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

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CHAPTER TWO TOMATO PRODUCTION AND MARKETING SYSTEM SERVING LUSAKA This chapter provides a broad and detailed examination of the tomato production and marketing system serving Lusaka. It starts by explaining the broad array of data and the methods used. It then uses these data to examine fresh produce in consumer budget shares across four cities of Zambia. Next, it focuses on Lusaka, presenting an overview of the structure of the tomato production and marketing system for the city, organized around a detailed tomato channel map that brings together data and information from many sources. Key points about the organization of the sector are highlighted in this section, and are examined in more detail in subsequent sections. After the overview is a discussion of the entire vertical supply chain for the “traditional” sector followed by the “modern” sector. In closing, price behavior at the farm, wholesale, and retail levels is examined. 2.1 Data The data used in this chapter comes from three sources: the Food Security Research Project 6 Urban Consumption Survey (FSRP-UCS), the FSRP wholesale and retail price and quantity data, and data on the FFV procurement systems adopted by some selected retail outlets and FFV processing firms in Lusaka. 2.1.1 Urban Consumption Survey Data The UCS was conducted in 2007 and it contained household consumption data from urban consumers in Kitwe, Mansa, Lusaka and Kasama cities, all in Zambia. This survey was collected from a sample size of 2,160 urban consumers who were sampled using a 6 The Food Security Research Project (FSRP) has operated in Zambia since 1999, with funding from U.S. Agency for International Development/ Zambia and, recently, from the Swedish International Development Agency. Over the past decade it has collected various household- and market level data sets in collaboration with local organizations; some of those data sets are used in this thesis. 10
andomized cluster sample design. This data contains specific information on the various FFV, other food and non-food items purchased and consumed by the household; the value of consumption for all the foods purchased, and the primary retail outlet in which each item was purchased. In total, there was data collected on 37 FFV and food items such as rape, tomato, onion, cabbage, cassava leaves, sweet potato leaves, pumpkin leaves, bananas, mangoes, oranges, apples and beans, and nine non-food items such as fire wood, paraffin, batteries and vaseline jelly. In addition to this data on the FFV, food and non food items, the survey also collected data on household expenditures, the households’ participation in urban agriculture (horticultural crop production and livestock production) and the households’ food security levels. 2.1.2 Tomato Wholesale and Retail Price and Quantity Data FSRP market reporters collect price data at wholesale and retail, and quantity data at wholesale, for tomato, rape, and onions every Monday, Wednesday and Friday. This quantity data captures total volumes of tomatoes (and the other two crops) moving through Soweto market, while the price data is collected at Soweto and selected retail outlets. Soweto market is supplied with tomatoes from over 150 areas from Lusaka and Central provinces. Quantity data includes information on the area of origin and the size (number of crates) of every lot entering the market. By “area of origin” we refer to a production area at the sub-district level as identified by farmers and traders selling in the market. A “lot” is defined as the set of crates belonging to an individual farmer or trader whose tomatoes are being sold in the market. The Soweto wholesale price and quantity data 7 tracks entering 8 , starting and ending volumes of tomatoes in the market from all the 7 Food Security Research Project: Tomato wholesale and retail price and quantity data. 11
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: Chapter 5 concludes the thesis with
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 and 36: Table 2.4: Key Characteristics of T
Page 37 and 38: Table 2.6 cont’d Area Province Ma
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
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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
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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
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Group 1 Table 4.4: Basic Informatio
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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
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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
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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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