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

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Table 5.4. Determinants of soil conservation investments using 2SLS Machakos Taita- Combined Taveta Variables coefficient t-statistic coefficient t-statistic coefficient t-statistic ln SLOPE -0.71 -1.57 -0.138E-03 -0.11 -0.302E-02 -0.99 ln TENURE -0.177E-03 -0.04 0.31 0.85 -0.133E-02 -0.44 ln DISTH -0.290E-03 -0.11 -0.514E-03 -0.44 -0.469E-03 -0.46 ln LCROPAC 0.19 1.57 0.796E-01 2.06** 0.374E-01 0.69 ln EDUC 0.151E-02 0.83 0.180E-02 5.75*** 0.122E-02 2.44** EXT -0.219E-02 -1.12 -0.346E-02 -2.13** -0.293E-02 -1.35 ln WEALTH -0.828E-01 -0.13 -0.30 -1.61 -0.44 -1.25 SEX -1.02 -0.22 -0.93 -1.91* -1.75 -2.23** ln AGE -0.569E-03 -0.36 1.16 1.95* 0.157E-03 0.14 FAROR 0.875E-01 0.16 -0.263E-01 -0.45 0.17 1.08 ln HHS 0.79 0.42 1.15 2.75*** 0.13 0.18 ln FAMCA 0.71 1.57 0.39 3.97*** 0.662E-02 1.27 ln INC -0.68 -0.50 0.284E-01 0.49 -0.17 -1.06 ln ACCESCOS -0.232 E -03 -0.18 0.21 0.32 -0.133E-02 -0.85 ERODE 0.405E-03 0.14 0.210E-02 1.60 0.686E-03 0.52 ln CWORK -0.72 -0.31 -0.174E-02 -1.63 0.238E-03 0.15 ln MEDENS 11.55 1.36 1.51 0.23 3.05 0.50 ln MEDIV -4.25 -0.91 -1.41 -0.27 2.51 0.28 ln PARTIC -2.33 -0.46 1.41 0.43 -4.94 -0.52 ln COGNIT 5.22 0.90 -1.30 -1.10 2.03 1.54 LOC - - - - 2.73 4.43*** PERCEP -0.119E-01 -0.01 -0.13 -0.42 -0.52 -0.95 IMR 3.82 5.77*** 3.65 12.364*** 3.72 19.83*** N 152 144 296 *Significant at P
(Shultz 1964; Pudasiani 1983; Welch 1978; and Idachaba 1994). It also improves the farmer’s management capabilities (Gould, Saupe, and Klemme 1989). Other studies have also found a positive association between education and adoption of conservation technology (Earle, Rose, and Brownlea 1979; Ervin and Ervin 1982). Thus, a sufficient level of education increases the intensity of soil conservation. In addition to the capital returns generated by education, it also increases participation in social activities, which is a positive externality. . Education is a variable that is within the control of the policymaker. Efforts can thus be made to improve the education standards of farmers, possibly through the extension service and through local NGOs. Training may need to go beyond simple information for the adoption of new practices to include training in farm management—how to run a successful farm operation using the more complex soil conservation practices. The lack of significance of education for Machakos may have to do with the proximity to off-farm jobs in Nairobi. Education increases the opportunity costs of farmer’s time by increasing the likelihood of getting a high- paying job if one is available nearby. Sex is negative and significant for the combined data set and also for Taita-Taveta. This implies that female-headed households invest more in soil conservation than maleheaded ones. Bird-David et al. (1998) argue that female-headed households tend to enjoy a broader base of labor division and contribution of resources by members of the household. They also have a greater degree of control over the household resources and feel a greater degree of security. In addition, the authors argue that no significant differences were detected in the extent to which extension agents visited different household types. Nevertheless, Mwakubo (2003) contends that women are exposed to extension services more than men. This is because they are often members of women’s groups, while men’s groups are rare. Such groups are often the entry points for extension services—the place where extension messages are extended. Extension staff usually participate in public meetings called barazzas, which are sponsored by the provincial administration. Women are more likely to attend these meetings than men and to pay more attention to extension messages. Because women are keen to learn and make use of the knowledge gained, they may be better land managers. Age is positive and significant for Taita-Taveta. The combined data set has the expected sign, although it is not significant. Correlation of age with soil conservation investments possibly shows that terracing is a very expensive undertaking, which older people are more likely to undertake because they have more farming experience 21 and also more accumulated wealth with which to finance terrace construction (Nyang 1999). A bivariate correlation of age of the principal household member and number of rooms (a proxy for wealth) shows that it is positive (0.194) and significant (0.05). But where land markets are absent and poverty is rampant, age raises the time preference (high discount rate) of the poor, which may lower the desire for further conservation (Shiferaw and Holden 1998). Finally, household size and farm size per capita have a positive and significant effect on soil conservation investments in Taita-Taveta. A possible explanation is that the larger the household size, the more abundant the labor available for soil conservation investments. In addition, and more importantly, subsistence needs are rather high, which can be met through increased crop production made possible via increased soil conservation investments. The lack of significance for Machakos may be explained by the availability of other livelihood opportunities, such as off-farm jobs in Nairobi. We are also of the view that there is less land pressure in Taita-Taveta, compared with Machakos. Moreover, this variable (farm size per capita) is expected to be negative. 21 This suggests that farmers have to learn about the effects of a new technology before adopting it entirely. This is important if risks of the new technology are unknown and hence there is a need to know its risk profile.
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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
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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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Page 422 and 423: Table 21 -- CBAHWs’ ranking of sp
Page 424 and 425: epresentative of livestock keepers
Page 426 and 427: Despite the restriction imposed by
Page 428 and 429: veterinarians. Such associations co
Page 430 and 431: References Akabwai, D., V. Shean, a
Page 432 and 433: Johnson, P. J., and C. Chahuares. 1
Page 434 and 435: Appendix 1: The Logistic Procedure
Page 436 and 437: Social Capital and Sustainable Agri
Page 438 and 439: 1.1 Soil conservation programs and
Page 440 and 441: 1.3 Research Objectives and Hypothe
Page 442 and 443: Institutional and Policy factors -
Page 444 and 445: land pressure is high (Holden 1991)
Page 446 and 447: include density of membership in gr
Page 448 and 449: then summed up according to increas
Page 450 and 451: Social capital, resource use, and a
Page 452 and 453: Table 4.4 Farmers’ perception of
Page 454 and 455: Table 4.5: Empowerment and politica
Page 456 and 457: Table 4.8: Indicators of collective
Page 458 and 459: Table 4.10: Comparison of means of
Page 460 and 461: 5. The influence of social capital
Page 462 and 463: especially when considered on an ad
Page 464 and 465: households may pay less attention t
Page 466 and 467: Table 5.3 Determinants of terracing
Page 468 and 469: and Gichuki 1994). In the 1940s, th
Page 472 and 473: 5.3. Social capital, resource use,
Page 474 and 475: 6. Implications for policy and prog
Page 476 and 477: 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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