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

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Estimated covariances = 93 Number of obs = 106 95 Number of obs = 127 124 Number of obs = 183 Estimated autocorrelation = 0 Number of groups = 93 0 Number of groups = 95 0 Number of groups = 124 Estimated coefficients = 17 Obs per group: Min= 1 16 Obs per group: Min= 1 17 Obs per group: Min= 1 Avg = 1.264151 Avg = 1.503937 Avg = 1.644809 max = 3 max = 2 max = 2 Wald chi2 449.83 Wald chi2 21943.14 Wald chi2 1082.65 Log likelihood = -96.1581 Pr > chi2 = 0 -101.274 Pr > chi2 = 0 -157.803 Pr > chi2 = 0 Millet Sorghum Maize lnincacr Coef. Std. Err. z P>|z| Coef. Std. Err. z P>|z| Coef. Std. Err. z P>|z| ss2 -0.7147 0.3567 -2.004 0.045 3.1428 0.1466 21.434 0.000 (dropped) ss3 -0.8604 0.3828 -2.247 0.025 3.5175 0.1443 24.371 0.000 -0.1265 0.0263 -4.804 0.000 ss4 -0.0499 0.3429 -0.146 0.884 dropped due to collinearity dropped due to collinearity irrigatd dropped due to collinearity 0.0832 0.4542 0.183 0.855 0.6119 0.2126 2.878 0.004 logacres -0.9185 0.1203 -7.638 0.000 -0.1589 0.0525 -3.030 0.002 -0.2184 0.0488 -4.477 0.000 Family labour -0.2549 0.0983 -2.594 0.009 -0.2617 0.0448 -5.841 0.000 0.0577 0.0377 1.531 0.126 Labour2 0.0289 0.0092 3.143 0.002 0.0314 0.0046 6.807 0.000 -0.0076 0.0027 -2.855 0.004 invest 0.0342 0.0124 2.752 0.006 0.0902 0.0164 5.482 0.000 0.0552 0.0037 15.054 0.000 dd1 (dropped) (dropped) -0.2100 0.0888 -2.366 0.018 dd4 -1.2910 0.3909 -3.302 0.001 (dropped) -0.6477 0.0838 -7.733 0.000 dd5 -1.8974 0.6313 -3.005 0.003 (dropped) -1.0396 0.2622 -3.965 0.000 dd6 -1.3749 0.2994 -4.593 0.000 0.3095 0.0992 3.120 0.002 0.7457 0.1169 6.377 0.000 dd7 -1.3056 0.2861 -4.564 0.000 0.5586 0.1194 4.677 0.000 -0.7227 0.0811 -8.913 0.000 dd8 (dropped) 0.4283 0.1823 2.350 0.019 -0.1729 0.0906 -1.907 0.057 dd9 -4.1017 0.4666 -8.791 0.000 dropped due to collinearity -0.5425 0.0862 -6.293 0.000 dd10 -0.1786 0.2662 -0.671 0.502 -0.0531 0.1271 -0.418 0.676 -0.8658 0.0917 -9.442 0.000 dd11 -0.7450 0.2820 -2.642 0.008 0.0090 0.0906 0.099 0.921 -0.5901 0.1254 -4.705 0.000 _cons 5.8924 0.4715 12.497 0.000 (dropped) 3.9814 0.0849 46.897 0.000
Estimated covariances = 79 Number of obs = 98 46 Number of obs = 51 Estimated autocorrelation = 0 Number of groups = 79 0 Number of groups = 46 Estimated coefficients = 16 Obs per group: Min= 1 12 Obs per group: Min= 1 Avg = 1.387755 Avg = 1.196078 max = 2 max = 2 Wald chi2 538.99 Wald chi2 2233.12 Log likelihood = -71.9023 Pr > chi2 = 0 -14.834 Pr > chi2 = 0 Beans Simsim lnincacr Coef. Std. Err. z P>|z| Coef. Std. Err. z P>|z| ss2 0.0716 0.0624 1.146 0.252 0.4900 0.1015 4.828 0.000 ss3 dropped due to collinearity dropped due to collinearity ss4 dropped due to collinearity dropped due to collinearity irrigatd 0.4140 0.3186 1.299 0.194 (dropped) logacres -0.5232 0.0591 -8.853 0.000 -0.0324 0.1121 -0.289 0.772 Family labour -0.2157 0.0671 -3.215 0.001 0.3003 0.1193 2.518 0.012 Labour2 0.0334 0.0083 4.002 0.000 -0.0230 0.0119 -1.930 0.054 invest 0.0227 0.0051 4.480 0.000 0.0164 0.0026 6.417 0.000 dd1 -0.4629 0.2633 -1.758 0.079 0.9022 0.2526 3.572 0.000 dd4 (dropped) (dropped) dd5 (dropped) dropped due to collinearity dd6 0.2964 0.2665 1.112 0.266 dropped due to collinearity dd7 -0.5888 0.2617 -2.250 0.024 0.3209 0.2118 1.515 0.130 dd8 -0.3936 0.3745 -1.051 0.293 dropped due to collinearity dd9 -0.6716 0.2684 -2.502 0.012 dropped due to collinearity dd10 -0.8762 0.4535 -1.932 0.053 (dropped) dd11 -0.1934 0.4979 -0.388 0.698 -0.2594 0.2106 -1.232 0.218 _cons 4.0020 0.2811 14.239 0.000 2.7992 0.3737 7.490 0.000
Page 1 and 2:
Part One - Agricultural Productivit
Page 3 and 4:
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
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 and 74: Appendix 2. THE 5V’s PRIORITY CLA
Page 75: Appendix 5. Determinants of Product
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
Page 125 and 126: SEXHH SEXLUSER TSECUR VEGCP1 CHILDE
Page 127 and 128:
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
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
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APPENDIXES Appendix A: Districts of
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Questions and responses Government
Page 381 and 382:
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
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
Page 396 and 397:
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
Page 478 and 479:
BIBLIOGRPAHY Admassie, Y., L. I. Mw
Page 480 and 481:
Gambetta, D. 1988. Can we trust tru
Page 482 and 483:
Social capital and watershed develo
Page 484 and 485:
Obare, G. A., S. W. Omamo, and J. C
Page 486 and 487:
Washington D.C.: The World Bank Tem
Page 488 and 489:
Appendix: A list of Contributors Ab
Page 490 and 491:
Appendix: Projects Supported Under
Page 492:
IFPRI Eastern Africa Food Policy Ne
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