skewness towards zero in the case of Suba (Figure 12). Figure 12: Distribution of Land Sizes in Suba and Laikipia Districts Suba Laikipia 80 70 60 60 50 40 40 30 20 0 0.0 5.0 10.0 15.0 20.0 25.0 30.0 35.0 Std. Dev = 5.23 Mean = 4.1 N = 144.00 20 10 0 0.0 5.0 10.0 15.0 20.0 25.0 30.0 2.5 7.5 12.5 17.5 22.5 27.5 Std. Dev = 5.88 Mean = 6.9 N = 157.00 Estimated acres p1 Estimated acres p1 The main source of access to land is through inheritance, with about half of the responding obtaining land through inheritance while 22 percent purchased the land. About 12 percent of the respondents acquired land through government settlement while about one percent were squatters. Land subdivision is common in both regions, with 57 percent of the land parcels in Suba having been subdivided within the last few years. In Laikipia, about 20 percent of the parcels were subdivided recently. 4.1.11 Land Productivity Most farms in Suba and Laikipia have been farmed for a long period of time, leading to productivity decline. Two thirds of the respondents said their land productivity had declined. Only 28 percent of respondents reported productivity increases. About 63 of those whose land productivity declined were from Laikipia district, where a relatively higher proportion of land was under cultivation all year round (Table 5). About 60 percent of the respondents in Laikipia had at least 70 percent of their land under cultivation. Table 5: Status of Productivity over the years Value Frequency Percentage Constant 5 1.6 Decreasing 205 66.1 Increasing 88 28.4 No answer 12 3.9 Total 310 100.0
Figure 13 shows the level of cultivation in Laikipia district with trees being planted mainly around the homesteads while farms remain without any trees. Figure 13: Land Cultivation in Laikipia It is evident from Table 6 that productivity has been dropping more on larger farms than smaller ones. One would observe that cells for larger farms have mostly been experiencing productivity declines with very few of them registering productivity increases. Farmers who reported increase in land productivity were mainly those with smaller farms. They confirmed having kept productivity stable through use of fertilizer and manure. Table 6: Crosstab Analysis of Parcel Size and Land Productivity Over Time (%) Parcel Size (in acres) Land 0-1.0 1.1-2.0 2.1-4.0 4.1-6.0 6.1-10.0 10.1-15.0 15.1-25.0 > 25.0 Productivity Constant 5% 2% 2% - 3% - - - Decreased 67% 56% 57% 75% 90% 72% 82% 75% Increased 28% 42% 41% 25% 7% 28% 18% 25% 4.1.12 Education Bivariate analysis showed a significant relationship between education and both use of improved farm inputs and land productivity. Correlation coefficient showed that educated farmers are more likely to use fertilizer and certified seed than their less educated counterparts (Annex 1). Similar results were derived from Cross-tab analysis. Table 7
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Part One - Agricultural Productivit
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I. Introduction Agricultural Produc
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came about from expansion of cultiv
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study, therefore, limited itself to
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Land allocation and yields of 12 cr
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Table 6: Key economic variables for
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local seed in absolute terms and th
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Table 11: Crosscutting priority con
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Table 13: General constraints to ma
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These results clearly demonstrate t
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Table 18: Crosscutting constraints
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V. Policy Implications The findings
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References Appleton, Simon (2001).
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1.0 BACKGROUND 1.1 Introduction Low
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egins with a summary of the literat
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Source: National Wetlands Conservat
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shillings (§37-38). Every landowne
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Similarly, Howard (1995) used socia
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Uganda may well have more than a qu
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factors that explain household leve
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of inputs 18 , pests and diseases,
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(PMA p. 27). It also requires impro
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agriculturalists, who still do not
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to have covered 30,000 ha. During t
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4.0 RESEARCH METHODOLOGY The breadt
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• What is the current extent of w
Page 53 and 54: Figure 2. Changes in Sources of Com
Page 55 and 56: Figure 5. Proportion of Households
Page 57 and 58: estimates are remarkably consistent
Page 59 and 60: FSI - Percentage by District Distri
Page 61 and 62: was corrected using the White-Huber
Page 63 and 64: utilization for the household. Howe
Page 65 and 66: The nature of the structures to con
Page 67 and 68: impact of irrigation on horticultur
Page 69 and 70: growing population. Wetland protect
Page 71 and 72: APPENDICES Appendix 1. The Wetlands
Page 73 and 74: Appendix 2. THE 5V’s PRIORITY CLA
Page 75 and 76: Appendix 5. Determinants of Product
Page 77 and 78: Estimated covariances = 79 Number o
Page 79 and 80: International Food Policy Research
Page 81 and 82: Scherr, Sara J., 1999b. Poverty-env
Page 83 and 84: Land Tenure, Agricultural Productiv
Page 85 and 86: 1.3 Statement of the problem Land s
Page 87 and 88: In order to achieve these objective
Page 89 and 90: densely populated Nyeri and Kakameg
Page 91 and 92: Figure 3: Conceptual Model Type of
Page 93 and 94: Figure 4: Location of the Study Dis
Page 95 and 96: By 2001, land demarcation and regis
Page 97 and 98: 3.4 Survey Design The survey was un
Page 99 and 100: 3.5.3 Model of Environmental Degrad
Page 101 and 102: questionnaire (Figure 8). Prominent
Page 103: Figure 10: Availability of hired la
Page 107 and 108: joint significance test on the 4 dr
Page 109 and 110: Table 8: Regression Results on Maiz
Page 111 and 112: was classified into three categorie
Page 113 and 114: Table 9: Tobit Analysis with Enviro
Page 115 and 116: 5.0 CONCLUSIONS AND POLICY IMPLICAT
Page 117 and 118: 5.5 Access to Market A number of fa
Page 119 and 120: FAO (2003b). “Women and Food Secu
Page 121 and 122: Omiti John and Paul Obunde (2002).
