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

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Table 7b--Unit root tests for first differences of prices in the postliberalization era Market p Criterion ADF test statistic Null hypothesis (unit root present) Kiritiri (no trend) 1 AIC, HQC -8.373 Reject Kiritiri (with trend) 1 AIC, HQC -8.365 Reject Siakago (no trend) 0 AIC, SBC, HQC -9.779 Reject Siakago (with trend) 0 AIC, SBC, HQC -9.812 Reject Kitale (no trend) 0 SBC, HQC -7.134 Reject Kitale (with trend) 0 SBC, HQC -7.083 Reject Nairobi (no trend) 0 AIC, SBC, HQC -6.116 Reject Nairobi (with trend) 0 AIC, SBC, HQC -6.101 Reject Migori (no trend) 0 AIC, SBC, HQC -9.143 Reject Migori (with trend) 0 AIC, SBC, HQC -9.082 Reject Awendo (no trend) 0 AIC, SBC, HQC -8.420 Reject Awendo (with trend) 0 AIC, SBC, HQC -8.360 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. To test for cointegration, residuals were obtained from regressions of the price in market i, P i , t on the price in market j, P j , t as given already in equation 2. The residuals were then tested for the presence of unit roots. If the t-value for δ 1 is greater than the critical 95 percent level ADF statistic, the residuals are integrated of order zero and the prices are cointegrated. Again as noted earlier, in theory, if market i is cointegrated with market j, then market j should be cointegrated with market i. In practice, however, test results may differ. For this reason the cointegration test was repeated for all markets by interchanging the left-hand and right-hand price variables. Results are presented in Tables 8a and 8b with the first column showing the dependent variable in the first regression and the first row representing the dependent variable of the second regression. According to Engle and Granger (1991) a link between market i and market j is said to be segmented if there is no cointegration in either direction, or rather if regressing series i on series j and regressing j on i both yield nonstationary residuals. This implies that if there is cointegration in at least one direction, then the link is considered to be integrated. Following this argument, the cointegration tests show that for the preliberalization sample the hypothesis of cointegration of OLS residuals is rejected only for the Kiritiri- Siakago, Kitale-Nairobi, Kitale-Migori, and Nairobi-Migori links. This implies that all other markets were not integrated in the preliberalization period. The result highlights the importance of the restriction that limited the amount of grain that could be moved out of a district in the era of market controls. In the postliberalization period the hypothesis of no long-term relations among pairs of markets is rejected in all cases except for the Nairobi- Awendo, Siakago-Migori, and Siakago-Awendo. We concluded that only the three market links listed were not cointegrated in the postliberalization period considered in this study. Dividing the sample into preliberalization and postliberalization subsamples and carrying out the appropriate cointegration tests led us to observe that most markets became cointegrated in the postliberalization era. We conclude that liberalization improved the transmission of price signals among various markets in the country, thereby strengthening the links between markets.
Table 8a--Unit root tests for OLS residuals in the preliberalization era Kiritiri Siakago Kitale Nairobi Migori Awendo Kiritiri ----- Reject Cannot reject Cannot reject Cannot reject Cannot reject Siakago Reject ----- Cannot reject Cannot reject Cannot reject Cannot reject Kitale Cannot reject Cannot reject ----- Reject Reject Cannot reject Nairobi Cannot reject Cannot reject Cannot reject ----- Reject Cannot reject Migori Cannot Reject Cannot reject Reject Reject ----- Cannot reject Awendo Cannot Cannot Cannot Cannot Cannot ----- reject reject reject reject reject Source: Authors’ survey, 2001. Table 8b--Unit root tests for OLS residuals in the postliberalization era Kiritiri Siakago Kitale Nairobi Migori Awendo Kiritiri ----- Reject Reject Reject Reject Reject Siakago Reject ----- Reject Reject Cannot reject Cannot reject Kitale Reject Reject ----- Reject Reject Reject Nairobi Reject Reject Reject ----- Cannot reject Cannot reject Migori Reject Cannot Reject Reject ----- Reject reject Awendo Reject Cannot Reject Cannot Reject ----- reject reject Source: Authors’ survey, 2001. Having established cointegration of various markets in the postliberalization era, we proceeded to assess whether price movements follow well-defined paths--that is, start around demand or production centers and then spread around the country using the Granger causality test as explained in section 2.3.3. The results of this test are presented in Table 9. The reader is reminded that Granger causality tests were undertaken for those market links where cointegration in the postliberalization era had been established. Table 9--F-statistics for the Granger causality tests Market i Market j Kiritiri Siakago Kitale Nairobi Migori Awendo Kiritiri - 22.28 3.41 10.67 3.23 4.84 Siakago 21.67 - 4.47 5.46 X X Kitale 2.85 1.35 - 26.95 9.65 10.76 Nairobi 4.91 6.03 27.14 - 7.77 X Migori 0.63 X 15.52 9.39 - 13.79 Awendo 2.57 X 9.51 X 10.70 -
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
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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
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 and 184: model depends on whether or not the
Page 185: Table 6b--Unit root tests for price
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)
Page 235 and 236: 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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