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

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Table 5.12: Regression results of the determinants of maize price Dependent variable logarithm of wholesale price of maize Coef. Std. error t P > |t| 95% conf. interval Log of the average opening price 0.956 0.037 25.690 0.000 0.88 3 Log of the closing price of the previous day 0.056 0.037 1.496 0.137 - 0.01 8 Dummy for pay period -0.003 0.003 -0.924 0.357 - 0.00 9 Dummy for holiday -0.002 0.004 -0.426 0.671 - 0.01 0 Constant -0.050 0.018 -2.760 0.007 - 0.08 6 Heteroskedastic-consistent standard errors Number of observations = 122 Observationadjusted R2 = 0.99 Prob > F = 0.000 1.030 0.129 0.003 0.006 -0.014 6. LARGE-SCALE OPERATORS 6.1. Wholesalers The survey at the central market has shown that specialized wholesale operators are not a major part of the trading system. We made attempts, however, to contact grain wholesalers operating outside the central grain market. A total of five companies, namely Hawas Agri- Business Plc., Ambassel Trading House, Ethiopian Grain Trading Enterprise (EGTE, a parastatal formerly known as the Agricultural Marketing Corporation), Ethiopian Amalgamated Ltd., and Guna Trading House Share Company, were approached to provide information about their operations. Storage facilities and capacities vary significantly between the different companies. The EGTE has the largest storage capacity and is the major provider of storage services in the country, whereas Ambassel has no storage of its own (Table 6.1).
Table 6.1: Storage capacity of the companies (quintals) Ethiopia Capacity Hawas Ambassel EGTE Amalgamated Guna Own store 60,000 0 8.3 million 40,000 400,000 Rented store n.a. 60,000 0 92,000 50,000 Note: n.a. means not available. All the companies buy their stocks from surplus-producing areas without going to the central grain market in Addis. They buy directly from producers, traders, or agents in the different rural markets. Some of them also float tenders to buy grain. Two companies, EGTE and Ethiopia Amalgamated, were involved in importing wheat. Wheat and maize, the major crops handled, are sold to donors such as the World Food Programme (WFP), Euro Aid, and various nongovernmental organizations (NGOs). The Disaster Prevention and Preparedness Commission (DPPC) also gets some of its supplies from the companies. Other major customers are the Ministry of Defense and flourmills. The grain is cleaned, graded, and fumigated in some cases. Since teff is mainly bought by urban households and there are no large-scale processing or milling factories, the trading companies have minimal interest in the crop. Grain trade is the major activity for EGTE, whereas the other companies undertake other activities as well, including merchandise trade, fertilizer trade, and export of pulses and oilseeds. The companies enter the grain trade in response to tenders or requests from the major buyers. These companies may carry out no purchase in some years or in most parts of a given year. For instance, only one company (Ambassel) bought maize in 2001/02. The quantity of grain handled is also smaller in some years. Even EGTE has sharply reduced its food grain purchases in recent years and diverted its resources to purchasing oilseeds and pulses for export. It has been reported that maize and sorghum are exported in years of bumper harvests. For instance, Guna exported about 200,000 quintals of sorghum and maize to Sudan in 2000/01. Contract enforcement is a major problem of the trading companies. Three of the five companies had faced disputes in the preceding three years. One of the companies (EGTE) lost 104 million birr over the same period, while the other (Hawas) lost 1.7 million. Grain prices at the central market start to increase whenever one or more of the companies are about to buy grain. On the other hand, prices decline if they are staying out of the market. The volatility of the market is partly induced by the occasional involvement of the companies. It appears that large-scale wholesalers operating on a more permanent and consistent basis would have a stabilizing effect on the market.
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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
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 and 272: Table 5.8: Results of stationary te
Page 273 and 274: Table 5.10: Summary of Granger caus
Page 275: holiday sales. The results of the r
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
Page 323 and 324: next season, grain prices tend to b
Page 325 and 326: 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
Page 484 and 485:
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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