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

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Figure 5b. Monthly average wholesale prices for wheat (birr/100 kgs., 1999 and 2001) maize 1999 maize 2001 180 90 160 80 140 70 120 60 100 50 80 40 60 30 40 20 january february march april may june july august september october november december 20 10 0 0 Figure 5c. Monthly average wholesale prices for maize (birr/100kgs., 1999 and 2001) Source: Central Statistical Authority, various issues. When grain prices are substantially reduced, it discourages farmers from applying chemicals to prevent pest attacks, leading to even larger crop losses than usual. This is because the marginal benefit as a result of chemical treatment could be less than the marginal cost of the treatment. For example, during the 2001/02 crop season, maize prices were reduced by as much as 80 percent, as a result of a 40 percent increase in output. Under such circumstances, crop prices might be so unattractive that farmers would not even pay the transport charges to take their grain to the nearest market place for sale. 7.2. Regression Results Table 13 presents the Tobit regression results. Note that nonbag storage capacities were not significant. Education also was not significant in explaining variations in the dependent variable. Similarly, farmers’ expectations of grain loss were found to be not statistically significant.
Table 13: Regression results (Tobit estimates: the dependent variable is the proportion of sales during the first quarter to total sales during the year) Variables Coefficient t-ratio Constant 0.7694* 6.296 FSIZE 0.0135** 2.119 SEX -0.1407*** -1.926 EDUC 0.0014 0.303 CHEM -0.0762** -2.440 STCAP -0.0011 -0.183 TLU -0.0084** -2.547 PRICDIF -0.3026** -2.429 EXPLOSS 0.0984 1.081 TAXLOAN 0.0001* 3.150 Sigma 0.2598 Number of samples 292 Log likelihood function -30.9562 *, **, *** Significant at 1 percent, 5 percent and 10 percent levels, respectively. A total of six variables turned out to be significant in explaining the variations in the proportion of crop sales during the first quarter to total sales by households. Moreover, with the exception of the SEX variable, the signs of all of these variables are also according to a priori expectations, leading to the following conclusions: (i) (ii) (iii) (iv) (v) (vi) The pressure on households, triggered by large family sizes, to meet nongrain purchased consumption needs tends to force farmers into immediate crop sales; Female household heads are more likely to sell crops immediately during the first quarter than male household heads. This may be ascribed to fewer options available to female-headed households in terms of resorting to other sources of cash income (for example, livestock sales); Application of chemicals (insecticides) reduces the risk of pest attack and the tendency to instant sales; Livestock ownership reduces the pressure to meet cash needs by selling crops, because households tend to resort to sale of livestock and its products rather than crop sales; Intercrop differences are important explanatory variables for households’ behavior in sales decisions; that is, farmers who mainly grow maize (a more susceptible crop) and wheat are more likely to sell quickly than those who mainly grow teff (a less susceptible crop); and Households’ need for immediate cash to meet various obligations explains why they are willing to dispose of their grain crops when prices are lowest.
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Part One - Agricultural Productivit
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I. Introduction Agricultural Produc
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came about from expansion of cultiv
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study, therefore, limited itself to
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Land allocation and yields of 12 cr
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Table 6: Key economic variables for
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local seed in absolute terms and th
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Table 11: Crosscutting priority con
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Table 13: General constraints to ma
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These results clearly demonstrate t
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Table 18: Crosscutting constraints
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V. Policy Implications The findings
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References Appleton, Simon (2001).
