guidelines for designing and implementing grain stock surveys

Guidelines for designing and implementing grain stock surveys

GUIDELINES FOR DESIGNING AND IMPLEMENTING GRAIN

STOCK SURVEYS

VERSION 1

FOOD AND AGRICULTURE ORGANIZATION OF THE UNITED NATIONS

Rome, 2017

GUIDELINES FOR DESIGNING AND IMPLEMENTING GRAIN STOCK SURVEYS | VERSION 1ii

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ContentsAcronyms vAcknowledgements vi

Chapter 1 Introduction ........................................................................................................................................................... 1

1.1 Rationale 1 1.2 Status of available stock data 2 1.3 A conceptual framework for measuring stocks 3 1.4 Structure of the guidelines 5

Chapter 2 Current practices in national stock surveys..................................................................... 7

2.1 Introduction 7 2.2 Dedicated surveys of on-farm or commercial stocks 8 2.3 Surveys of more than one category of stakeholder 10 2.4 Stock modules included in other surveys 12 2.5 Main recommendations 13

Chapter 3 Technical issues affecting stock surveys ....................................................................... 15

3.1 Introduction 15 3.2 Timing 15 3.3 Targeting 17 3.4 The selection of crops to be included 20 3.5 Main recommendations 21

Chapter 4 The main steps in designing stock surveys ................................................................ 23

4.1 Introduction 23 4.2. Selection of the sampling frame and sampling design 23 4.3. Preparation of survey questionnaires 27 4.4. Main recommendations 30

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Chapter 5 The main steps in stock surveys .............................................................................................. 31 5.1 Data collection 31 5.2 Data processing and dissemination 33 5.3 Data documentation 34 5.4. Main recommendations 34

Chapter 6 Conclusions ...................................................................................................................................................... 35

References .......................................................................................................................................................... 41

ANNEXES .............................................................................................................................................................. 47

Annex 1 ......................................................................................................................................................................... 47

Annex 2 ......................................................................................................................................................................... 48

Annex 3 ......................................................................................................................................................................... 50

Annex 4 .......................................................................................................................................................................... 68

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AcronymsAMIS Agricultural Market Information System

DEFRA Department for the Environment, Food and Rural Affairs (United Kingdom)

FAO Food and Agriculture Organization of the United Nations

LSMS-ISA Living Standards Measurement Study – Integrated Survey of Agriculture

NASS National Agricultural Statistics Service (USA)

NFA National Food Authority (the Philippines)

USDA United States Department of Agriculture

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AcknowledgementsThese Guidelines have been written by François Fonteneau, Programme Coordinator, FAO Statistics Division; Romeo Recide, Deputy National Statistician, Philippines Statistical Authority; and Clara Aida Khalil, Statistician, FAO Statistics Division. Valuable inputs and comments were provided by Josef Schmidhuber, Deputy Director, FAO Statistics Division; Christophe Duhamel, Team Leader, Global Strategy for Improving Rural and Agricultural Statistics, FAO Statistics Division; Mark R. Miller, Director, International Programs Office, USDA National Agricultural Service; and Yakob Mudesir Seid, Statistician, FAO Statistics Division. The authors are deeply grateful for their contributions.

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1Introduction1.1 Rationale

Building national technical and institutional capacities for collecting market information and improving the quality of data is a crucial component of the Agricultural Market Information System (AMIS). Together with AMIS, the Bill & Melinda Gates Foundation created the Strengthening Agricultural Market Information Systems Globally and in Selected Countries project, one of whose objectives is to improve market information systems in Bangladesh, India and Nigeria. One of its components is the improvement of food stock estimation with a view to developing an approach that can be applied in developing countries.

The initial steps are summarized in the 2013 report by Philip Abbott “Improved Methodology for Estimation of Food Stocks”, which provides a literature review of current stock estimation practices and a proposal for a set of supporting guidelines. The literature review showed that although food stocks feature prominently in market analyses, there is little documentation on estimation methods.

