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

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Given these problems faced by traditional systems, if not vigorously addressed, they will only become worse over time, due to rapid urbanization and income growth that fuels even more rapid growth in demand in urban areas. 1.1.1 The Situation in Zambia The republic of Zambia is a landlocked country located in Southern Africa bordered by eight countries namely: Mozambique, Malawi, Tanzania, Democratic Republic of Congo, Angola, Namibia and Zimbabwe (Figure 1.1). The country has a population estimated at 12.5 million with 65% being rural population and 35% urban population, and has a Gross Domestic Product (GDP) per capital of US$1,223 2 . Figure 1.1: Geographical Location of the Republic of Zambia Zambia Source: http://www.worldatlas.com/webimage/countrys/africa/zm.htm In Zambia, nearly 90% of all fresh produce marketed in Lusaka 3 flows through traditional retail channels, specifically the open air markets and street vendors and other informal traders operating outside the market, while modern retail channels such as supermarket 2 International Monetary Fund (IMF) publications. http://www.imf.org/external/pubs/ft/weo/2008/02/weodata 3 Lusaka is the capital city of Zambia and has the largest FFV wholesale and retailing system. 4 Zambia
chains and independent supermarkets hold combined shares of less than 10% (Food Security Research Project Urban Consumption Survey, 2007). This clearly tells us that the traditional sector dominates the fresh produce system as in most of Sub Saharan Africa (SSA). In many SSA countries, there has been rapidly rising share of urban population in total population. According to the Population Division of the Department of Economic and Social Affairs of the United Nations Secretariat, over the past few decades and in the next to come, the percent of urban population has been and will continue to rise steadily compared to the rural population which is actually decreasing 4 . However, in Zambia this has not exactly been the trend. Over the period between 1980 to 2030, the percent of urban population had initially been increasing, then it begun to decrease in the 1990’s and then steadily rising after 2005 5 . The decreasing annual urban population trend is attributed to the investments made in the mining sector which saw a good number of people moving to the rural mine areas for employment. Considering the overall increase in the urban population in SSA, the traditional marketing channels in African horticultural sectors are now subject to heavy pressures for change. In Zambia, urban populations are growing rapidly and therefore the traditional horticulture systems need substantial investment. Since urban marketing infrastructure in most of the continent, Zambia included, has received very little investment in recent decades, the result has been often chaotic, unsanitary, and high-cost marketing systems 4 World Urbanization Prospects: The 2007 Revision Population Database http://esa.un.org/unup/p2k0data.asp 5 http://esa.un.org/unup/p2k0data.asp 5
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: (Ksh 1 )7.5 billion) of total veget
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 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
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patterns differ across markets, red
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case of a flood, its effects could
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3.2 Hypothesis Testing The level of
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Table 3.2: Description of Data Used
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Coefficient of Variation= Where;
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Where; P t - the observed tomato pr
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A look at price variability in each
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For further comparison of the mean
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Figure 3.2: Comparison of the Ratio
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Figure 3.4: Comparison of Condition
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thereby making the farmers more con
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d. The absence of cold chain system
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depend on local suppliers for their
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The provision of market information
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upon arrival in the market. Lower q
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- Assets used in tomato production,
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Tomato price data used for analysis
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4.4 The Monte Carlo Model The Basel
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CF Fixed conversion factor of 37.
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- Seedling costs - Seed costs - Fie
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differences were due to differences
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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
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4.5.2 Simulation Results for the Di
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Scenario 1: Increased Sales Frequen
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knowledge of what their yields and
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Table 4.12: The Effect of Supply Ch
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Table 4.13: Production of Low and H
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quality; when supplies are high in
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etter farmers would attempt to have
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CHAPTER 5 CONCLUSION This study was
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top twelve tomato supply areas acco
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Freshpikt and Rivonia are the main
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on prediction errors from a price p
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absence of a cold chain system, the
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price variability, the expectation
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In the scenario analysis of increas
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price variability affects the diffe
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facilitate the provision of low cos
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APPENDICES 135
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i. What type of farmers do they pre
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Taipei, Taiwan Table A2.3. Model Su
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Colombo, Sri Lanka A2.7. Model Summ
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APPENDIX 3. Graphs of Price Predict
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Figure A3.3. Price Prediction Resid
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Figure A3.5. Price Prediction Resid
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9. Name of Main Respondent (if diff
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SECTION 3 - HARVEST AND SALES OF CR
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SECTION 4 - PLANTING AND HARVEST PA
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155 _______________ _______________
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5.2 Planted Seedlings Phase Field #
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PHASE 2 - FIELD PREPARATION 5.5 Enu
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5.7 Irrigation prior to transplanti
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4=Spraying 5=Weeding 6=Placement of
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Field # Please list all the types o
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that you used in your tomato produc
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Trailer Van/light truck Borehole Bo
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Field # Time from 1 st harvest Phas
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Second Field Field # Time from 1 st
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Field # Time from 1 st harvest Phas
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Second field: 8.0 Harvesting and Ma
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APPENDIX 5. Distribution of Sampled
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Figure A6.2. Distributions for Cost
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Figure A6.4. Distributions for Cost
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APPENDIX 7. Histograms of Farmer Pr
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Figure A7.3. Baseline Scenario: His
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Figure A7.5. Increased Sales Freque
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Figure A7.7. Increased Sales Freque
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Figure A7.9. Supply Chain Improveme
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Figure A7.11. Supply Chain Improvem
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Figure A7.13. Scenario on Quality o
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Figure A7.15. Scenario on Quality o
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Figure A7.17. Scenario on Low Quali
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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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