12. Analysing demand and estimating market turn-over

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The purpose of this chapter is to describe how the agro-economic, demographic and survey data collected by a project can be used to analyse existing trade patterns and form the basis for making projections of future demand at an existing or new market.

Analysis of existing trade patterns

In analysing existing trading patterns the intention should be to understand how a market relates to all the other outlets through which production is channelled. This will vary greatly, both by type of crop and by season. In some cases, typically with fruit production, the majority of produce may be sold at field level. This provides a guaranteed outlet and is often combined with an arrangement for providing cash before harvesting (the crop is "bought off the tree" In other cases, crops are traded through a hierarchy of local markets, which assemble produce for sending to a local secondary wholesale market or by-pass this market by sending directly to a terminal wholesale market in a distant city.

This analysis is a critical stage in the preparation of a development project for understanding the impact of any intervention in the marketing process. To describe how it can be undertaken is, however, difficult as the circumstances under which such interventions take place will completely vary between different countries. The following notes, therefore, give an indication of the types of issues that will need to be addressed.

Horticultural production and its spatial distribution. To understand existing trading patterns it is necessary to compare market survey results on the origin of produce being traded with published data on production. A typical tabulation of national-level vegetable production data for Nepal is shown in Table 12.1. The spatial distribution (by season) of these production areas is shown in Figure 18, together with the location of the main areas for fruit, fish and potato production.

Comparable production data is normally also available at provincial and district levels. The data should be examined to see what changes may be occurring in both the levels of production and its distribution. Agricultural production data is often very approximate as it is frequently
prepared by adjusting a previous year's data by applying theoretical changes in yield. However, the overall throughput of existing rural assembly markets, urban wholesale markets and retail facilities will obviously be influenced by local levels of production of fruit and vegetables and an analysis of available production data should help to establish the broad flows through the various marketing channels.

Table 12.1 Vegetable production and consumption targets, Nepal

  1975-1976 1979-1980 1984-1985 1986-1987 1989-1990 2000
Cultivated area ('000 ha) 83 96 138 140 141 141
Production (000 m/t) 423 528 743 875 970 1,515
Yield m/t per he) 5 6 5 6 10 11
Per caput consumption not not        
(kg per annum) stated stated 44.8 46.0 50.9 65.0

Source: Improved production of tropical vegetables in Nepal. 1988.
Pokhrel, M. N., Ministry of Agriculture, Nepal.
Note: excluding potato and leafy vegetables

Although the location of production areas is obviously influenced by factors such as soil fertility, moisture availability, temperature and topography, their relationship to potential consumers is equally important. Transport costs also play a major role in influencing the location of production areas, but there is usually a tendency for producers of a similar crop to congregate in a particular area.

This tendency to specialize can be studied as a pattern by converting the figures for the areas under crop or production levels, for each district or sub-region, into a series of coefficients, computing them as a percentage of a provincial or regional total. The coefficients can be grouped into, say, five different levels of productivity: very high, high, average, low and very low. These can then be plotted on a base map to show the spatial distribution and importance of production areas by district or sub-region within the market's catchment. From such an analysis, and by comparing the production areas in relation to the location of the main markets and the availability of transport facilities, it should be possible to deduce the likely direction of produce flows.

The following conclusions (see Figure 19) were deduced from such an analysis undertaken in Northern Thailand:

The majority of the produce from outside Chiang Mat Province naturally by-passed the province and this pattern would not be significantly altered by any intervention in the marketing system. Because of Chiang Mat cay's location in the centre of the province, only a proportion of its vegetable production would be marketed through the provincial capital. Producers south of the city were likely to sell either direct from the field or assemble their produce locally in the production area, for direct transfer to Bangkok and other destinations outside the province. In contrast, production areas to the north were more likely to use wholesale facilities available in the city. The relatively small volumes of flower production in the province were concentrated around the city. The pattern for upland and perennial crop production was found to be very similar to that for vegetables, but with probably less incentive for producers remote from the city to use its wholesaling facilities.

Many studies in the evolution of land-use have frequently confirmed the persistence of intensive horticultural production close to major centres of population. Market garden areas near to cities, producing high value fruit, vegetables and cut flowers, are a typical example of this. In addition to "rings" of production around cities, a substantial amount of cultivation in most less-developed countries may still be undertaken within the boundaries of municipal areas.

However, with urbanization, there will be increasing pressure on cultivable land within city boundaries, What generally happens is that land such as kitchen gardens becomes more intensively used, so that production of vegetables, fruit and fish (from pond culture) increases, while the production of other crops, such as rice, decreases. Despite its importance to low-income families, such intensive cultivation may be actively discouraged in order to reduce the incidence of malaria. It may also be used as an excuse to limit the operation of hawkers (who may sell both local produce and that produced outside the city) or as part of an often dubious programme of urban "beautification".