This paper is intended for statisticians and managers in national statistics offices wanting to develop or improve survey programmes for the direct measurement of grain and other food stocks. It provides guidance and tools for direct measurement of food stocks, discusses current and best practices for stock estimation through sample surveys, reflects on conceptual, technical, human and budgetary issues related to stock surveys and provides examples and tools for countries wishing to develop their stock survey programmes.

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1.2 Status of available stock data

This paper is based on an assessment of the methods that countries currently use to produce data on stocks. As documented by Abbott (2013), there are three approaches to obtaining the available data.

The first is to consider only the records of public agencies or parastatal marketing boards: this is the case in Bangladesh, for example, where information about public stocks of food grains can be found on the website of the Food Planning and Monitoring Unit. But this information is clearly incomplete because it ignores stocks held by commercial entities, producers and in some cases by households.

The second approach, which is used in most countries and regions, is to estimate stocks as a residual element in the supply/utilization equilibrium. This is the method used by international data providers such as the Food and Agriculture Organization of the United Nations (FAO), the International Grain Council, and the United States Department of Agriculture (USDA) to estimate stocks in the many countries where stock status is not surveyed.

The approach begins with the following equilibrium condition:

Carry – in stocks + production + imports = exports + carry – out stocks + food use + feed use + industrial use,waste, losses and seed use

The level of stock is estimated as a residual in the balancing condition, presuming that all the other elements are known. The issues related to this method are discussed in Abbott (2013), who also provides suggestions for improvement.

The third method, which is the focus of this paper, is to survey commercial producers and agents to determine the extent of private stock holdings at critical times and to report on stocks held by governments. Among the recommendations of the expert meeting on stock measurement organized by AMIS in London in November 2014 was that private stocks should be estimated by means of surveys1.

Information about stock surveys is available for Brazil, Canada, Indonesia, the Philippines, Ukraine, the United Kingdom and the United States

In many developing countries, especially in Africa, we found examples of agricultural and household surveys that contained sections on stocks. These include: i) the Enquête Permanente Agricole in Burkina Faso; ii) the National Agricultural Sample Survey in The Gambia; iii) the Enquête Agricole de Conjoncture in Mali; and iv) the Enquête Agricole Annuelle in Senegal.

1 http://www.amis-outlook.org/events/detail/en/c/270511/


In developed countries – Canada and the United States of America are examples – data on stocks held on farms can be extracted from small-scale production surveys.

Examples of household surveys can be drawn from Ethiopia, Malawi, Niger, Nigeria, United Republic of Tanzania and Uganda, the countries in the Living Standards Measurement Study Integrated Survey on Agriculture (LSMS-ISA ) programme of the World Bank.

In India, the Directorate of Economics and Statistics of the Ministry of Agriculture and Farmers’ Welfare has conducted a cost-of-cultivation survey every year since 1996. Part of the survey involves collecting information about on-farm stocks of the principal crops and related data.

These practices are discussed below and form the basis of our recommendations.

Our assessment of stock-measurement approaches in agricultural censuses involved 196 questionnaires – 89 in the 2000 round and 107 in the 2010 round. It emerged that on average only 23.6 per cent of the questionnaires reviewed – 22.4 per cent in the 2000 round and 24.7 per cent in the 2010 round – included questions on stocks. In most cases we found only questions about storage capacity; few questionnaires asked about the actual quantities of crops in storage.

1.3 A conceptual framework for measuring stocks

The first step in developing a strategy for stock measurement through sample surveys is to define the relevant stocks. Generally speaking, stocks are defined as the quantities of particular crops held in storage by supply-chain agents, from farmers to consumers, at a given time.

Food stocks can be categorized in terms of the agents holding them, the time at which they are held and the reasons why they are held. To be practical, the categorization of food stocks must be accurate in determining the different forms in which a particular crop may be stored: paddy rice and milled rice are examples (Abbott, 2013).

