Most, if not all statistical offices or organizations involved in agricultural statistics, (viz., production and trade of commodities) keep their data in separate files, separate computers and, sometimes, perhaps even at separate locations. In this document the advantages of maintaining such data "side by side" in a single file, with interlinking algorithms, are pointed out . This results in added value to the data and, at the same time, leads to the estimation of other useful data, which may not otherwise be available. This document promotes the establishment of a particular database structure of agricultural statistics in the form of supply utilization accounts (SUAs).

Supply utilization accounts are time series data dealing with statistics on supply (production, imports and stock changes) and utilization (exports, seed, feed, waste, industrial use, food, and other use) which are kept physically together to allow the matching of food availability with food use.

Furthermore, by taking the data for a period, limiting it to food commodities and converting the food into calories, proteins and fats (commodity by commodity), it is possible to prepare food balance sheets (FBS). This document promotes a particular report output from the database in the form of food balance sheets.

A food balance sheet presents a comprehensive picture of the pattern of a country's food supply during a specified reference period. The total quantity of foodstuffs produced in a country, added to the total quantity imported and adjusted to any change in stocks that may have occurred since the beginning of the reference period, gives the supply available during that period. On the utilization side, a distinction is made between the quantities exported, fed to livestock, used for seed, processed for food use and non-food uses, lost during storage and transportation, and food supplies available for human consumption. The per caput supply of each food item available for human consumption is then calculated by dividing the respective quantity by the related data on the population actually consuming it; that is the meaning of the term- per caput. Data on per caput food supplies are expressed in terms of quantity and also - by applying appropriate food composition factors for all primary and processed products - in terms of caloric value, protein and fat.

The internet document looks at some benefits and limitations of constructing supply utilization accounts and food balance sheets.

Ladislav Kabat
Director
FAO Statistics Division

I. INTRODUCTION

All recognize the importance of development planning and share the goal to achieve higher standards of living. Timely and reliable statistics are needed to prepare and monitor such plans. The statistical framework of supply/utilization accounts (referred to as SUAs) for food and agricultural commodities can be a very powerful tool for making the best use of available statistical information and the Statistics Division advocates this agricultural database structure that is referred to as a supply utilization accounts database.

Establishing a SUA for each 12-month period will also help to pinpoint many inconsistencies in the statistical series, which lead to a better recognition of the need to improve the data on food and agriculture. While in food balance sheets (hereafter referred to as FBS) data extracted from SUAs present a comprehensive picture of country's pattern of food supply during a specified reference period.

II. MEANING OF "SUPPLY UTILIZATION ACCOUNTS"

General Description

The increased involvement of government authorities concerned with assessment, monitoring and planning exercises in the field of agriculture and rural development has had a significant impact on processing methods for the compilation and analysis of statistical data. It is no longer meaningful to deal separately with individual statistical series, such as those of production and trade, etc. Although individual data series continue to be important, it is equally important to establish the links between them. It is necessary to deal with flows and matrices rather than with individual sets of data. The statistics of any single commodity have to be traced all the way from production and utilization to final consumption.

As a consequence of maintaining the data series in this integrated fashion, it is possible to compute a variety of derived statistics and indicators relating to food and agriculture in a consistent manner from the same central data storage. The core statistics of such a statistical framework are the SUAs for food and agricultural commodities. For each product, the SUA traces supplies from production, imports and stocks to its utilization in different forms: addition to stocks, exports, animal feed, seed, processing for food and non-food purposes, waste (or losses), and, lastly, as food available to the population, where appropriate.

SUAs are then essentially time series data for various elements of food statistics, which are kept side by side.

SUA Equations

These elements can be inter-related in a number of balancing equations. The first equates the sum of the supply elements:

Opening stocks + production + imports

With the sum of the utilization elements:
Exports + feed + seed + waste + processing for food + food + other utilization + closing stocks.

