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

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CLASS V – VARIOUS WETLANDS • these either do not provide essential goods or services upon which many people depend or, they do provide such resources but these are so locally abundant that degradation or over-harvesting is unlikely in the foreseeable future; • they harbour no endangered, endemic or rare species, nor unique habitats; they represent the majority of the nations wetlands VICTOR wetlands are generally too big to be seriously threatened by wholesale drainage or permanent degradation by existing technology; this threat may however grow in future; these are! VICTIM wetlands are dispensable wetlands that could be ‘sacrificed’ or traded for other socioeconomic development uses e.g. agriculture or urban development; VANQUISHED wetlands are those that are either (1) totally converted to productive alternate uses e.g. dairy farming or irreversible urban development; these should remain converted: (2) those totally converted but not productively used; restoration should be applied where economically viable.
Appendix 5. Determinants of Productivity – Detailed Analysis Results Estimated covariances = 167 Number of obs = 187 115 Number of obs = 141 46 Number of obs = 54 Estimated autocorrelation = 0 Number of groups = 167 0 Number of groups = 115 0 Number of groups = 46 Estimated coefficients = 18 Obs per group: Min= 1 18 Obs per group: Min= 1 12 Obs per group: Min= 1 Avg = 1.245989 Avg = 1.397163 Avg = 1.296296 max = 3 max = 3 max = 2 Wald chi2 1116.39 Wald chi2 5938.43 Wald chi2 148.41 Log likelihood = -143.124 Pr > chi2 = 0 -114.224 Pr > chi2 = 0 -12.2101 Pr > chi2 = 0 Cassava Sweetpotato Groundnuts lnincacr Coef. Std. Err. z P>|z| Coef. Std. Err. z P>|z| Coef. Std. Err. z P>|z| ss2 0.0308 0.0631 0.489 0.625 -0.7694 0.1461 -5.265 0.000 0.3671 0.0940 3.904 0.000 ss3 -0.4612 0.1708 -2.700 0.007 -0.6458 0.1596 -4.048 0.000 dropped due to collinearity ss4 -0.9388 0.6152 -1.526 0.127 -0.9014 0.2035 -4.431 0.000 dropped due to collinearity irrigatd 0.5961 0.1193 4.996 0.000 0.6908 0.0900 7.673 0.000 dropped due to collinearity logacres -0.1193 0.0272 -4.386 0.000 -0.2637 0.0733 -3.599 0.000 -0.4218 0.1028 -4.104 0.000 Family labour 0.2536 0.0311 8.143 0.000 0.1036 0.0505 2.053 0.040 -0.1222 0.1107 -1.105 0.269 Labour2 -0.0204 0.0027 -7.462 0.000 -0.0087 0.0041 -2.103 0.035 0.0183 0.0092 1.989 0.047 invest 0.0039 0.0005 7.295 0.000 0.0274 0.0013 21.054 0.000 0.0001 0.0030 0.018 0.985 dd1 0.5057 0.0977 5.174 0.000 -2.0411 0.4910 -4.157 0.000 dropped due to collinearity dd4 -0.4977 0.0804 -6.189 0.000 -0.9275 0.4099 -2.263 0.024 dropped due to collinearity dd5 -1.1300 0.1091 -10.354 0.000 -2.1219 0.4062 -5.223 0.000 dropped due to collinearity dd6 0.3934 0.0901 4.369 0.000 -1.2315 0.3958 -3.111 0.002 0.8987 0.4120 2.181 0.029 dd7 0.0334 0.0742 0.450 0.653 -1.0731 0.3996 -2.686 0.007 0.5354 0.5512 0.971 0.331 dd8 0.8114 0.1332 6.090 0.000 0.1751 0.4094 0.428 0.669 0.7024 0.4765 1.474 0.140 dd9 -0.0093 0.1232 -0.075 0.940 0.0822 0.3875 0.212 0.832 0.9621 0.3605 2.669 0.008 dd10 -0.3199 0.1033 -3.096 0.002 -1.2246 0.4141 -2.957 0.003 -0.2066 0.3841 -0.538 0.591 dd11 0.2348 0.0715 3.282 0.001 -0.8152 0.3916 -2.082 0.037 0.3971 0.3783 1.050 0.294 _cons 4.2641 0.1142 37.327 0.000 5.2222 0.4238 12.322 0.000 3.1584 0.4708 6.708 0.000
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
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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
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 and 58: estimates are remarkably consistent
Page 59 and 60: FSI - Percentage by District Distri
Page 61 and 62: was corrected using the White-Huber
Page 63 and 64: utilization for the household. Howe
Page 65 and 66: The nature of the structures to con
Page 67 and 68: impact of irrigation on horticultur
Page 69 and 70: growing population. Wetland protect
Page 71 and 72: APPENDICES Appendix 1. The Wetlands
Page 73: Appendix 2. THE 5V’s PRIORITY CLA
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
Page 109 and 110: Table 8: Regression Results on Maiz
Page 111 and 112: was classified into three categorie
Page 113 and 114: Table 9: Tobit Analysis with Enviro
Page 115 and 116: 5.0 CONCLUSIONS AND POLICY IMPLICAT
Page 117 and 118: 5.5 Access to Market A number of fa
Page 119 and 120: FAO (2003b). “Women and Food Secu
Page 121 and 122: Omiti John and Paul Obunde (2002).
Page 123 and 124: Annex 1: Pearson Correlation Coeffi
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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
Page 337 and 338:
The objectives of DRS were to popul
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increasing participation. Thus, the
Page 341 and 342:
Table 2. Perceived change in benefi
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unsatisfactory (Table 8). Flaws in
Page 345 and 346:
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
Page 377 and 378:
APPENDIXES Appendix A: Districts of
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Questions and responses Government
Page 381 and 382:
Questions and responses Lack of coo
Page 383 and 384:
CHAPTER TEN Animal Health Service D
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• Individuals are selected for tr
Page 388 and 389:
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
Page 398 and 399:
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
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
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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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