With regard to the times at which stocks are held, the quantity of any given crop stored at the end of one crop year and carried into the next is considered to be the most informative in terms of establishing prices and determining market outcomes; they are referred to as “carry-out stocks” or “ending stocks”. Carry-out stocks influence the linkage of prices from one crop year to another according to the theory of storage (Wright, 2011): when the stocks are large, prices are linked according to the cost of storage, whereas domestic prices may disconnect when a poor harvest is anticipated and stocks are low (Abbott, 2013). When there is more than one harvest per year, as is the case with rice, for example, the amount of carry-out may also be of interest.


Another relevant dimension for food-security policy is the quantity of stock held in a given year and the cost of storage. Very poor subsistence farmers, for example, may have to sell their grains shortly after harvest for low prices, and then buy seed grain before the next harvest for higher prices (Stephens and Barrett, 2011).

In general, data on short-term stocks may influence market behaviour because they show how crops are apportioned and used as a crop year proceeds. The data required to investigate this are not often available, and hence researchers have to carry out surveys of specific issues (Abbott, 2013).

As will be shown in Section 3, the timing of stock holding affects the way in which surveys are carried out in that it affects the definition of the stocks for which questionnaires are designed, and it determines when and how often surveys should be implemented.

An alternative is to define stocks by identifying the stakeholders who actually own the crop in storage. An initial distinction in this case is that between public and private stocks: public stocks are the reserves of a particular crop owned by government agencies or parastatal farms, and private stocks are those held by farmers, traders and end users.

This distinction can be complicated in that the agent holding the stocks may not be the owner of them. This was the case, for example, of the India Food Corporation when it encountered capacity constraints and contracted private firms to hold some of its reserves. The reality of this issue in national food stock surveys emerged from analysis of the questionnaire used by the Agriculture Division of Statistics Canada for the survey of commercial stocks of corn and soybeans (Statistics Canada, 2010). This asked respondent companies to provide information only on: i) stocks owned by the company and held in its elevators, which were entered in the “company-owned stocks” column; and ii) other stocks, which were recorded in the “stocks held for other” column.

Several categories of “private stock” can be defined: two broad groups are on-farm stocks as opposed to commercial stocks, and in many countries stocks owned by non-farm households may also be relevant for food-security analysis.

Finally, stocks can be classified according to the purposes for which they are held, such as “working stocks” and “reserves”. Working stocks are the quantities of a crop held by a processor, livestock feeder or other agent to ensure continuous operation. Storage in excess of working stocks can be referred to as reserves, buffer stocks or stocks held to influence prices or maintain food supplies from one crop year to another.


Specific categories of reserves are identified when a reserve is held for a particular purpose (Abbott, 2013). Emergency reserves, for example, are typically stocks held by or for a public agency to meet future food aid or public distribution requirements (Rashid and Lemma, 2011). It should be noted that categorization as emergency reserves or buffer stocks is likely to apply to public stocks if there is a legislative mandate for them. In the case of private-sector agents, however, this distinction may be ambiguous because they may hold working stocks and reserves to insure against changing market conditions without clear distinction between them.

Annex 1 lists these concepts in a glossary.

1.4 Structure of the guidelines

This paper analyses the current availability of data on stocks, reviews national practices for surveys of private stocks and provides guidance and tools for developing and implementing survey programmes. It is addressed to chief statisticians and managers in national statistics offices wishing to develop or improve programmes for direct measurement of publicly and privately held stocks of grain and other crops.

Whereas the objective of AMIS was to improve information about wheat, maize, rice and soybeans, this paper covers all storable crops included in the survey programmes of the countries considered, with a focus on grains and oilseeds. Section 1 presents the background of stock surveys, and section 2 considers and categorizes all the survey programmes reviewed. Section 3 presents the main issues related to stock surveys, section 4 offers practical survey guidelines, and section 5 discusses the design and implementation of stock surveys. Section 6 presents conclusions and a synthesis of the main recommendations of the paper.


