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

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5.2.5. Characteristics of the Household Sample With Respect to Diversity of Wetlands Utilization and Food Security As mentioned previously, household level indices were created for Diversity of Wetlands Utilization (WDI) and for Food Security (FSI). The Food Security index was based on the following three survey questions. How many meals do you usually eat every day How frequently does your family get animal protein (E.g. meat, milk eggs) How frequently do you experience staple food shortages 37 1= One, 2=Two, 3=Three, 4=Three plus tea 42, 1=special occasions only 2=At least once a month, 3=At least once a week, 4= Daily 43 1=Food is never enough, 2=Every season, 3= At least once every year, 4= Only in bad years, 5=Never The responses from the three questions were summed, resulting in an index with possible answers ranging from 3 to 13. These answers were then clustered into an index with four possible values. 3 - 6=1 7 - 8=2 9 - 10=3 11-13=4 Distributed in the following manner FSI Frequency Percent Cumulative Percent 1 37 13.45 13.45 2 96 34.91 48.36 3 115 41.82 90.18 4 27 9.82 100.00 Total 275 100.00 The distribution of the food security index varied significantly, however, between districts within the study area, with Kumi, Kaberamaido, Soroti and Masindi being the most food secure and Kayunga, Apac and Lira being the most insecure.
FSI – Percentage by District District 1 2 3 4 Total Apac 25.81 38.71 32.26 3.23 100 Kaberamaido 6.25 31.25 43.75 18.75 100 Kamuli 14.29 46.43 35.71 3.57 100 Kayunga 46.15 15.38 23.08 15.38 100 Kumi 7.69 19.23 46.15 26.92 100 Lira 19.61 49.02 31.37 0 100 Masindi 0 21.43 64.29 14.29 100 Nakasongola 4.17 37.5 45.83 12.5 100 Pallisa 10.53 36.84 47.37 5.26 100 Soroti 5.66 28.3 52.83 13.21 100 Total 14.016 32.409 42.264 11.311 100 Pearson chi2(27) = 56.7354 Pr = 0.001 Likelihood-ratio chi2 (27) = . Cramer's V = 0.2622 gamma = 0.1763 ASE = 0.061 Kendall's tau-b = 0.1368 ASE = 0.047 In a comparable manner an index for diversity of wetland utilization was created for each household based on the number of various uses to which the household derived from the wetlands. Options included irrigation, hunting, fishing, fuel wood and building/craft material collection. (Since virtually every household collected water from the wetland for household use, water collection was not considered a separate use.) The potential range of values is from zero to four where four equals four or more uses. The Distribution of the WDI across districts is shown in the table below. Clearly there were significant differences in distribution across locations, with Nakasongola, Kaberamaido and Kayunga exhibiting the least diversity of use and Kumi, Pallisa and Soroti exhibiting the most. Table 3. Distribution of Wetlands Utilization by District WDI District 0 1 2 3 4 Total Average Apac 6.06 9.09 24.24 18.18 42.42 100 2.8179 Kaberamaido 6.25 12.5 25 31.25 25 100 2.5625 Kamuli 6.9 10.34 17.24 20.69 44.83 100 2.8621 Kayunga 0 31.25 43.75 6.25 18.75 100 2.125 Kumi 0 3.7 22.22 14.81 59.26 100 3.2961 Lira 1.72 6.9 25.86 24.14 41.38 100 2.9656 Masindi 0 6.25 37.5 25 31.25 100 2.8125 Nakasongola 12.5 37.5 8.33 33.33 8.33 100 1.8747 Pallisa 0 9.09 9.09 36.36 45.45 100 3.1815 Soroti 1.75 10.53 5.26 42.11 40.35 100 3.0878 Total 3.68 12.04 19.4 26.76 38.13 100 2.8364 Pearson chi2(40) = 100.9866 Pr = 0.000 Likelihood-ratio chi2 (40) = . Cramer's V = 0.2906 gamma = 0.0523 ASE = 0.057 Kendall's tau-b = 0.0422 ASE = 0.046
Page 1 and 2:
Part One - Agricultural Productivit
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I. Introduction Agricultural Produc
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came about from expansion of cultiv
Page 7 and 8: study, therefore, limited itself to
Page 9 and 10: Land allocation and yields of 12 cr
Page 11 and 12: Table 6: Key economic variables for
Page 13 and 14: local seed in absolute terms and th
Page 15 and 16: Table 11: Crosscutting priority con
Page 17 and 18: Table 13: General constraints to ma
Page 19 and 20: These results clearly demonstrate t
Page 21 and 22: Table 18: Crosscutting constraints
Page 23 and 24: V. Policy Implications The findings
Page 25 and 26: References Appleton, Simon (2001).
Page 27 and 28: 1.0 BACKGROUND 1.1 Introduction Low
Page 29 and 30: egins with a summary of the literat
Page 31 and 32: Source: National Wetlands Conservat
Page 33 and 34: shillings (§37-38). Every landowne
Page 35 and 36: Similarly, Howard (1995) used socia
Page 37 and 38: Uganda may well have more than a qu
Page 39 and 40: factors that explain household leve
Page 41 and 42: of inputs 18 , pests and diseases,
Page 43 and 44: (PMA p. 27). It also requires impro
Page 45 and 46: agriculturalists, who still do not
Page 47 and 48: to have covered 30,000 ha. During t
Page 49 and 50: 4.0 RESEARCH METHODOLOGY The breadt
Page 51 and 52: • 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: estimates are remarkably consistent
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 and 104: Figure 10: Availability of hired la
Page 105 and 106: Figure 13 shows the level of cultiv
Page 107 and 108: 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
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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
Page 486 and 487:
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
Page 492:
IFPRI Eastern Africa Food Policy Ne
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