Page 123 and 124: Annex 1: Pearson Correlation Coeffi
Page 125 and 126: SEXHH SEXLUSER TSECUR VEGCP1 CHILDE
Page 127 and 128: Part two - Agricultural Markets
Page 129 and 130: Market Liberalisation and Agricultu
Page 131 and 132: farms show annual fluctuations, wit
Page 133 and 134: Figure 2: Recent trends in domestic
Page 135 and 136: 5. The Model The interest of this s
Page 137 and 138: sources for each sector. α IM ji a
Page 139 and 140: Savings Households’ savings are a
Page 141 and 142: The value-added price is defined th
Page 143 and 144: Specifically, the Government polici
Page 145 and 146: Table 5: Calculated Tariff Rates (%
Page 147 and 148: disincentive to farmers. Inability
Page 149 and 150: competitiveness. The second one is
Page 151 and 152: Table 7: Wage Rates and Labour Inco
Page 153 and 154: Similar simulation is undertaken in
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References Block, S. and C.P. Timme
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Tyler, G. J. and Akinboade, O. 1992
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(A.10) ai ∑ P ϖ P i=1,...,3; j =
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(A.32) price (A.33) P Q = P ( 1+ td
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Table A.2: Variables of KEGEM Varia
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VA A i Efficiency parameter in valu
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CHAPTER FIVE Post-Liberalization Ma
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As alluded to earlier, initial agri
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directly to dairy farmers as animal
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to engage in this new role, the gov
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2.0 RESEARCH METHODOLOGY 2.1 Overal
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markets with minor gaps in data ser
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Price-series correlations are conve
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Migori Awendo Postliberalization 1,
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model depends on whether or not the
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Table 6b--Unit root tests for price
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Table 8a--Unit root tests for OLS r
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3.3 The Role of Infrastructure and
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Table 13--Reported distances from t
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Table 15--Reported maize storage pr
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Table 17--Traders’ perception of
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3.3.6.2 Awareness of the Liberaliza
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Retailer (open-air market) 21 13 7
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3.4 Maize Marketing Costs Traders w
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3.4.4 License and Market Fees Accor
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5.Develop farmers’ and traders’
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Coulter, J., and J. A. F. Compton.
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Meilink, A. H. 1987. Food consumpti
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Figure 1 Maize surplus and deficit
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Figure 3 Trends in Maize Prices 199
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Price per 90kg bag (Kshs) Mbeere Di
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Figure 4 Modes of transporting maiz
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Figure 6: Limitations to storage ca
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Figure 8: Problems experienced in a
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CHAPTER SIX Grain Marketing in Addi
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A third, related explanation argues
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educed marketing costs related to p
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1.4. Research questions This study
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1.6. Organization of the report Thi
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the cases, respectively (Table 2.4)
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Brokers believe that most regional
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There is also a close relationship
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Table 2.14: Buyers’ methods for i
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Source: Survey, 2002. Table 2.18: D
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Table 2.22: Method used to grade di
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Table 2.25: Access to credit broker
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It has been reported that grain pur
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3. GRAIN RETAILERS Retailers serve
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Like brokers, retailers use cash or
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Table 3.11: Buyers’ information a
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Table 3.14: Retailers’ views of g
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Getting reliable price information
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Table 4.4: How do you set a sales p
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Table 4.7: Means of settling disput
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a.m. The survey included wholesale
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Table 5.3: Instability index of dai
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Table 5.7: Seasonality index of who
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Figure 5.3: Ratio of wholesale to r
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Table 5.8: Results of stationary te
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Table 5.10: Summary of Granger caus
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holiday sales. The results of the r
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Table 6.1: Storage capacity of the
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Intermarket grain flow is coordinat
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• a legal, regulatory, and enforc
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REFERENCES Al-Hassen, R., A. Dorwar
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Seppala, P. 1998. Decisive liberali
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achieve some welfare objective. The
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Annex Table 2.10: Have you faced di
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Annex Table 2.21: Do you consider p
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Annex Table 3.3: Cost structure of
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Annex Table 4.2: Complementary acti
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CHAPTER SEVEN Post-Harvest Grain Ma
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only (see Abebe 2000: 80-83). That
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of processing as an important post-
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occur at all stages of post-harvest
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Endowment & access to Resources (e.
