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

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land pressure is high (Holden 1991), and may subsequently lead to a reduction in terrace investment. We also infer a positive relationship between education and terrace investments, as education embodies acquisition of managerial skills. Empirical evidence suggests that older farmers are more likely to reject conservation practices (Gould, Saupe, and Klemme 1989) and new productive practices (Bellon and Taylor 1993). Land tenure insecurity has been found to deter investment in resource management and conservation (Hayes, Roth, and Zepeda 1997; Reardon and Vosti 1992; Nowak 1987). Thus, we assume that farmers who perceive the security of their land tenure to be insufficient would be less willing to invest in terraces. Where credit markets are imperfect, a larger farm size, often related to wealth, may mean that such households are not so constrained by lack of liquidity that they cannot invest in land quality management. [CHANGES OK] Since the type of house variable is correlated with wealth and welfare of rural households, we expect it to influence soil conservation positively. The physical erosion potential has been shown to positively affect adoption decisions (Gould, Saupe, and Klemme 1989; Ervin and Ervin 1982). Consequently, we hypothesize the slope of cropland to be positively related to intensity of terrace structures. The net effect of diversification (out of agriculture) on land quality investments is theoretically not clear (Hayes, Roth, and Zepeda 1997; Gould, Saupe, and Klemme1989). Increased dependence on nonagricultural activities may lower the economic significance of soil erosion. Alternatively, off-farm income may ease the liquidity constraint for soil conservation investment or the purchase of soil fertility-enhancing inputs. According to Pagiola (1995), poor farmers may have more incentive to adopt sustainable farming practices than other farmers because future harm from degrading a resource is potentially unbounded. Yet if we consider that soil conservation in the form of terracing is labor-intensive, then we would expect wealthy farmers capable of overcoming the labor constraint to invest in more terracing, all else being equal. 2.3 Productivity as an outcome of terracing Investments in terraces reflect the agents’ expectations concerning growth in production. Land productivity can act as an indicator of growth in production since, in most cases, land is a major constraint in expansion of agricultural production ceteris paribus. In the soil conservation model presented in Figure 1, a productivity variable has been included as an outcome of terrace investment. Social capital may facilitate reciprocal insurance arrangements, thereby decreasing household or individual risk, or it may be used to facilitate access to credit or information that would lead to increased productivity and better marketing opportunities (Malucio, Haddad, and May 1999; Gerani 2001). We postulate, therefore, that crop output per acre will be a function of conventional factors of production in addition to the elements of social capital. 3. Research methodology In this section, the study design is discussed, including selection of the study areas, survey methods, measurement of variables, and methods of data analyses.
3.1 Selection of the study sites, sampling frame, and data collection methods The study areas are in agro-ecological zone IV, which ranges from semi-arid to semi-humid, depending on altitude. (Jaetzold and Schmidt 1983) The Lower Highland Zone has 115 to 145 growing days (a medium to medium/short growing season) and an annual mean temperature between 15°C and 18°C. The Upper Midland Zone has between 75 and 104 growing days (a short to very short growing season) and a mean annual temperature between 21°C and 24°C. Raising cattle and sheep and growing crops such as barley are recommended activities for the Lower Highland zone, while growing sunflower and maize crops are recommended for the Upper Midland zone. The data for this study come from a survey of rural households in Machakos and Taita-Taveta districts. Four sublocations were chosen in each district on the basis of terracing density; the number of terraces per acre and physical infrastructural endowments such as roads. Two sublocations with higher terracing density were selected in each district, one with a higher endowment of physical infrastructure and one with lower. Likewise, two sublocations with lower terracing density but higher and lower physical infrastructural endowments were also selected. A village was then selected randomly from each of the sublocations. The villages selected in Machakos District were King’elu, Kaliluni, Nzololo, Kyamuange, and Kekesunyi; in Taita-Taveta District, Mwakimoi, Mwakiki, and Kale were selected. The survey was carried out using a structured questionnaire in each district, with about 40 households chosen randomly in each village. In addition, village profiles using focus group discussions were conducted in an effort to find out about groups that exist in the villages and their relation to soil and water conservation. 3.2 Description and measurement of variables A description and measurement of the model variables are given in Table 3.1. In this study, the length of terrace per hectare 12 is a proxy for soil conservation investments. The enumerators asked each farmer about the number of terraces on each parcel of land and the average length. This was confirmed both by pacing out the length and by actual measurement. Because of the heterogeneous nature of the crops grown—maize, beans, bananas and, citrus, among others—the market value is used to obtain the aggregate crop output (CROPAC) for the whole farm, As well as a lagged value of crop output (LCROPAC), which is the value of crop output the year before the survey (2002). This is essential since there are always lags in effects, especially with farmers in agricultural systems. What is termed agricultural productivity (CROPHA) is crop output per acre. Other aspects such as livestock and trees are not included. Access costs (ACCESCOS) are the transport costs per person to the major market in each district in Kenya shillings. As for attributes of social capital or the extent of “connectedness,” 13 four measures of social capital are used. They 12 Terrace construction is the major soil conservation measure in the study area (Zaal 1999; Mwakubo 2003). 13 Gabre-Madhin (2001), for instance, measures social capital by the number of persons in the grain trade business that the trader knows personally.
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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
Page 394 and 395: of defined roles for CBAHWs within
Page 396 and 397: Interviews with veterinary officers
Page 398 and 399: The estimated model was of the form
Page 400 and 401: Gender remains a sensitive issue. P
Page 402 and 403: The most common ailments and diseas
Page 404 and 405: 4.3 Factors influencing the level o
Page 406 and 407: Table 9 -- Factors influencing the
Page 408 and 409: Table 10 - Factors determining the
Page 410 and 411: Table 12 -- Current mean numbers of
Page 412 and 413: Figure 4: Percentage of household h
Page 414 and 415: CBAHWs were the most utilized chann
Page 416 and 417: Users of veterinarians’ services
Page 418 and 419: Table 18 -- Levels of incomes and l
Page 420 and 421: higher average calving per cow, whi
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 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 470 and 471: Table 5.4. Determinants of soil con
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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