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

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Table 3: Sectoral Parameters Agriculture Manufacturing Service Elasticity in intermediate input CES 0.80 0.60 0.40 Elasticity in value added CES 0.50 0.70 0.60 Elasticity in composite labour CES 0.50 0.50 0.50 Elasticity in import CES 0.80 0.60 0.40 Elasticity in export CET 1.30 0.80 0.30 Source: Average of equivalent values used in Fargeix and Sadoulet (1994) for Ecuador, Dervis et al. (1982) for a semi-industrialised Turkish economy, Dorosh (1996) for Madagascar and Dorosh et al. (1996) for Niger. Table 4: Household Consumption Parameters (Income Elasticities) 11 Uhh1 Uhh2 Uhh3 Rhh1 Rhh2 Rhh3 Rhh4 Rhh5 Rhh6 Rhh7 Agriculture 0.90 0.70 0.50 0.90 0.80 0.70 0.60 0.50 0.50 0.70 Manufacturing 1.10 1.30 1.40 1.10 1.20 1.30 1.40 1.50 1.60 1.30 Service 0.70 0.80 1.10 0.70 0.80 0.90 1.00 1.10 1.20 0.80 Frisch parameter -4.00 -3.00 -2.00 -4.50 -4.00 -3.50 -3.00 -2.50 -2.00 -3.50 Source: Fargeix and Sadoulet (1994) and Lluch et al. (1977). The Trade Policy Simulation The policy simulation in KEGEM is not a complete removal of all trade tariffs but a calculated reduction in the tariff rate. From the input-output and social accounting matrix data of 1986, the effective import duty rates were an average of 16.4 percent and 25.2 percent for agricultural and manufactured imports, respectively. 12, 13 Table 5 shows the rates computed by averaging the tariff rates (import duty divided by import values). 11 Uhh1 = Low income urban households; Uhh2 = Middle income urban households; Uhh3 = High income urban households; Rhh1 = Rural households holding less than 0.5 ha. and with little additional income; Rhh2 = Rural households holding 0.5 ha. with substantial additional income; Rhh3 = Rural households holding greater than 0.5 ha. but less than 1.0 ha. with little additional income; Rhh4 = Rural households (holding less than 0.5 ha. but less than 1.0 ha. with substantial additional income; Rhh5 = Rural households holding greater than 1.0 ha. but less than 8.0 ha.; Rhh6 = Rural households holding greater than 8.0 ha. (small farms only); Rhh7 = Other rural households. 12 These import duty rates are calculated by the simple formula: tariff rate for sector i = total duty collections in sector i/total imports of sector i. 13 These tariff rates are very similar to those calculated using National Accounts data as import duty divided by the import values.
Table 5: Calculated Tariff Rates (%) from Import Duty Collections in Selected Years 1986 1989 1990 1992 1993 1994 1999 Food and Animals 15.0 17.0 5.0 2.0 4.0 6.2 32.6 Bev & Tobacco 92.0 84.0 73.0 24.0 22.0 18.8 13.9 Crude Materials 29.0 22.0 20.0 10.0 16.0 13.9 13.0 Mineral Fuels 11.0 8.0 7.0 0.23 8.0 20.7 15.1 Oils and Fats 2.6 6.4 0.6 15.5 24.1 22.1 9.0 Chemicals 14.4 16.5 17.8 10.2 10.9 12.8 5.4 Manufacturers 27.0 20.7 17.6 14.2 16.7 20.0 13.9 Equipment 17.0 12.0 12.7 8.7 16.6 18.1 11.3 Miscellaneous 17.0 14.8 13.7 8.4 12.7 11.4 11.4 Average Rate (Total 16.5 13.8 12.5 7.6 12.7 16.0 12.8 Duty Collections) Source: Statistical Abstracts, various issues The effective tariff rates computed from the input-output tables and social accounting matrix tables for 1986 were close to those obtained from a similar computation using Kenya’s national accounts information (Table 5). 14 We use the rates from the inputoutput tables and the social accounting matrix for 1986 as the starting point for this study as indicated earlier. In this simulation we investigate the implications of reducing the manufactured goods tariffs by 40 percent to an effective rate of 15 percent from the average of 25.2 percent and a reduction by a similar amount of the agricultural commodity tariffs to 10 percent from an effective rate of 16.4 percent. Impacts on GDP Growth The results of this simulation are shown in Table 6. At the macro level, trade liberalisation through lower import tariffs contributes half a percentage point improvement in the real GDP. As expected, output fell in the manufacturing sector by 1.6 percent due to import competition with the lower tariffs. Agricultural output, which was expected to benefit from cheaper inputs derived from trade liberalisation, improved marginally by 0.04 percent. Trade liberalisation in Kenya therefore results in expected outcome, that is, lower tariffs hurt the import-competing manufacturing sector while benefiting export-producing sectors such as agriculture. While there is no disaggregation of agricultural sector in the model, intuitively the losing sub-sectors are food crops (maize, wheat and rice) and the gainers are exports crop sector (tea, coffee and horticulture). As noted earlier, per capita food production declined in the postliberalisation period while export crops, except for coffee, performed reasonably well over that period. The most likely explanation of these outcomes is that food crops sector faced stiffer competition from food imports from neighbouring countries but export crops benefit from cheaper inputs. The result that the agricultural sector does still experience some positive growth may be then explained by the value added in the export crops sector being larger than the value added of the food crops. In spite of the postulation about the food sector and export 14 The high increase of tariff levels for agricultural products is as a result of elimination of non-tariffs following Kenya’s being a signatory to the WTO Agreement on Agriculture in 1995 and consequently adoption of tariffication as required by the Agreement
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
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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
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
Page 129 and 130: Market Liberalisation and Agricultu
Page 131 and 132: farms show annual fluctuations, wit
Page 133 and 134: Figure 2: Recent trends in domestic
Page 135 and 136: 5. The Model The interest of this s
Page 137 and 138: sources for each sector. α IM ji a
Page 139 and 140: Savings Households’ savings are a
Page 141 and 142: The value-added price is defined th
Page 143: Specifically, the Government polici