Current practices in national stock surveys

2.1 Introduction

This paper is the result of an assessment of national stock survey programmes carried out with a view to identifying practices that will contribute to the preparation of guidelines for such surveys in future.

This section discusses the surveys reviewed and groups the countries implementing them into three categories:

• countries surveying stocks held by a single category of private stakeholders;• countries surveying stocks held by more than one category of agent; and• countries that include modules on stocks in surveys covering sectors such as

agriculture, households and business.

2


Examples of each category are provided in Figure 2.1.

FIGURE 2.1Categories of sample surveys for the direct measurement of private stocks

Even though the first approach – conducting small specialized surveys of particular stakeholders – was identified as a best practice in Abbott (2013) and the report of the AMIS expert meeting on stock measurement, the following sub-sections stress that many factors have to be considered in selecting the most suitable strategy, and emphasize that what may work in one country may not be the best practice in another.

2.2 Dedicated surveys of on-farm or commercial stocks

This group is characterized by small surveys focusing on a single category of agents holding and/or owning stocks, identified in Abbott (2013) as best practices. These surveys are designed to elicit the quantity of stocks of a particular crop or group of crops at a given time, and can provide more timely and accurate data than more complex surveys.

This group includes:• the Commercial Stocks Survey and the Palay and Corn Stocks Survey in the

Philippines;• the Off-Farm Grain Stocks Survey in the United States of America;• the Survey of Commercial Stocks of Corn and Soybeans and the Survey of

Commercial Stocks of Major Special Commodities in Canada; and• the Cereal Stocks Survey and the Ports, Cooperatives and Merchants’ Stocks Survey

in the United Kingdom.

Dedicated surveys of a single category of stakeholder

•Off-FarmGrainStocksSurvey(USDA-NASS)•SurveyofCommercialStocksofCornandSoybeans(StatisticsCanada)•SurveyofCommercialStocksoftheMajorSpecialCommodities

(Statistics Canada)•Ports,CooperativesandMerchantsStocksSurvey(DEFRA)•CerealStocksSurveys(DEFRA)•CommercialStocksSurveys(NFA,PhilippinesStatisticsAuthority)•PalayandCornStocksSurvey(BSA,PhilippinesStatisticsAuthority)

Dedicated surveys of more than one category of stakeholder

•NationalSurveyofRiceStocks(BPS,Indonesia)•StocksSurvey(Instituto Brasileiro de Geografia e Estatística, Brazil)

Stock module included in other surveys

•EnquêtePermanenteAgricole(Institut National de la Statistique et de la Démographie, Burkina Faso)

•Crop/StocksSurvey(USDA-NASS)•FieldCropReportingSeries(StatisticsCanada)•Enquête Agricole de Conjoncture (Institut National de la Statistique, Mali)•Enquête Agricole Annuelle, Senegal)•SurveysintheLSMS-ISAprogramme


2.2.1 Commercial Stocks Survey and the Palay and Corn Stocks Survey in the Philippines

The Philippines has been collecting monthly data on stocks of rice and maize, its staple grains, for over 30 years. The survey results are documented in the CountryStat Philippines website1 and in the metadata produced by the Bureau of Agricultural Statistics. The Bureau of Agricultural Statistics, Electronic Archiving and Network Service 2 also provides direct access to microdata and documents related to on-farm stock surveys.

This programme is jointly run by the Bureau of Agricultural Statistics and the National Food Authority (NFA): 3 the former is responsible for the collection of household stocks, whereas the latter monitors stocks in commercial warehouses and in NFA depositories. It should be noted that the households included in the Palay and Corn Stocks Survey are producer households and non-farm households. The results of these monthly surveys provide the inventory of grain stocks for the given reference period. Annex 3 gives full details.

