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

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Table 6a--Unit root tests for price series in the preliberalization era Market p Criterion ADF test statistic Null hypothesis (unit root present) Kiritiri (no trend) 0 AIC, SBC, HQC -1.563 Cannot reject Kiritiri (with trend) 0 AIC, SBC, HQC -1.680 Cannot reject Siakago (no trend) 0 AIC, SBC, HQC -1.422 Cannot reject Siakago (with trend) 0 AIC, SBC, HQC -1.505 Cannot reject Kitale (no trend) 0 AIC, SBC, HQC -2.144 Cannot reject Kitale (with trend) 0 SBC, HQC -2.110 Cannot reject Nairobi (no trend) 0 AIC, SBC, HQC 0.026 Cannot reject Nairobi (with trend) 1 AIC, SBC, HQC -1.965 Cannot reject Migori (no trend) 0 SBC, HQC -1.645 Cannot reject Migori (with trend) 2 AIC, SBC, HQC -2.833 Cannot reject Awendo (no trend) 0 AIC, SBC, HQC -0.933 Cannot reject Awendo (with trend) 0 AIC, SBC, HQC -2.235 Cannot reject 95% critical value for the ADF statistic (no trend) -2.997 95% critical value for the ADF statistic (with -3.662 trend) The next step involved differencing the price series and repeating the unit root test on the price differences. The equations estimated were: = i, α + 0 δ 1 P + m i, t − 1 ∑ = n + = α m Δ m Pi, t −m U (6) t Δ 2 P t Δ 2 P = i, t α + 0 δ 1 P t (7) i 1 m 1 m n m 1 , − + ∑ = = + α m Δ m P + i, t −m β 1 T U t The model selection criteria suggest orders of augmentation of between zero and two with most regressions being of order zero. In all cases, and regardless of the order of augmentation chosen, the computed ADF statistics are well above the 95 percent critical value of the test given at the last two rows of Tables 7a and 7b. Hence the hypothesis that the first differences of the price series have unit roots is firmly rejected. From the evidence provided by this test, it was concluded that the price series are integrated of order one--that is, all price series are I(1). Once the order of economic integration was established, the next step was to test for cointegration of the price series.
Table 6b--Unit root tests for price series in the postliberalization era Market p Criterion ADF test statistic Null hypothesis (unit root present) Kiritiri (no trend) 1 AIC, HQC -3.434 Reject Kiritiri (with trend) 0 SBC, HQC -3.682 Reject Siakago (no trend) 0 AIC, SBC, HQC -1.973 Cannot reject Siakago (with trend) 0 AIC, SBC, HQC -2.387 Cannot reject Kitale (no trend) 2 AIC, HQC -2.838 Cannot reject Kitale (with trend) 2 AIC, SBC, HQC -3.142 Cannot reject Nairobi (no trend) 2 AIC, HQC -2.115 Cannot reject Nairobi (with trend) 2 AIC, HQC -2.400 Cannot reject Migori (no trend) 0 AIC, SBC, HQC -2.153 Cannot reject Migori (with trend) 0 AIC, SBC, HQC -2.426 Cannot reject Awendo (no trend) 0 AIC, SBC, HQC -1.590 Cannot reject Awendo (with trend) 0 AIC, SBC, HQC -1.845 Cannot reject 95% critical value for the ADF statistic (no trend) -2.902 95% critical value for the ADF statistic (with -3.472 trend) Source: Authors’ survey, 2001. Table 7a--Unit root tests for first differences of prices in the preliberalization era Market p Criterion ADF test statistic Null hypothesis (unit root present) Kiritiri (no trend) 0 AIC, SBC, HQC -4.652 Reject Kiritiri (with trend) 0 AIC, SBC, HQC -4.566 Reject Siakago (no trend) 0 AIC, SBC, HQC -4.255 Reject Siakago (with trend) 0 AIC, SBC, HQC -4.187 Reject Kitale (no trend) 0 AIC, SBC, HQC -4.198 Reject Kitale (with trend) 0 AIC, SBC, HQC -4.163 Reject Nairobi (no trend) 0 AIC, SBC, HQC -2.317 Cannot reject Nairobi (with trend) 1 AIC, SBC, HQC -2.164 Cannot reject Migori (no trend) 0 AIC, SBC, HQC -3.803 Reject Migori (with trend) 0 AIC, SBC, HQC -3.777 Reject Awendo (no trend) 0 AIC, SBC, HQC -4.476 Reject Awendo (with trend) 0 AIC, SBC, HQC -4.314 Reject 95% critical value for the ADF statistic (no trend) -3.004 95% critical value for the ADF statistic (with trend) -3.633 Source: Authors’ survey, 2001.
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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
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 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: model depends on whether or not the
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
Page 195 and 196: Table 17--Traders’ perception of
Page 197 and 198: 3.3.6.2 Awareness of the Liberaliza
Page 199 and 200: Retailer (open-air market) 21 13 7
Page 201 and 202: 3.4 Maize Marketing Costs Traders w
Page 203 and 204: 3.4.4 License and Market Fees Accor
Page 205 and 206: 5.Develop farmers’ and traders’
Page 207 and 208: Coulter, J., and J. A. F. Compton.
Page 209 and 210: Meilink, A. H. 1987. Food consumpti
Page 211 and 212: Figure 1 Maize surplus and deficit
Page 213 and 214: Figure 3 Trends in Maize Prices 199
Page 215 and 216: Price per 90kg bag (Kshs) Mbeere Di
Page 217 and 218: Figure 4 Modes of transporting maiz
Page 219 and 220: Figure 6: Limitations to storage ca
Page 221 and 222: Figure 8: Problems experienced in a
Page 223 and 224: CHAPTER SIX Grain Marketing in Addi
Page 225 and 226: A third, related explanation argues
Page 227 and 228: educed marketing costs related to p
Page 229 and 230: 1.4. Research questions This study
Page 231 and 232: 1.6. Organization of the report Thi
Page 233 and 234: 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
Page 482 and 483:
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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