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

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The producer and consumer prices are determined as composites of the domestic (basic) price and the export price and import price respectively as in models that use the Dervis et al. (1982) style. The prices of effective inputs formed in the nested production structure are determined in a similar fashion to those in ORANI. The key assumption in determining the basic price is that, in equilibrium, all firms make zero profit, achieved by setting the basic price equal to unit cost of production. As explained in Siriwardana (1996), the assumption of constant returns to scale in production and competitive pricing behavior in each of the economic activities ensures that zero pure profits are earned in equilibrium. The price of the domestic commodity is the sum of payments for intermediate inputs, labour services and capital payments, such that it is an average price of the costs of inputs. The implication of the basic price equation is that the basic value of good i is a weighted average of the prices of the inputs to the production of i, the weights being the cost shares of each input. Given the domestic price of a given sector’s commodity, the purchasing price for the domestic intermediate input produced in sector j used in sector i can be deduced. In ORANI-style models, the basic value of a commodity is the price paid to producers. The producer price in KEGEM is a combination of the basic (domestic) price with the export price in domestic currency. The composite producer price is, therefore, a weighted average of the domestic commodity and export commodity price. The aggregate world price for commodities is exogenous and fixed. For the period covered by this study, export taxes or subsidies were not an important policy instrument for the Kenyan government, hence, the export price equation differs with most CGE models in that it does not include the export subsidy (tax) variable. Quantities of a commodity sold locally are combined with quantities imported using a constant elasticity of substitution aggregation function to determine the total supply of the composite commodity. The domestic price is combined with the import price in domestic currency to determine the composite consumer price. It follows that the price of the composite commodity, is a weighted average of the import price and the local market price. Import prices, are equal to world price of imports, converted into Kenyan shillings at prevailing exchange rate, and adjusted for import taxes. The purchasers’ price for the imported intermediate commodity from sector j used as an input in sector i is given by a similar equation to that of imports, adjusted for indirect taxes. The introduction of exchange rate and exogenous world import prices in the imports price equation allows world prices to have a determining influence on Kenyan domestic prices. Due to the nested and separable nature of KEGEM, there are other important prices whose origins need to be explained. These are the prices of the composites that are formed in the assumed production technology. They are the composite prices for the effective intermediate input, effective primary input and effective labour input. It is worth remembering that these composite commodities have been assumed to involve independent decisions, that is, the separability assumption. Therefore, it is plausible that for each of these composites there is an independent price equation. The price for these effective units are formed in a manner similar to the ORANI-style models in particular the MONASH-MRF model (see Peter et al. 1996). For instance, the price of the composite intermediate commodity j used in the production process of sector i is a cost-weighted Divisia index of individual prices of intermediate inputs by source.
The value-added price is defined through an equation that captures prices of primary inputs. The effective primary factor price is a cost-weighted Divisia index of the rental price of capital and the average sectoral wage. The rental price of capital is endogenous and changes accordingly to clear the market for the fixed capital and is different compared to the price of capital goods or the price of assets used for investment in a given sector. The wage mechanism adopted for the Kenyan labour markets affect the values of equilibrium quantities for output and endogenous prices. However, in order to uphold consistency with price formation for the other composites in the production structure, the sectoral wage is determined by a weighted average of wages of different labour categories. That is, the average wage is a Divisia index of the wages of different labour categories. The wage rate of different occupations is derived through an indexation to the consumer price index. The consumer price index is computed through a weighting formula from the price of the composite domestic commodity, capturing both domestic and import prices. The consumer price index captures the differing influences that domestic and imported inputs in the different sectors have in the Kenyan economy. The producer price index is computed in KEGEM in a manner similar to the CPI. The producer price index captures both domestic and export prices. Equilibrium in the Products and Factor Markets To complete the model, equilibrium is imposed in product markets between demand and supply of domestic products. That is, the model ensures that demand equals supply for domestically produced commodities. The left-hand side of equilibrium equation in the product markets is the supply while the right hand side captures the total demand, which is made up of local demand of domestic output for intermediate inputs; demands for households’ consumption; demands for government purchases; demand for inputs to capital formation; and export supply. Unlike in ORANI, the final demands in KEGEM are composites of local and imported products. Total demand is the sum of all demands by households, government and other sectors for intermediate and investment use. Therefore, there is a market-clearing equation, ensuring equilibrium in every composite commodity markets. The condition for balance of trade equilibrium is formulated as part of the market equilibrium conditions in domestic currency. Tyler and Akinboade (1992) found that Keynesian closure could be applied to Kenya’s labour market, which assumes unlimited supply of labour at a fixed nominal wage so that the level of employment is determined endogenously by demand for labour. In this study, this closure is applied in the simulation of import tariffs. Essentially, employers are assumed to obtain as much labour as they would like to employ at prevailing real wage rates. With a wage indexation parameter of one, then the real wages of the different occupations are unaffected by the tariff changes. 8 This assumption is realistic for Kenya given that historically there have been high rates of unemployment. Moreover, real wages in Kenya have mainly been determined by bargaining processes rather than by changes in the labour market conditions. Besides the assumption on labour, it is also assumed that capital is fixed and is sector specific. 8 KEGEM is mix of linear and non-linear equations. Therefore, it is unlikely that there will be a perfect match between the change in the price index and the real wage given the outcome on nominal wage. A discrepancy in the change in the price index vis-à-vis the change in the real wage is acceptable and this is seen in the results discussed later in the paper.
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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
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
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: Savings Households’ savings are a
Page 143 and 144: Specifically, the Government polici
Page 145 and 146: Table 5: Calculated Tariff Rates (%
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
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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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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
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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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