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Figure 2: The Study Areas (shaded a
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(6) β i = β 0 λ i , 0
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Intercrop differences Liquidity con
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eplace old animals (19 percent of h
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Table 5. Number and capacity of gra
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Table 7b.Estimated grain loss durin
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7.1.3. Grain Marketing Practices an
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1.8 Producers' price 1.6 1.4 1.2 1
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next season, grain prices tend to b
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Table 13: Regression results (Tobit
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of grain production was reportedly
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instruments to mitigate price risks
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Coulter, J. and G. Onumah, (2002).
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Appendix: Supplementary Tables Appe
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CHAPTER EIGHT Collective Action in
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The objectives of DRS were to popul
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increasing participation. Thus, the
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Table 2. Perceived change in benefi
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unsatisfactory (Table 8). Flaws in
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Table 14. Measures of wealth status
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Results from Regression Analysis Ta
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However, to maintain these benefits
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Table 18. Determinants of participa
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_______ 1981. Common property and c
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Management Regulations and Enforcem
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In theory, under PFM, the governmen
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3.2 Desk study The desk study invol
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Table 1: Number and gender of indiv
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Poverty Increase in number of fishe
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Table 5: Responses given by various
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wages after the catch is sold (see
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70 60 No of respondents 50 40 30 20
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4.2.3 Lack of attention to social i
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5.3 Regulate the construction of re
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REFERENCES Allison, E. H., and P. M
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APPENDIXES Appendix A: Districts of
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Questions and responses Government
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Questions and responses Lack of coo
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CHAPTER TEN Animal Health Service D
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• Individuals are selected for tr
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Makueni district was selected becau
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1.5 Justification of the study The
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more sustainable (Leonard 1993; Uma
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of defined roles for CBAHWs within
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Interviews with veterinary officers
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The estimated model was of the form
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Gender remains a sensitive issue. P
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The most common ailments and diseas
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4.3 Factors influencing the level o
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Table 9 -- Factors influencing the
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Table 10 - Factors determining the
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Table 12 -- Current mean numbers of
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Figure 4: Percentage of household h
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CBAHWs were the most utilized chann
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Users of veterinarians’ services
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Table 18 -- Levels of incomes and l
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higher average calving per cow, whi
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Table 21 -- CBAHWs’ ranking of sp
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epresentative of livestock keepers
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Despite the restriction imposed by
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veterinarians. Such associations co
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References Akabwai, D., V. Shean, a
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Johnson, P. J., and C. Chahuares. 1
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Appendix 1: The Logistic Procedure
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Social Capital and Sustainable Agri
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1.1 Soil conservation programs and
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1.3 Research Objectives and Hypothe
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Institutional and Policy factors -
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land pressure is high (Holden 1991)
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include density of membership in gr
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then summed up according to increas
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Social capital, resource use, and a
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Table 4.4 Farmers’ perception of
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Table 4.5: Empowerment and politica
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Table 4.8: Indicators of collective
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Table 4.10: Comparison of means of
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5. The influence of social capital
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especially when considered on an ad
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households may pay less attention t
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Table 5.3 Determinants of terracing
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and Gichuki 1994). In the 1940s, th
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Table 5.4. Determinants of soil con
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5.3. Social capital, resource use,
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6. Implications for policy and prog
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essential for the formation of exte
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BIBLIOGRPAHY Admassie, Y., L. I. Mw
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Gambetta, D. 1988. Can we trust tru
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Social capital and watershed develo
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Obare, G. A., S. W. Omamo, and J. C
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Washington D.C.: The World Bank Tem
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Appendix: A list of Contributors Ab
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Appendix: Projects Supported Under
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IFPRI Eastern Africa Food Policy Ne
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