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1.0 BACKGROUND 1.1 Introduction Low
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egins with a summary of the literat
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Source: National Wetlands Conservat
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shillings (§37-38). Every landowne
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Similarly, Howard (1995) used socia
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Uganda may well have more than a qu
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factors that explain household leve
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of inputs 18 , pests and diseases,
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(PMA p. 27). It also requires impro
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agriculturalists, who still do not
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to have covered 30,000 ha. During t
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4.0 RESEARCH METHODOLOGY The breadt
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• What is the current extent of w
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Figure 2. Changes in Sources of Com
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Figure 5. Proportion of Households
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estimates are remarkably consistent
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FSI - Percentage by District Distri
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was corrected using the White-Huber
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utilization for the household. Howe
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The nature of the structures to con
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impact of irrigation on horticultur
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growing population. Wetland protect
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APPENDICES Appendix 1. The Wetlands
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Appendix 2. THE 5V’s PRIORITY CLA
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Appendix 5. Determinants of Product
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Estimated covariances = 79 Number o
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International Food Policy Research
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Scherr, Sara J., 1999b. Poverty-env
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Land Tenure, Agricultural Productiv
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1.3 Statement of the problem Land s
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In order to achieve these objective
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densely populated Nyeri and Kakameg
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Figure 3: Conceptual Model Type of
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Figure 4: Location of the Study Dis
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By 2001, land demarcation and regis
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3.4 Survey Design The survey was un
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3.5.3 Model of Environmental Degrad
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questionnaire (Figure 8). Prominent
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Figure 10: Availability of hired la
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Figure 13 shows the level of cultiv
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joint significance test on the 4 dr
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Table 8: Regression Results on Maiz
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was classified into three categorie
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Table 9: Tobit Analysis with Enviro
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5.0 CONCLUSIONS AND POLICY IMPLICAT
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5.5 Access to Market A number of fa
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FAO (2003b). “Women and Food Secu
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Omiti John and Paul Obunde (2002).
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Annex 1: Pearson Correlation Coeffi
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SEXHH SEXLUSER TSECUR VEGCP1 CHILDE
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Part two - Agricultural Markets
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Market Liberalisation and Agricultu
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farms show annual fluctuations, wit
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Figure 2: Recent trends in domestic
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5. The Model The interest of this s
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sources for each sector. α IM ji a
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Savings Households’ savings are a
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The value-added price is defined th
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Specifically, the Government polici
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Table 5: Calculated Tariff Rates (%
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disincentive to farmers. Inability
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competitiveness. The second one is
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Table 7: Wage Rates and Labour Inco
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Similar simulation is undertaken in
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References Block, S. and C.P. Timme
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Tyler, G. J. and Akinboade, O. 1992
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(A.10) ai ∑ P ϖ P i=1,...,3; j =
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(A.32) price (A.33) P Q = P ( 1+ td
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Table A.2: Variables of KEGEM Varia
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VA A i Efficiency parameter in valu
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CHAPTER FIVE Post-Liberalization Ma
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As alluded to earlier, initial agri
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directly to dairy farmers as animal
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to engage in this new role, the gov
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2.0 RESEARCH METHODOLOGY 2.1 Overal
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markets with minor gaps in data ser
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Price-series correlations are conve
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Migori Awendo Postliberalization 1,
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model depends on whether or not the
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Table 6b--Unit root tests for price
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Table 8a--Unit root tests for OLS r
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3.3 The Role of Infrastructure and
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Table 13--Reported distances from t
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Table 15--Reported maize storage pr
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Table 17--Traders’ perception of
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3.3.6.2 Awareness of the Liberaliza
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Retailer (open-air market) 21 13 7
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3.4 Maize Marketing Costs Traders w
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3.4.4 License and Market Fees Accor
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5.Develop farmers’ and traders’
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Coulter, J., and J. A. F. Compton.
