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

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5. The influence of social capital on perceptions of soil erosion problems, investments in terraces, and agricultural productivity In this chapter, we present and discuss the results of the empirical model. The descriptive statistics for explanatory variables are given in Table 5.1. They have been disaggregated for the individual study sites to enable a comparison of the variable mean values, to establish whether there is a significant difference between the two sites. Inadequate rural infrastructure, which translates to relatively high access costs to input and output markets, imposes significant burdens on cost-minimizing smallholders. Farmers faced with high farm-to-market access costs commit fewer resources to agricultural production (Obare, Omamo, and Williams 2003), resulting in low productivity. In the study areas, relatively high access costs prevailed. The mean differential access cost (ACESCOS) of 115 in Machakos and 93 in Taita-Taveta should have a bearing on crop returns in the two study sites, yet mean crop income is not significantly different between the two districts. This could be due to the existing output market structures. Machakos District has access to relatively dense consumption demand sites such as the town of Machakos and even Nairobi, which is not far. In Taita-Taveta, the supply outlets are thin and the nearest high-demand market, Mombasa, is relatively far. Therefore, although Taita-Taveta’s access costs may be lower, that advantage is offset by the reduced prices that farmers receive for their products due to a relatively thin market and, thus, lower demand.
Table 5.1. Descriptive statistics for explanatory variables used in empirical analysis Variable District N Mean Std. Dev. Diff. Significant ACESCOS Machakos 155 114.84 24.50 F=36.709*** Taita-Taveta 160 93.17 40.66 t=-5.709 INC Machakos 160 64,134.85 178688.89 F=4.994 Taita-Taveta 161 40,046.58 83046.60 t=-1.467 CROPAC Machakos 160 16847.85 39512.74 F=0.830 Taita-Taveta 161 15699.70 29536.19 t=-0.300 LIVESTOCK Machakos 99 26811.21 33221.15 F=2.744* WEALTH Taita-Taveta 151 33312.85 57516.24 t=1.018 DISTH Machakos 158 357.22 918.92 F=85.888*** Taita-Taveta 158 2065.98 3630.076 t=5.736*** TERRACES Machakos 160 926.1328 1267.22 F=0.019 Taita-Taveta 161 598.51 1994.22 T=-1.755* HHS Machakos 160 6.14 2.76 F=0.001 Taita-Taveta 161 6.38 2.73 t=0.788 FARMSIZE Machakos 156 1.93 3.39 F=1.533 Taita-Taveta 161 2.47 3.21 t=1.456 MANURE USE Machakos 121 1160.33 1921.38 F=5.424** Taita-Taveta 45 480.78 887.58 t=-2.282** FERTUSE Machakos 53 45.33 69.91 Taita-Taveta 0 WEALTH Machakos 160 2.07 1.68 F=3.187* Taita-Taveta 161 2.19 2.17 t=0.582 EDUC Machakos 159 6.79 3.98 F=1.765 Taita-Taveta 119 7.18 3.70 t=0.834 SLOPE Machakos 156 2.33 0.87 F=0.521 Taita-Taveta 157 2.24 0.84 t=-0.904 TENURE Machakos 155 5.91 1.23 F=22.167*** Taita-Taveta 161 5.86 0.96 t=-0.441 FARMCA Machakos 156 0.35 0.57 F=3.134* Taita-Taveta 161 0.46 0.66 t=1.639 LABOUR Machakos 160 156.07 166.38 F=14.049*** Taita-Taveta 161 235.35 295.10 t=2.962*** *Significant at P
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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
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Figure 2. Changes in Sources of Com
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Figure 5. Proportion of Households
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estimates are remarkably consistent
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FSI - Percentage by District Distri
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was corrected using the White-Huber
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utilization for the household. Howe
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The nature of the structures to con
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impact of irrigation on horticultur
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growing population. Wetland protect
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APPENDICES Appendix 1. The Wetlands
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Appendix 2. THE 5V’s PRIORITY CLA
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Appendix 5. Determinants of Product
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Estimated covariances = 79 Number o
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International Food Policy Research
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Scherr, Sara J., 1999b. Poverty-env
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Land Tenure, Agricultural Productiv
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1.3 Statement of the problem Land s
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In order to achieve these objective
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densely populated Nyeri and Kakameg
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Figure 3: Conceptual Model Type of
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Figure 4: Location of the Study Dis
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By 2001, land demarcation and regis
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3.4 Survey Design The survey was un
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3.5.3 Model of Environmental Degrad
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questionnaire (Figure 8). Prominent
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Figure 10: Availability of hired la
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Figure 13 shows the level of cultiv
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joint significance test on the 4 dr
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Table 8: Regression Results on Maiz
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was classified into three categorie
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Table 9: Tobit Analysis with Enviro
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5.0 CONCLUSIONS AND POLICY IMPLICAT
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5.5 Access to Market A number of fa
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FAO (2003b). “Women and Food Secu
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Omiti John and Paul Obunde (2002).