Page 147 and 148: disincentive to farmers. Inability
Page 149 and 150: competitiveness. The second one is
Page 151 and 152: Table 7: Wage Rates and Labour Inco
Page 153 and 154: Similar simulation is undertaken in
Page 155 and 156: References Block, S. and C.P. Timme
Page 157 and 158: Tyler, G. J. and Akinboade, O. 1992
Page 159 and 160: (A.10) ai ∑ P ϖ P i=1,...,3; j =
Page 161 and 162: (A.32) price (A.33) P Q = P ( 1+ td
Page 163 and 164: Table A.2: Variables of KEGEM Varia
Page 165 and 166: VA A i Efficiency parameter in valu
Page 167 and 168: CHAPTER FIVE Post-Liberalization Ma
Page 169 and 170: As alluded to earlier, initial agri
Page 171 and 172: directly to dairy farmers as animal
Page 173 and 174: to engage in this new role, the gov
Page 175 and 176: 2.0 RESEARCH METHODOLOGY 2.1 Overal
Page 177 and 178: markets with minor gaps in data ser
Page 179 and 180: Price-series correlations are conve
Page 181 and 182: Migori Awendo Postliberalization 1,
Page 183 and 184: model depends on whether or not the
Page 185 and 186: Table 6b--Unit root tests for price
Page 187 and 188: Table 8a--Unit root tests for OLS r
Page 189 and 190: 3.3 The Role of Infrastructure and
Page 191 and 192: Table 13--Reported distances from t
Page 193 and 194: Table 15--Reported maize storage pr
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Table 17--Traders’ perception of
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3.3.6.2 Awareness of the Liberaliza
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Retailer (open-air market) 21 13 7
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3.4 Maize Marketing Costs Traders w
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3.4.4 License and Market Fees Accor
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5.Develop farmers’ and traders’
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Coulter, J., and J. A. F. Compton.
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Meilink, A. H. 1987. Food consumpti
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Figure 1 Maize surplus and deficit
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Figure 3 Trends in Maize Prices 199
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Price per 90kg bag (Kshs) Mbeere Di
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Figure 4 Modes of transporting maiz
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Figure 6: Limitations to storage ca
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Figure 8: Problems experienced in a
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CHAPTER SIX Grain Marketing in Addi
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A third, related explanation argues
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educed marketing costs related to p
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1.4. Research questions This study
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1.6. Organization of the report Thi
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the cases, respectively (Table 2.4)
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Brokers believe that most regional
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There is also a close relationship
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Table 2.14: Buyers’ methods for i
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Source: Survey, 2002. Table 2.18: D
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Table 2.22: Method used to grade di
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Table 2.25: Access to credit broker
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It has been reported that grain pur
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3. GRAIN RETAILERS Retailers serve
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Like brokers, retailers use cash or
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Table 3.11: Buyers’ information a
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Table 3.14: Retailers’ views of g
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Getting reliable price information
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Table 4.4: How do you set a sales p
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Table 4.7: Means of settling disput
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a.m. The survey included wholesale
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Table 5.3: Instability index of dai
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Table 5.7: Seasonality index of who
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Figure 5.3: Ratio of wholesale to r
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Table 5.8: Results of stationary te
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Table 5.10: Summary of Granger caus
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holiday sales. The results of the r
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Table 6.1: Storage capacity of the
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Intermarket grain flow is coordinat
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• a legal, regulatory, and enforc
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REFERENCES Al-Hassen, R., A. Dorwar
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Seppala, P. 1998. Decisive liberali
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achieve some welfare objective. The
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Annex Table 2.10: Have you faced di
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Annex Table 2.21: Do you consider p
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Annex Table 3.3: Cost structure of
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Annex Table 4.2: Complementary acti
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CHAPTER SEVEN Post-Harvest Grain Ma
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only (see Abebe 2000: 80-83). That
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of processing as an important post-
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occur at all stages of post-harvest
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Endowment & access to Resources (e.