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Meilink, A. H. 1987. Food consumpti
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Figure 1 Maize surplus and deficit
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Figure 3 Trends in Maize Prices 199
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Price per 90kg bag (Kshs) Mbeere Di
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Figure 4 Modes of transporting maiz
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Figure 6: Limitations to storage ca
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Figure 8: Problems experienced in a
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CHAPTER SIX Grain Marketing in Addi
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A third, related explanation argues
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educed marketing costs related to p
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1.4. Research questions This study
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1.6. Organization of the report Thi
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the cases, respectively (Table 2.4)
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Brokers believe that most regional
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There is also a close relationship
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Table 2.14: Buyers’ methods for i
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Source: Survey, 2002. Table 2.18: D
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Table 2.22: Method used to grade di
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Table 2.25: Access to credit broker
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It has been reported that grain pur
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3. GRAIN RETAILERS Retailers serve
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Like brokers, retailers use cash or
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Table 3.11: Buyers’ information a
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Table 3.14: Retailers’ views of g
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Getting reliable price information
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Table 4.4: How do you set a sales p
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Table 4.7: Means of settling disput
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a.m. The survey included wholesale
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Table 5.3: Instability index of dai
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Table 5.7: Seasonality index of who
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Figure 5.3: Ratio of wholesale to r
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Table 5.8: Results of stationary te
Page 273 and 274: Table 5.10: Summary of Granger caus
Page 275 and 276: holiday sales. The results of the r
Page 277 and 278: Table 6.1: Storage capacity of the
Page 279 and 280: Intermarket grain flow is coordinat
Page 281 and 282: • a legal, regulatory, and enforc
Page 283 and 284: REFERENCES Al-Hassen, R., A. Dorwar
Page 285 and 286: Seppala, P. 1998. Decisive liberali
Page 287 and 288: achieve some welfare objective. The
Page 289 and 290: Annex Table 2.10: Have you faced di
Page 291 and 292: Annex Table 2.21: Do you consider p
Page 293 and 294: Annex Table 3.3: Cost structure of
Page 295 and 296: Annex Table 4.2: Complementary acti
Page 297 and 298: CHAPTER SEVEN Post-Harvest Grain Ma
Page 299 and 300: only (see Abebe 2000: 80-83). That
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Page 303 and 304: occur at all stages of post-harvest
Page 305 and 306: Endowment & access to Resources (e.
Page 307 and 308: Figure 2: The Study Areas (shaded a
Page 309 and 310: (6) β i = β 0 λ i , 0
Page 311 and 312: Intercrop differences Liquidity con
Page 313 and 314: eplace old animals (19 percent of h
Page 315 and 316: Table 5. Number and capacity of gra
Page 317 and 318: Table 7b.Estimated grain loss durin
Page 319 and 320: 7.1.3. Grain Marketing Practices an
Page 321 and 322: 1.8 Producers' price 1.6 1.4 1.2 1
Page 323: next season, grain prices tend to b
Page 327 and 328: of grain production was reportedly
Page 329 and 330: instruments to mitigate price risks
Page 331 and 332: Coulter, J. and G. Onumah, (2002).
Page 333 and 334: Appendix: Supplementary Tables Appe
Page 335 and 336: CHAPTER EIGHT Collective Action in
Page 337 and 338: The objectives of DRS were to popul
Page 339 and 340: increasing participation. Thus, the
Page 341 and 342: Table 2. Perceived change in benefi
Page 343 and 344: unsatisfactory (Table 8). Flaws in
Page 345 and 346: Table 14. Measures of wealth status
Page 347 and 348: Results from Regression Analysis Ta
Page 349 and 350: However, to maintain these benefits
Page 351 and 352: Table 18. Determinants of participa
Page 353 and 354: _______ 1981. Common property and c
Page 355 and 356: Management Regulations and Enforcem
Page 357 and 358: In theory, under PFM, the governmen
Page 359 and 360: 3.2 Desk study The desk study invol
Page 361 and 362: Table 1: Number and gender of indiv
Page 363 and 364: Poverty Increase in number of fishe
Page 365 and 366: Table 5: Responses given by various
Page 367 and 368: wages after the catch is sold (see
Page 369 and 370: 70 60 No of respondents 50 40 30 20
Page 371 and 372: 4.2.3 Lack of attention to social i
Page 373 and 374: 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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