Seasonal variations in trade. A key factor in market operations is the degree to which trade varies by season, reflecting peaks in production. If a marketing authority maintains daily records from an existing market then a comprehensive data base will be available for making such an assessment. Table 12.2 shows such a set of data for three wholesale markets in the Near East, the peak months being compared to the average months using a ratio. Figure 20 illustrates the same data as a histogram, demonstrating the comparatively small seasonal variation at the Rabat wholesale market, compared with Amman and Cairo.

Figure 19 Variations in vegetable production in Chiang Mai Province, Thailand

Table 12.2 Seasonal throughput variations in Near Fast markets

Month Central Market
Amman, Jordan
Rod al Farag
Cairo, Egypt
Marche de Gros Rabat, Morocco
(tons) (ratio) (tons) (ratio) (tons) (ratio)
January 15,091 1.17 23,759 0.99 11,552 0.89
February 9,642 0 75 23,420 0.98 11,305 0.87
March 13,948 1.08 22,718 0.95 12,801 0.99
April 16,683 1.29 19,721 0.82 12,432 0.96
May 11,497 0.89 27,641 1.15 13,523 1.05
June 5,582 0.43 28,210 1.18 14,323 1.11
July 4,961 0.38 25,593 1.07 14,736 1.14
August 7,813 0.60 27,909 1.16 13,729 1.06
September 12,806 0.99 25,978 1.08 11,883 0.92
October 17,024 1.32 21,978 0.92 13,118 1.02
November 20,050 1.55 19,796 0.83 12,718 0.98
December 20,244 1.56 21,202 0.88 12,973 1.00
Total 155,341   287,925   155,093  
Average 12,945 1.00 23,994 1.00 12,924 1.00

Source: Market Authorities (data collected by FAO)

Figure 20 Comparison of seasonal variation in trade volumes (Near East markets)

If markets records are not available or there are no markets presently in operation, then other methods of analysis will need to be adopted. For an existing market, the types of interview and roadside surveys outlined in Chapter 11 may give some indication of seasonal variation. However, there may not be sufficient time-series data to draw any concrete conclusions to suggest that the trade at a wholesale market completely reflects the seasonal variations. Peak production is often more likely to be purchased directly in the field, at the "farm-gate" or be marketed through local assembly markets/trans-shipment points. Comprehensive official or research data is not likely to be available on the variation in fruit and vegetable production by season, except for price data, which is virtually impossible to use for deducing seasonal indices because of the time lags in price changes, the impact of storage and the substitution between produce.

Figure 21 Simplified cropping programme in Sri Lanka

Typical cropping calendars for upland/lowland, rainfed systems and off-season production in irrigated areas can provide useful models for examining seasonal variations in horticultural production. A simplified example for Sri Lanka of such a cropping pattern is shown in Figure 21.

These diagrams can be interpreted by using the informed judgements of farmers and traders as to where production is coming from and the broad distribution of volumes between seasons (ideally on a monthly basis). For semi-dry produce, such as garlic and onions, storage and market price may have a significant effect on marketing. Curing, drying and storage extends the period of marketing and an off-season crop may alter prices substantially. In contrast some highly perishable produce may only have a single growing season and apart from what can be canned or dried, the main production has to be marketed during that period.

Figure 22 Marketing channel partícípants, Sri Lanka

Figure 23 Proportions of produce going through different marketing channel (Jordan)

Marketing channels. Another consideration in understanding the existing pattern of trade is the problem of defining the channels through which production might pass. Reference has been made in the previous sections as to how this may vary according to factors such as the location of production areas, credit arrangements and seasonality. Other factors such as political and cultural conditions, the level of transport facilities and the presence of a traditional network of rural markets will also influence how the channels may operate. Figure 22 illustrates the complex pattern of channels that exists in Sri Lanka

Informal surveys of farmers, wholesalers and retailers can be used to define such a pattern. However, to understand how the pattern might impinge on the role of a wholesale market the flows in the system need to be quantified. Figure 23 illustrates the results of surveys undertaken in Jordan on the flow of produce through the main marketing channels.

To make such estimates it may be necessary to extend the scope of surveys to include local assembly markets so that the role that they play can also be defined. Figure 24 illustrates the results of such a survey in Northern Thailand Some of the markets are exclusively involved with the assembly of produce, whilst others are involved mainly with distributing produce to rural consumers received from the nearby urban wholesale market of Muang mad, in Chiang Mail

Figure 25 is a further analysis of the data from Northern Thailand and suggests that the function of the local markets is strongly influenced by the type of produce that is traded. Most local trade is in vegetables, with a low volume of fruit sales, confirming the fact that fruit sales often by-pass the local market system. The reasons for this are that fruit sales are predominately for markets outside the district and the sales of vegetables are often to local people for their own consumption. They most probably have their own fruit trees or would buy from neighbours.

Trade volumes by-passing the wholesale market. To establish existing trade volumes, and amounts of trade that might be by-passing an existing wholesale market, surveys of produce flow should be undertaken over an extended period, covering all flows into a city. Table 12.3 shows the results of a typical roadside and retail outlet survey undertaken in Kathmandu over a 10-day period in April 1989.

