i AN ASSESSMENT OF TOMATO PRICE VARIABILITY IN LUSAKA ...

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Table 2.5 cont’d Area Province Market share Farmer Size Seasonality (Supply months) Manyika Lusaka 0.061 0.7 4.59 Small farmers: most farmers are in the low deciles. Mwembeshi Lusaka 0.05 1.12 5.77 All types of farmers: the farmers are almost evenly spread out in all deciles with the 5th and the 9th deciles having more observations. Makeni Lusaka 0.048 0.67 4.41 Small farmers: most of the farmers are in the lower deciles. Chalimbana Lusaka 0.047 1.31 6.01 All types of farmers: the farmers are almost evenly spread out across all deciles but with mode Mkushi Farm Block in the 7th and 8th deciles. Central 0.043 2.81 7.27 Large farmers: most of the farmers are in the top two deciles. 24 Highest sales during high price month of February 2007, also December 2007 to January 2008, but maintained a substantial amount of sales in the low price period of March 2007 to August 2007. Sales heavily concentrated in low price months – May to September 2007. Sales heavily concentrated in low price months of July to September 2007. Low price months - June to Aug 2007. High price month – December 2007 Most sales concentrated during high price months – February to March 2007 and December 2007 to February 2008. Weighted Average Price Received (ZMK/kg) 1,093 928 921 945 1382
Table 2.6 cont’d Area Province Market share Farmer Size Seasonality (Supply months) Nkolonga Central 0.031 2.36 7.54 Large farmers: most of the farmers are in the top three Farmers in Kapiri Mposhi district deciles. Central 0.027 2.25 7.27 Large farmers: most of the farmers are in the top four deciles. Mwalumina Lusaka 0.022 1.16 5.78 Medium farmers: most farmers are located in the median deciles between 5 and 8 with more in the 8th Average for all areas 25 Nearly all sales occurred during high price months – November 2007 to January 2008. Most sales during high price months – October to November 2007, January 2008, and January to February 2007. Main peak during low price months of June to September 2007; second peak high price months of December 2007 to January 2008. Weighted Average Price Received (ZMK/kg) 1,168 - 0.68 - - decile. - - 1,079 Source: Food Security Research Project – Tomato Supply data 2007/2008 1 1 is the smallest possible mean decile and 10 is the largest possible mean decile. 1,372 890
Page 1 and 2: AN ASSESSMENT OF TOMATO PRICE VARIA
Page 3 and 4: DEDICATION This thesis is dedicated
Page 5 and 6: to the Dean, School of Agricultural
Page 7 and 8: 3.4.1 Variability and Predictabilit
Page 9 and 10: LIST OF TABLES Table 2.1: Budget Sh
Page 11 and 12: LIST OF FIGURES Figure 1.1: Geograp
Page 13 and 14: 1.1 Background CHAPTER 1 INTRODUCTI
Page 15 and 16: (Ksh 1 )7.5 billion) of total veget
Page 17 and 18: chains and independent supermarkets
Page 19 and 20: towards lowering the costs, encoura
Page 21 and 22: Chapter 5 concludes the thesis with
Page 23 and 24: andomized cluster sample design. Th
Page 25 and 26: 2.2 Methods With these three sets o
Page 27 and 28: perceptions of farmers and traders
Page 29 and 30: Table 2.2: Budget Share of Differen
Page 31 and 32: Table 2.3: Budget Share of Differen
Page 33 and 34: Figure 2.1: Channel Map for Tomato
Page 35: Table 2.4: Key Characteristics of T
Page 39 and 40: Figure 2.2: Monthly Soweto Wholesal
Page 41 and 42: from all 150 supply areas while cha
Page 43 and 44: Table 2.7: Retail Outlet Market Sha
Page 45 and 46: Table 2.9: Retail Outlet Market Sha
Page 47 and 48: Freshmark mostly prefers to have la
Page 49 and 50: With the dual procurement system th
Page 51 and 52: Compared to Soweto market which had
Page 53 and 54: During this period, tomato prices w
Page 55 and 56: Figure 2.4: Tomato Pricing at Whole
Page 57 and 58: Table 2.11: Mean Tomato Prices for
Page 59 and 60: 2.5 Summary and Conclusions 2.5.1 I
Page 61 and 62: In the period January 2007 to June
Page 63 and 64: CHAPTER 3 TOMATO PRICE VARIABILITY
Page 65 and 66: In the hot wet season, disease prev
Page 67 and 68: patterns differ across markets, red
Page 69 and 70: case of a flood, its effects could
Page 71 and 72: 3.2 Hypothesis Testing The level of
Page 73 and 74: Table 3.2: Description of Data Used
Page 75 and 76: Coefficient of Variation= Where;
Page 77 and 78: Where; P t - the observed tomato pr
Page 79 and 80: A look at price variability in each
Page 81 and 82: For further comparison of the mean
Page 83 and 84: Figure 3.2: Comparison of the Ratio
Page 85 and 86: Figure 3.4: Comparison of Condition
Page 87 and 88:
thereby making the farmers more con
Page 89 and 90:
d. The absence of cold chain system
Page 91 and 92:
depend on local suppliers for their
Page 93 and 94:
The provision of market information
Page 95 and 96:
upon arrival in the market. Lower q
Page 97 and 98:
- Assets used in tomato production,
Page 99 and 100:
Tomato price data used for analysis
Page 101 and 102:
4.4 The Monte Carlo Model The Basel
Page 103 and 104:
CF Fixed conversion factor of 37.