For the preparation of a balance like this, it assumes that reliable and independent information is available for each of its elements. Alternatively, if no information is available for one of the elements, the residual will provide an estimate. In practice, however, the construction of balances of this type is made difficult by the absence of adequate information on opening and closing stocks. Experience shows, however, that information on changes in stocks is made more readily available than on their actual size. If a net decrease in stocks is defined as "from stocks" and a net increase in stocks as "to stocks" the following two equations will be obtained:

i) from stocks + production + imports = exports + feed + seed + waste + processing for food + food + other utilization;

or:

ii) production + imports = exports + feed + seed + waste + processing for food + food + other utilization + to stocks.

The combination of production and imports with both increases and decreases in stocks results in a supply available for export and domestic utilization, where domestic utilization is defined as the sum of: feed + seed + waste + processing for food + food + other utilization.

Advantages of SUAs

The advantage of storing the commodity data in the form of SUAs is that they are internally consistent. Each element of supply of a commodity matches the other and total supply matches total utilization. This system provides a check on the statistical data supplied by various national and/or international agencies. It also provides a useful tool for choosing between alternative sources of data and a logical framework for estimating missing observations. Even so, every effort must be made to make the data consistent by adhering, as far as possible, to the same definitions, coverage, specifications, etc., for each commodity and element. Since total supply equals total utilization, the accounts are in the form of balancing equations with the result that one element usually is calculated as the remainder or residual.

Conceptual Problems Related to the Preparation of SUAs

• The most important conceptual problem arises mainly with respect to the accuracy and availability of data. Incompleteness and inaccuracy of basic data tend to be the main problems, even where the statistics are available, they are not always reliable. Official production data is sometimes questionable. This is because farmers frequently equate production with tax collection and, in some cases, reliable information on food losses caused by pests and disease is not available. Hence the estimates of yield are likely to be inaccurate. If so, it follows that production statistics derived from the harvested and estimated yield may be subject to a biased estimation. Crop patterns and utilization of some crops (e.g., cassava and bananas) is not completely harvested. Some is left as a reserve to be used if the need arises or perhaps left to rot.

• Production statistics may not be available for all commodities needed and mostly confined to important food crops. Non-commercial or subsistence production, i.e. home produce and food from hunting, fishing and gathering by the household for their own consumption, is usually not included or it is not available which may be a large part of total production in some countries.

• Information on commercial stocks may be available from official or marketing authorities, factories, wholesalers and retailers, but inventories of catering establishments; institutions and households may not be available.

• Information on waste in industrial processing may be easily found, but waste during storage, transportation may not be available and other waste information - on quantities intentionally discarded for the purpose of price control or disease control - may be hidden. In these cases, even though the basic data are reliable, some adjustments are required to adapt the basic data to FBS concepts/coverage.

• Import and export data may be accurate in the majority of countries, but in others, there may be significant amounts of trade across national boundaries that go unrecorded. Moreover, import and export transactions may not receive equal attention from the custom's administration because taxes or quotas are generally concentrated more on import items than export. As a consequence, the reliability of export data may also be questionable.

• There may not exist basic data on the feed, seed and industrial/manufacture use of crop and livestock products. The cost of production surveys and manufacturing surveys, which are the appropriate sources of data, are often not conducted regularly in developing countries. Even where the surveys are conducted, their coverage is usually limited (e.g., cost of production surveys cover only a few important crops or do not cover livestock commodities, etc.).

• There are also problems related to the time-reference period to be used in reporting production. Several twelve-month periods, such as July/June, October/September and April/March have been proposed and were indeed also applied. However, none of these periods covered satisfactorily and uniformly the production of all agricultural commodities, their trade and domestic utilization. It can be assumed that there is no single twelve-month period which is fully suitable for recording supply and utilization for all products. It was therefore felt that although the calendar year time-reference period (January-December) might not be a completely satisfactory solution, its advantage would appear to outweigh its disadvantages. The application of a calendar year time-reference period during which the bulk of the harvest takes place also helps in linking the agricultural statistics with those of the industrial and other sectors of the economy.

Preparing SUAs

Ideally, the basic data required should be obtained from just one authority. This implies that, firstly, the country should have a comprehensive statistical system, which records all current information relating to each component of the FBS (from producers to consumers). Secondly, concepts of the information adopted should be those of the FBS. Thirdly, the information available should be consistent, at least with respect to measurement unit and time reference period. In practice, however, such an ideal statistical system does not exist. Even in those mainly developed countries, which possess uncommonly sophisticated reporting procedures, the available data do not always meet either the second or third condition. Therefore, the basic data are necessarily based on a large variety of sources.