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Figure 2: The Study Areas (shaded a
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(6) β i = β 0 λ i , 0
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Intercrop differences Liquidity con
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eplace old animals (19 percent of h
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Table 5. Number and capacity of gra
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Table 7b.Estimated grain loss durin
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7.1.3. Grain Marketing Practices an
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1.8 Producers' price 1.6 1.4 1.2 1
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next season, grain prices tend to b
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Table 13: Regression results (Tobit
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of grain production was reportedly
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instruments to mitigate price risks
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Coulter, J. and G. Onumah, (2002).
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Appendix: Supplementary Tables Appe
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CHAPTER EIGHT Collective Action in
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The objectives of DRS were to popul
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increasing participation. Thus, the
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Table 2. Perceived change in benefi
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unsatisfactory (Table 8). Flaws in
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Table 14. Measures of wealth status
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Results from Regression Analysis Ta
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However, to maintain these benefits
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Table 18. Determinants of participa
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_______ 1981. Common property and c
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Management Regulations and Enforcem
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In theory, under PFM, the governmen
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3.2 Desk study The desk study invol
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Table 1: Number and gender of indiv
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Poverty Increase in number of fishe
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Table 5: Responses given by various
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wages after the catch is sold (see
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70 60 No of respondents 50 40 30 20
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4.2.3 Lack of attention to social i
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5.3 Regulate the construction of re
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REFERENCES Allison, E. H., and P. M
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APPENDIXES Appendix A: Districts of
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Questions and responses Government
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Questions and responses Lack of coo
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CHAPTER TEN Animal Health Service D
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• Individuals are selected for tr
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Makueni district was selected becau
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1.5 Justification of the study The
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more sustainable (Leonard 1993; Uma
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of defined roles for CBAHWs within
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Interviews with veterinary officers
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The estimated model was of the form
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Gender remains a sensitive issue. P
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The most common ailments and diseas
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4.3 Factors influencing the level o
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Table 9 -- Factors influencing the
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Table 10 - Factors determining the
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Table 12 -- Current mean numbers of
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Figure 4: Percentage of household h
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CBAHWs were the most utilized chann
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Users of veterinarians’ services
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Table 18 -- Levels of incomes and l
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higher average calving per cow, whi
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Table 21 -- CBAHWs’ ranking of sp
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epresentative of livestock keepers
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Despite the restriction imposed by
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veterinarians. Such associations co
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References Akabwai, D., V. Shean, a
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Johnson, P. J., and C. Chahuares. 1
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Appendix 1: The Logistic Procedure
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Social Capital and Sustainable Agri
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1.1 Soil conservation programs and
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1.3 Research Objectives and Hypothe
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Institutional and Policy factors -
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land pressure is high (Holden 1991)
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include density of membership in gr
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then summed up according to increas
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Social capital, resource use, and a
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Table 4.4 Farmers’ perception of
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Table 4.5: Empowerment and politica
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Table 4.8: Indicators of collective
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Table 4.10: Comparison of means of
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5. The influence of social capital
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especially when considered on an ad
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households may pay less attention t
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Table 5.3 Determinants of terracing
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and Gichuki 1994). In the 1940s, th
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Table 5.4. Determinants of soil con
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5.3. Social capital, resource use,
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6. Implications for policy and prog
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essential for the formation of exte
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BIBLIOGRPAHY Admassie, Y., L. I. Mw
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Gambetta, D. 1988. Can we trust tru
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Social capital and watershed develo
Page 484 and 485:
Obare, G. A., S. W. Omamo, and J. C
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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
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IFPRI Eastern Africa Food Policy Ne
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