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

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Table 5.9: Results of integration tests Crop type Wholesale-retail market 1. Teff Adda teff -6.04 Wollenkomi teff -8.08 Bechena teff -7.23 2. Wheat Wheat first -5.43 Wheat second -7.81 Wheat third -6.54 3. Maize White maize -5.98 Maize mixed -6.96 The results of the integration test show that the wholesale and retail markets are integrated. In other words, there a exists long-run and stable price relationship between the two markets for the sample grain products. If there is interaction between a pair of markets, then there must be Granger causality—that is, one series may cause another and vice versa. Thus, the next step is to conduct such a test in order to determine the direction of causality. Theoretically, if a time series variable P wit influences another series variable P rit , then there exists a Granger causality relationship between these two variables in which P wit Granger causes P rit and vice versa. Formally, this test can be conducted based on the following model. (i) Pwit = ψ 11 ΔP + ... + ψ nΔP + ψ ΔP + + ψ nΔP −ζ [ P −αP −δ] + ε wit− 1 wit−n 21 ... 1 rit−1 2 wit−n 1 wit−1 rit−1 it (5.4) (ii) Pr ψ 31 ΔP + ... + ψ3 nΔP + ψ Pwit n P [ P P ] rit n 41Δ 1 + ... + ψ4 Δ −ζ2 −α −δ + ε − − − wit−1 2t (5.5) = it rit 1 wit−n rit−1 The hypotheses to be tested to determine the Granger causality relationship between wholesale and retail prices are: (a)(P rit does not Granger Cause P wit ); and (b) (Pwit does not Granger Cause Prit) Based on the integration test, an attempt was made to perform a causality test for the two markets, and the results are given in Table 5.10.
Table 5.10: Summary of Granger causality tests P wit does not Granger cause P rit Crop type 1. Teff Adda teff 0.42 0.29 (0.66) (0.75) Wollenkomi teff 0.35 0.33 (0.71) (0.72) Bechena teff 0.84 14.40*** (0.43) (0.00) 2. Wheat Wheat first 11.64*** 2.56* (0.00) (0.08) Wheat second 16.37*** 5.24*** (0.00) (0.01) Wheat third 29.77*** 0.01 (0.00) (0.99) 3. Maize White maize 10.32*** 0.97 (0.00) (0.98) Mixed maize 11.75*** 1.78 (0.00) (0.17) P rit does not Granger cause P wit Note: The unparenthesized figures are F-statistics, while the figures in parentheses are p- values. *** Significant at 1% or less. * Significant at 10%. Table 5.10 reveals interesting information about the direction of causality between the two markets. The causality directions are from wholesale to retail for both white and mixed maize. Thus, the wholesale markets lead the retail markets for maize. With regard to wheat, there is a two-way interaction or causation between the two series.The influence of the wholesale market is stronger, however, than that of the retail market in all grades of wheat. This shows that wholesale markets do not receive adequate feedback from the retail markets, especially in the case of maize. The results paint a different picture for teff, where there is a weak causality relationship (not statistically significant) virtually in all types. The only exception is Bechena teff in which the retail market leads the wholesale market. Teff markets do not appear to have strong causal relationships.
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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
Page 221 and 222: Figure 8: Problems experienced in a
Page 223 and 224: CHAPTER SIX Grain Marketing in Addi
Page 225 and 226: A third, related explanation argues
Page 227 and 228: educed marketing costs related to p
Page 229 and 230: 1.4. Research questions This study
Page 231 and 232: 1.6. Organization of the report Thi
Page 233 and 234: the cases, respectively (Table 2.4)
Page 235 and 236: Brokers believe that most regional
Page 237 and 238: There is also a close relationship
Page 239 and 240: Table 2.14: Buyers’ methods for i
Page 241 and 242: Source: Survey, 2002. Table 2.18: D
Page 243 and 244: Table 2.22: Method used to grade di
Page 245 and 246: Table 2.25: Access to credit broker
Page 247 and 248: It has been reported that grain pur
Page 249 and 250: 3. GRAIN RETAILERS Retailers serve
Page 251 and 252: Like brokers, retailers use cash or
Page 253 and 254: Table 3.11: Buyers’ information a
Page 255 and 256: Table 3.14: Retailers’ views of g
Page 257 and 258: Getting reliable price information
Page 259 and 260: Table 4.4: How do you set a sales p
Page 261 and 262: Table 4.7: Means of settling disput
Page 263 and 264: a.m. The survey included wholesale
Page 265 and 266: Table 5.3: Instability index of dai
Page 267 and 268: Table 5.7: Seasonality index of who
Page 269 and 270: Figure 5.3: Ratio of wholesale to r
Page 271: Table 5.8: Results of stationary te
Page 275 and 276: holiday sales. The results of the r
Page 277 and 278: Table 6.1: Storage capacity of the
Page 279 and 280: Intermarket grain flow is coordinat
Page 281 and 282: • a legal, regulatory, and enforc
Page 283 and 284: REFERENCES Al-Hassen, R., A. Dorwar
Page 285 and 286: Seppala, P. 1998. Decisive liberali
Page 287 and 288: achieve some welfare objective. The
Page 289 and 290: Annex Table 2.10: Have you faced di
Page 291 and 292: Annex Table 2.21: Do you consider p
Page 293 and 294: Annex Table 3.3: Cost structure of
Page 295 and 296: Annex Table 4.2: Complementary acti
Page 297 and 298: CHAPTER SEVEN Post-Harvest Grain Ma
Page 299 and 300: only (see Abebe 2000: 80-83). That
Page 301 and 302: of processing as an important post-
Page 303 and 304: occur at all stages of post-harvest
Page 305 and 306: Endowment & access to Resources (e.
Page 307 and 308: Figure 2: The Study Areas (shaded a
Page 309 and 310: (6) β i = β 0 λ i , 0
Page 311 and 312: Intercrop differences Liquidity con
Page 313 and 314: eplace old animals (19 percent of h
Page 315 and 316: Table 5. Number and capacity of gra
Page 317 and 318: Table 7b.Estimated grain loss durin
Page 319 and 320: 7.1.3. Grain Marketing Practices an
Page 321 and 322: 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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