As mentioned before, since the basic data are obtained from different sources, they are subject to inconsistency. Their concepts are not likely to be the same as the FBS concepts, since they were not primarily planned for that purpose. The time reference period may not be consistent throughout, or there may be some time lag in the available data. The existence of all these problems shouldn't stop the expert using this most powerful tool. As far as possible, an effort should be made to put data from different sources together to prepare SUAs. The main sources commonly used are discussed below.

Production and trade data are part of ongoing national official statistics. They are based either on direct enquiries and records, or are estimated by government agencies. Information on stock changes is available from marketing authorities and factories or from farmer stock surveys. Information on industrial uses is obtained from industrial/manufacturing censuses/surveys. Feed and seeding rates are obtained from cost of production surveys or are estimated by the government agencies concerned. Waste in industrial processing is also obtained from manufacturing surveys. In some cases, the exercise has to be based also on other external sources.

Adjustments to the basic data and estimation/imputation of the missing data are necessary in order to maintain a certain degree of consistency, completeness and reliability of the resulting FBS . This is a basic axiom that one must work from. The underlying "hidden" assumption is that any number based on a professional estimation is preferred to zero. The FAO Conference, which is the governing body of FAO, has instructed us to do this estimation. Both official and unofficial data available in the Statistics Division and other units in FAO have been used to construct the SUAs. Missing data have been estimated on the basis of various surveys (of differing sizes), other information available to the economics and statistics community through the media and in particular professional journals, as well as technical expertise available in FAO.

At first, it is necessary to draw up a list of relevant primary and processed commodities, when establishing a coordinated system of SUAs. The definition of a complete list of commodities presents virtually insurmountable difficulties - both conceptual and statistical. For practical purposes, therefore, a workable list of commodities will have to be adopted. In drawing up such a list, countries may wish to keep in mind a general list of food and agricultural commodities.

A great degree of detail is required for the proper choice of food nutritive composition factors used for nutritional analyses (e.g., calorie, proteins and fat per 100 grams) of the food item, while the commodity list itself just depends on the different foods available in the country. As an example, this calls for specifying the proportions of different cheese from whole milk or from skim milk, since the nutritive factors differ. Similarly, the caloric and nutrient content of wheat (and other cereals) depends on the extraction rate used, the variety (hard or soft) of wheat milled and its water content.

Among the various criteria to be taken into account when setting-up a commodity list, choosing suitable reporting units deserves particular attention. The data should be expressed in common units in order to facilitate international comparisons and the metric system should be adopted whenever possible. Values and prices should be converted and expressed in terms of a suitable currency.

Whenever possible, trade in processed commodities should be expressed in the primary commodity equivalent, e.g. orange juice trade can be converted into orange equivalent trade data.

In Appendix 1, commodities are classified into major food groups for FBS purposes. This list should, however, be adjusted according to the availability of commodities in a given country.

It is useful to note that SUAs are used to prepare a number of statistical measures some important ones are:

i) Index numbers of production, trade and supply: One of the most important indicators for reviewing agricultural progress, and one that is extensively used, is the series of index numbers of food and agricultural production (total and per caput). Similarly, trade index numbers can be calculated independently for value, volume and unit values, as well as index numbers of food supply (total and per caput).

ii) Self-sufficiency ratios and import dependency ratios: These indicate the extent to which a country's supply of commodities and/or total food is derived from national production or originates from abroad.

iii) Food balance sheets reports (FBS):

III. WHAT ARE FOOD BALANCE SHEETS (FBS)

General Description

FBS are one important report coming from supply utilization accounts.

They are extracted out of time series SUAs and report a single year (or an average number of years) multiplying the food available by the nutritive factors, to access the calorie protein and fat available to the general population. FBS are a special report, which is generated from the SUA database in conjunction with certain additional vital data, viz., food nutritional values and the total population data for the country. The new element here is the nutritive factors and the abandonment of multi-year information or time series data to a single year.