Page 105 and 106:
- Seedling costs - Seed costs - Fie
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differences were due to differences
Page 109 and 110:
Table 4.2: Farmer Characteristics B
Page 111 and 112:
Group 1 Table 4.4: Basic Informatio
Page 113 and 114:
farmers can in practice suffer a to
Page 115 and 116:
4.5.2 Simulation Results for the Di
Page 117 and 118:
Scenario 1: Increased Sales Frequen
Page 119 and 120:
knowledge of what their yields and
Page 121 and 122:
Table 4.12: The Effect of Supply Ch
Page 123 and 124:
Table 4.13: Production of Low and H
Page 125 and 126:
quality; when supplies are high in
Page 127 and 128:
etter farmers would attempt to have
Page 129 and 130:
CHAPTER 5 CONCLUSION This study was
Page 131 and 132:
top twelve tomato supply areas acco
Page 133 and 134:
Freshpikt and Rivonia are the main
Page 135 and 136:
on prediction errors from a price p
Page 137 and 138:
absence of a cold chain system, the
Page 139 and 140:
price variability, the expectation
Page 141 and 142:
In the scenario analysis of increas
Page 143 and 144:
price variability affects the diffe
Page 145 and 146:
facilitate the provision of low cos
Page 147 and 148:
APPENDICES 135
Page 149 and 150:
i. What type of farmers do they pre
Page 151 and 152:
Taipei, Taiwan Table A2.3. Model Su
Page 153 and 154:
Colombo, Sri Lanka A2.7. Model Summ
Page 155 and 156:
APPENDIX 3. Graphs of Price Predict
Page 157 and 158:
Figure A3.3. Price Prediction Resid
Page 159 and 160:
Figure A3.5. Price Prediction Resid
Page 161 and 162:
9. Name of Main Respondent (if diff
Page 163 and 164:
SECTION 3 - HARVEST AND SALES OF CR
Page 165 and 166:
SECTION 4 - PLANTING AND HARVEST PA
Page 167 and 168:
155 _______________ _______________
Page 169 and 170:
5.2 Planted Seedlings Phase Field #
Page 171 and 172:
PHASE 2 - FIELD PREPARATION 5.5 Enu
Page 173 and 174:
5.7 Irrigation prior to transplanti
Page 175 and 176:
4=Spraying 5=Weeding 6=Placement of
Page 177 and 178:
Field # Please list all the types o
Page 179 and 180:
that you used in your tomato produc
Page 181 and 182:
Trailer Van/light truck Borehole Bo
Page 183 and 184:
Field # Time from 1 st harvest Phas
Page 185 and 186:
Second Field Field # Time from 1 st
Page 187 and 188:
Field # Time from 1 st harvest Phas
Page 189 and 190:
Second field: 8.0 Harvesting and Ma
Page 191 and 192:
APPENDIX 5. Distribution of Sampled
Page 193 and 194:
Figure A6.2. Distributions for Cost
Page 195 and 196:
Figure A6.4. Distributions for Cost
Page 197 and 198:
APPENDIX 7. Histograms of Farmer Pr
Page 199 and 200:
Figure A7.3. Baseline Scenario: His
Page 201 and 202:
Figure A7.5. Increased Sales Freque
Page 203 and 204:
Figure A7.7. Increased Sales Freque
Page 205 and 206:
Figure A7.9. Supply Chain Improveme
Page 207 and 208:
Figure A7.11. Supply Chain Improvem
Page 209 and 210:
Figure A7.13. Scenario on Quality o
Page 211 and 212:
Figure A7.15. Scenario on Quality o
Page 213 and 214:
Figure A7.17. Scenario on Low Quali
Page 215 and 216:
Figure A7.19. Scenario on Low Quali
Page 217 and 218:
BIBLIOGRAPHY 205
Page 219:
Stevens, C. and J. Kennan (1999). W
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