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Annex 1: Pearson Correlation Coeffi
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SEXHH SEXLUSER TSECUR VEGCP1 CHILDE
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Part two - Agricultural Markets
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Market Liberalisation and Agricultu
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farms show annual fluctuations, wit
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Figure 2: Recent trends in domestic
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5. The Model The interest of this s
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sources for each sector. α IM ji a
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Savings Households’ savings are a
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The value-added price is defined th
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Specifically, the Government polici
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Table 5: Calculated Tariff Rates (%
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disincentive to farmers. Inability
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competitiveness. The second one is
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Table 7: Wage Rates and Labour Inco
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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
Page 410 and 411: Table 12 -- Current mean numbers of
Page 412 and 413: Figure 4: Percentage of household h
Page 414 and 415: CBAHWs were the most utilized chann
Page 416 and 417: Users of veterinarians’ services
Page 418 and 419: Table 18 -- Levels of incomes and l
Page 420 and 421: higher average calving per cow, whi
Page 422 and 423: Table 21 -- CBAHWs’ ranking of sp
Page 424 and 425: epresentative of livestock keepers
Page 426 and 427: Despite the restriction imposed by
Page 428 and 429: veterinarians. Such associations co
Page 430 and 431: References Akabwai, D., V. Shean, a
Page 432 and 433: Johnson, P. J., and C. Chahuares. 1
Page 434 and 435: Appendix 1: The Logistic Procedure
Page 436 and 437: Social Capital and Sustainable Agri
Page 438 and 439: 1.1 Soil conservation programs and
Page 440 and 441: 1.3 Research Objectives and Hypothe
Page 442 and 443: Institutional and Policy factors -
Page 444 and 445: land pressure is high (Holden 1991)
Page 446 and 447: include density of membership in gr
Page 448 and 449: then summed up according to increas
Page 450 and 451: Social capital, resource use, and a
Page 452 and 453: Table 4.4 Farmers’ perception of
Page 454 and 455: Table 4.5: Empowerment and politica
Page 456 and 457: Table 4.8: Indicators of collective
Page 458 and 459: Table 4.10: Comparison of means of
Page 462 and 463: especially when considered on an ad
Page 464 and 465: households may pay less attention t
Page 466 and 467: Table 5.3 Determinants of terracing
Page 468 and 469: and Gichuki 1994). In the 1940s, th
Page 470 and 471: Table 5.4. Determinants of soil con
Page 472 and 473: 5.3. Social capital, resource use,
Page 474 and 475: 6. Implications for policy and prog
Page 476 and 477: essential for the formation of exte
Page 478 and 479: BIBLIOGRPAHY Admassie, Y., L. I. Mw
Page 480 and 481: Gambetta, D. 1988. Can we trust tru
Page 482 and 483: Social capital and watershed develo
Page 484 and 485: Obare, G. A., S. W. Omamo, and J. C
Page 486 and 487: Washington D.C.: The World Bank Tem
Page 488 and 489: Appendix: A list of Contributors Ab
Page 490 and 491: Appendix: Projects Supported Under
Page 492: IFPRI Eastern Africa Food Policy Ne
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