They are perhaps the major output of the FAO Statistics Division, although they are often overlooked by many who are more familiar with the FAO Production Yearbook, the FAO Trade Yearbook and the FAO Fertilizer Yearbook. The FBS are the statistical basis of much of FAO's long term forecasting and projections work and regularly become the major input into quantifying the numbers of malnourished in the world. They are generated once we have in place our SUA database.

Origin of FBS

The first attempts at preparing FBS date back to World War I. FBS were the leading source of data when, in 1936, at the request of the League of Nations Mixed Committee on the Problem of Nutrition and its Sub-Committee on Nutritional Statistics, a systematic international comparison of food consumption data was prepared.

During World War II, the interest in FBS increased considerably. The Inter-Allied Committee on Post-war Requirements used them in 1942/43 in their studies of post-war requirements in European countries and an even more detailed technique was developed and employed by a joint committee of experts from Canada, the United States of America and the United Kingdom in the report "Food Consumption Levels in the United States, Canada and the United Kingdom". During these years, FBS were also constructed in Germany for the country itself as well as for the occupied countries. In the work of the International Emergency Food Council, which dealt with problems of food allocation and distribution in the period of worldwide food shortages after the war, FBS played an important role.

From the outset, the Food and Agriculture Organization of the United Nations (FAO) has given considerable importance to furthering the development of FBS, reflecting their usefulness in analyzing the food situation at the level of individual countries. The technique has been extensively employed in FAO's "World Food Surveys". The "Handbook for the Preparation of Food Balance Sheets" was published in 1949. Since then, FBS have been prepared and published by FAO on a regular basis.

Calculating Per Caput Food Supply in FBS

The estimate of the total population is also a part of the set of ongoing official statistics. The per caput figure of each food commodity is obtained by dividing the food available for human consumption figure by the total population consuming it during the reference period. However, for many countries, this figure may also be subject to either incomplete or unreliable data. The total population estimates may refer to resident population only. Thus, non-resident population, such as illegal immigrants, tourists, refugees, foreign diplomatic personnel and their dependants, foreign armed forces, etc., are usually not included and these omitted individuals may constitute a considerable part of the population in some countries, if they were not counted in the population. This, therefore, would result in understating the total consuming population.

In food balance sheet, per caput food supplies in terms of quantity are given both in kilograms per year and grams per day. Calorie supplies are expressed in kilocalories (calories) per day, while supplies of protein and fat are provided in grams per day.

For the purpose of calculating the caloric value and the protein and fat content of the per caput food supplies, the choice of the appropriate food composition factors is very important. For example, the choice of the food composition factors for wheat flour depends, among other factors, on the water content, variety, and the degree of milling involved. The choice of the corresponding factors for cheese depends on whether the cheese is derived from whole milk, partly whole milk, or skim milk, as well as whether the cheese has been made from the milk of cows, sheep, goats, buffaloes, or camels, and lastly on whether the cheese is hard, semi-soft or soft. The nutritive factors can be obtained directly from the national food composition tables of the health authorities. These tables give the nutritional composition of food per 100 grams of edible portion.

As the quantity data of the FBS are on an "as purchased" basis, it is necessary that the nutritive composition in terms of edible portion be converted into this basis as well. The conversion is made by applying waste/refuse factors to the nutritive composition in term of edible portion. The resulting per caput total nutritive values are usually expressed on a daily basis. In the absence of food composition tables prepared by appropriate national institutions, one can use FAO's Food Composition Tables - Minerals and Vitamins - for International Use.

For calories, protein and fat, a grand total with a breakdown into components of vegetable and animal origin is shown at the beginning or the end of the food balance sheet.

Finally, one should pay special attention to the following when examining per caput food consumption and FBS in a country or a region:

1. changes in the energy and protein availability,
2. adequacy of average energy and protein availability,
3. starchy staples,
4. starchy staple ratio and animal products ratio,
5. changes in the starchy staple ratio and animal products ratio,
6. the trade situation: self sufficiency or import dependency
7. consumption of "luxury" foods.