The Kalimati market had been recently opened at the time of the survey. With such a new wholesale market, trade will only gradually build up and produce which formerly went through other marketing channels will then transfer to the new facility. If there is a genuine demand for a new market the increase in turnover should be quite rapid and a general trend for the volume handled to increase each month should be observable. Roadside surveys undertaken over a number of seasons will be required to see the longer-term effect of such changes on the pattern of trade

Figure 24 Assembly function of local markets, Chiang Mia Province

Table 12.3 Roadside survey: daily produce coming into Kathmandu (kg)

Commodity Kalimati whole- Other destinations
  sale market in the city
Cabbage 8,334 5
Cauliflower 1,426 126
Onion, dry 6,648  
Onion, green 369 1,794
Garlic, green 490 2,975
Chilli" green 1,044  
Beans 1,108 9
Potato (incl. exports) 5,595 32,834
Tomato 12,979 591
Grass/leaf produce 427 2,251
Spinach 549 2,666
Other 2,748 1,106
Total (av. 10 days) 41,717 44,357

Source: FAO Project GCP/NEP/043/SWI

Transport changes. Roadside surveys also provide useful data on the changes that might be occurring in the type of transport ("mode") used by farmers and traders for bringing produce to market. Before farmers become well organized, public transport often plays a key role. In Kathmandu, for example, the importance of the wholesale market's location adjacent to a bus terminal has led to significant amounts of produce coming long distances by bus. This is illustrated in Table 12.4. The improvement of rural roads the availability of credit to purchase a motorbike and sidecar, the availability of low-cost pick-ups and the organization of group marketing, can all have a significant effect on marketing practices.

Over-view of existing trade pasterns. Once an assessment has been made of all the factors influencing the pattern of trade an attempt should be made to compile these into a complete model of the produce flows on a daily, seasonal or annual basis. Figure 26 illustrates what happens during the peak period in Northern Thailand. It assumes that the peak daily provincial production volume was around 1,600 tons and that rural markets had an overall total turnover of 170 tons per day. From this diagram it can be seen that most of the daily production in Chiang Mai Province is exported directly to Bangkok or other provinces. In the cool season the pattern is broadly similar except that the quantities of fresh produce exported are perhaps half of what would be exported in the peak period. In the hot dry season exports are more likely to be directed towards the other provinces in the Northern Region rather than to Bangkok.

Figure 25 Variations in type of produce sold in local assembly markets, Chiang Mia Province

Table 12.4 Mode of transport for produce coming into Kathmandu (%)

Mode of transport Kalimati whole- sale market (%) Other destinations in the city (%)
Truck 37.3 28.8
Mini-bus 12.2 66.8
Bus 50.0 -
Bicycle 0.3 1.8
Farmer himself (headload) 0.2 2.6

Source: FAO Project GCP/NEP/043/SWI

Figure 26 Daily produce flows in a regional marketing system (Northern Thailand)

Projected patterns of trade. Unless a comprehensive horticultural plan exists, which is usually not the case, it is unlikely that the long-term potential for increased horticultural production can be established. Such projections of future outputs, accompanied by an overall marketing strategy for produce, are the ideal basis on which to make an assessment of changes in the patterns of trade. In their absence, it will be necessary to make a number of broad assumptions in respect of the total volumes traded and the share that might pass through any existing or new wholesale marketing facilities.

From the analysis of marketing channels, the spatial distribution of production and the results of origin/destination surveys it may be concluded that to alter the present pattern of marketing would be quite difficult. In making projections for changes in a marketing system, therefore, rather conservative assumptions may need to be adopted in relation to the potential throughput of any new market. There would need to be substantial financial benefits to farmers to attract them away from existing market channels, particularly from the common practice of direct purchasing at the farm level by outside traders withestablished relationships with the farmers (such as providing inputs and credit arrangements). It would be unrealistic to presume, therefore, that a greatly enlarged proportion of the trade can be attracted, in the short term, to use new facilities, unless an existing market is being closed down.

Long-term estimates of throughput are even more difficult to make because of the unreliability of production projections. The agricultural sector in many developing countries is responsible for a decreasing proportion of the gross national product, although there may at the same time have been an overall expansion of cropped areas, particularly for horticultural produce and to a lesser extent for field crops. In many countries the potential for this rate of expansion to continue is likely to decrease as only the more marginal areas become available.

Another common factor is likely to be the impact of urban expansion, which typically causes a loss of presently cultivated land within and on the periphery of cities. These effects are likely to be off set, however, by increases in cropping intensity and by farmers switching to higher-value crops. Without detailed studies of land-use change any estimates of increased production are usually very tentative. A common working hypothesis is to assume that the production of fruit and vegetables will expand at a rate slightly higher than that of urban population increase (say, at 3 - 5 percent per annum).

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