It is useful to take examine a few formats for FBS. Various formats, which have been developed over the years, still exist and can be used for the preparation and presentation of FBS. (See Appendix 2)

Advantages of FBS

• Annual FBS tabulated regularly over a period of years will show overall trends in the national food supply, disclose changes that may have taken place in the types of food consumed, i.e., the pattern of the diet, and reveal the extent to which the food supply of the country as a whole is adequate in relation to nutritional requirements.

• By bringing together the larger part of the food and agricultural data in each country, FBS are useful in making a detailed examination and appraisal of the food and agricultural situation in a country. A comparison of the quantities of food available for human consumption with those imported will indicate the extent to which a country depends upon imports (import dependency ratio) to feed itself. The amount of food crops used for feeding livestock in relation to total crop production indicates the degree to which primary food resources are used to produce animal feed which is useful information for analysing livestock policies or patterns of agriculture. Data on per caput food supplies are an important element for projecting food demand. This data is the basis of projections into the future and are used with other information such as income elasticity and national income forecasts to analyze various possible scenarios for the year 2010, 2020 and recently forecast to the year 2030. FBS let you tell a story in a single presentation or report format. They are a powerful tool to the speechwriter, the analyst, the economist, the policy maker, the nutritionist and even the military. They allow those that have it to describe the status of the country - rich or poor - the health of the country - the trade situation in food - and together with past FBS the direction development is taking and can be useful for economic and nutritional studies, for preparing development plans and for formulating related projects.

• They are often overlooked in the statistical system. Identification of important gaps in the available data might also stimulate the improvement of national statistics at the source.

• The calorie values obtained as the mean in the FBS become proxies for the food consumption mean intake and when combined with the variance in food consumption data collected from household consumption - or expenditure surveys - are used to estimate the distribution (function) of food intakes in the country. Finally, if we apply a particular cut-off point or value, in terms of human nutrition requirements, we are able to estimate the numbers malnourished, which is a very important capacity.

Some notable limitations

FBS are often far from satisfactory in the proper statistical sense, as is explained below:

• The accuracy of FBS depends on the reliability of the underlying basic statistics of population, supply and utilization of foods and on the accuracy of the nutritive value data of various foods which is usually the mandate of the national health and nutrition authorities. The data vary a lot both in terms of coverage and accuracy. In fact, there are many gaps particularly in the statistics of utilization for non-food purposes, such as feed, seed and manufacture, as well as in those of farm, commercial and even government stocks. To overcome the former difficulty, estimates can be prepared while the effect of the absence of statistics on stocks is considered to be reduced by preparing the FBS as an average for a three-year period. But even production statistics (on which the accuracy of FBS depends) are, in many cases, subject to improvement through carrying out statistical field surveys. Furthermore, there are few surveys on which to base sound figures for waste. In some cases, these estimates are subject to significant margins of error. Typically, assumptions about waste are based on expert opinion obtained in a country.

• At the same time, FBS do not give any indication of the differences that may exist in the diet consumed by different population groups, e.g., people of different socio-economic groups, ecological zones or geographical areas within a country.

• Nor do they provide information on seasonal variations in the total food supply. To obtain a complete picture, food consumption surveys (which show the distribution of the national food supply at various times of the year and among different groups of the population) should be conducted. In fact, the FBS and food consumption surveys are complementary and many countries do both of these. There are commodities for which a production estimate could best be based on estimated consumption as obtained from food consumption surveys.

It is very important to be aware of the fact that availability for human consumption is by no means identical with consumption. The quantities of food available for human consumption, as estimated in the food balance sheet, reflect only the quantities reaching the consumer. The amount of food actually consumed may be lower than the quantity shown in the food balance sheet depending on the degree of losses of edible food and nutrients in the household, e.g., during storage, in preparation and cooking (which affect vitamins and minerals to a greater extent than they do calories, protein and fat), as plate-waste, or quantities fed to domestic animals and pets, or thrown away.

IV. CONCLUSION

The SUA account database structure works for the agricultural statistician and is a useful tool in agricultural statistics. Furthermore, FBS generated from SUAs are often extremely useful for economists, planners, and health experts, but in view of the difficulty in obtaining accurate data, FBS need to be interpreted with much caution. They are a powerful means of bringing together from different sources, information about a food economy and are excellent for showing very broad changes in a food economy over a given period of time. The adoption of a programme of work that includes both SUAs and FBS is recommended to all involved in agricultural data and analysis.

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Appendix 1
LIST OF COMMODITIES CLASSIFIED BY MAJOR FOOD GROUPS

CEREALS
Wheat Rice (paddy)
Barley
Maize Rye Oats
Millet Sorghum
Cereals other

STARCHY ROOTS
Potatoes
Sweet potatoes
Cassava
Roots other

SUGAR
Sugar cane
Sugar beet
Sugar
non-centrifugal Sugar (raw equiv.)
Honey

PULSES
Beans
Peas
Pulses other

TREE NUTS
Cashew nuts
Chestnuts
Almonds
Pistachio
Walnuts

OIL CROPS - Primary
Soybeans
Groundnuts
Sunflower seed
Rapeseed & Mustard seed
Cotton seed
Coconuts (incl.copra)
Sesame seed
Palm kernels
Olives
Oilcrops other

VEGETABLES
Tomatoes
Onions
Vegetables other

FRUIT
Oranges
Mandarines
Lemons
Limes
Grapefruit
Citrus other
Bananas Plantains
Apples (excl. cider)
Pineapples
Dates
Grapes (excl. wine)
Fruit other

STIMULANTS
Coffee
Cocoa beans
Tea

SPICES
Pepper
Pimento
Clove
Spices other

ALCOHOLIC BEVERAGES
Wine
Barley beer
Beverages fermented
Beverages alcoholic
Alcohol
non-food

MEAT
Bovine meat
Mutton/goat meat
Pig meat
Poultry meat
Other meat
Offals

MILK
Cow milk
Sheep milk
Goat milk

EGGS
Hen eggs
Eggs other

FISH AND SEAFOOD
Freshwater fish
Marine fish
Crustaceans
Molluscs

VEGETABLE OILS - Secondary
Soybean oil
Groundnut oil
Sunflower-seed oil
Rape & mustard oil
Cottonseed oil
Palm kernel oil
Palm oil
Copra oil
Sesame-seed oil
Olive oil
Oilcrops oil other

ANIMAL FATS
Butter ghee
Cream
Fats animal raw

Appendix 2
FORMATS OF FOOD BALANCE SHEETS

The three "Sample Forms for Food Balance Sheets" that are shown have different headings for various columns which need some further explanations.

 
Format I

Available supply represents the concept of supply available for domestic utilization.

Food (gross) is simply the balance of the available supply after feed, seed, manufacture and waste have been deducted. It represents the quantities directly available to consumers before the application of extraction rates, if this is necessary.

Extraction rate applies chiefly to cereals and is used to effect a conversion of grains to flour and of paddy rice to milled rice. This column is also used to show the extraction of raw sugar from cane and sugar beets and of oil from oilseeds and so on. In addition to reflecting the input/output ratio between originating/parent commodity and processed commodity, the extraction rate also determines the choice of the appropriate food composition factors.

Food (net) represents the actual quantities of food directly available for human consumption after the application of extraction rates to the corresponding figures in the food (gross) column.

Columns 18-20 show the food composition factors which have been applied when converting the quantities of daily per caput food supplies into energy, protein and fat content.

Format II

The headings in this second format are a more general format than Format I.

Format III

This third format may be used when presenting a food balance sheet in standardized form.

Processed Trade (E-I) shows exports minus imports of processed commodities expressed in their primary/parent commodity equivalent and where "E" denotes exports and "I" denotes imports.

Stock changes indicate increases (+), or decreases (-), in stocks.

Food Manufacture shows amounts of the commodity in question used to manufacture processed commodities which are part of a separate food group (e.g., fats and oils, beverages).

Other uses comprise quantities used for the manufacture of non-food products, e.g., oil for soap. In order not to distort the picture of the national food pattern, quantities mainly consumed by tourists may be included here.

Food includes commodities consumed in the form of secondary products as well as their primary form . This, for example, in the case of wheat, means cakes and biscuits and wheat flour.