2.2.2 The Off-Farm Grain Stocks Survey in the United States of America

This USDA National Agricultural Statistical Service (NASS) 4 stock survey – a model for best practices in this field – assesses on-farm and off-farm stocks separately each quarter. The former is part of a broad survey of production, yields and areas, whereas the latter is an independent survey to estimate stocks of grains, oilseeds and pulses in non-farm commercial facilities, which ensures that all commercial entities in states that may not be important for the production of the crops concerned are surveyed. Data are reported for on-farm and off-farm stocks by state and nationally.

2.2.3 The Cereal Stocks Survey and the Ports, Cooperatives and Merchants Stocks Survey in the United Kingdom

The Department of Environment, Food and Rural Affairs (DEFRA) in the United Kingdom conducts two separate stock surveys:

• the Cereal Stocks Survey to determine cereal stocks held on farms in England and Wales; and

• the Ports, Cooperatives and Merchants Stocks Survey to determine cereal stocks held by the commercial sector in the United Kingdom.

The results of the two surveys are combined for use by the Government, the European Union and FAO for the assessment of market conditions and evolving agricultural policies, and for the compilation of the United Kingdom’s food balance sheets.

1 http://countrystat.psa.gov.ph/2 http://beans.psa.gov.ph/index.php/home3 http://www.nfa.gov.ph/4 http://www.nass.usda.gov/


2.2.4 The Survey of Commercial Stocks of Corn and Soybeans in Canada

The stock surveys conducted by Statistics Canada are similar to those of NASS-USDA. Questions about on-farm stocks are included in the Field Crop Reporting Series, whereas commercial stocks are measured through the independent Survey of Commercial Stocks of Corn and Soybeans.

This survey focuses on commercial stocks of corn and soybeans and on the industrial use of corn. An similar but separate survey measures stocks of canary seed, chickpeas, dry field peas, lentils, mustard seed and sunflower seed.

2.3 Surveys of more than one category of stakeholderLike those introduced in section 2.2, the two programmes reviewed here are independent surveys of stocks. The difference is that they cover simultaneously all the agents in the value chains who may hold stocks of the crops concerned, rather than focusing on single categories of stakeholders and stocks.

2.3.1 The National Survey of Rice Stocks in Indonesia

The National Survey of Rice Stocks was implemented for the first time in 2015 by the Ministry of Agriculture and the Indonesian Central Statistics Agency. The survey covers all units that are believed to have stocks of rice at a given point in time. Its main objectives are to:

• provide direct estimates of specific items in the national food balance;• identify the amount of rice stored in producer and consumer households as

commercial stocks; and• establish the total amount of national rice reserves.

There are two units of analysis: i) household units – producer households engaged in cultivating rice, and consumer households; and ii) non-household units – small-scale, medium-scale and large-scale businesses, hotels and guest houses, restaurants, food stalls and catering services, hospitals, correctional centres, rice-milling and rice-trading concerns and Badan Urusan Logistik (BULOG, the Indonesian national logistics agency).

A full description of these surveys is provided in Annex 3.


2.3.2 The Stocks Survey in Brazil

The Brazilian stocks survey was developed at the Instituto Brasileiro de Geografia e Estatística in 1958 through the Depósito de Gêneros Alimentícios e Forragens. Implemented every two years, the survey served military objectives such as guaranteeing supplies in times of national insecurity.

The survey has been subsequently redesigned several times to meet changing requirements and conditions. It is currently conducted twice a year and covers all establishments in the national territory that possess at least one building or facility constructed or adapted to store agricultural products. Various users rely on the data produced by this survey: economists at the Ministry of Agriculture, Livestock and Supply, private companies in the logistics sector, private companies involved in agricultural marketing, cereal growers, agricultural cooperatives, universities and the national Department of Agriculture.


2.4 Stock modules included in other surveys

The inventory of survey practices highlighted the existence of many cases in which stocks were estimated by means of specific modules in agricultural or household surveys.

Statistics Canada and USDA collect data on farm stocks as part of the Field Crop Reposting Series in Canada and the Crop/Stocks Survey in the United States of America to provide detailed estimates of crop acreage, yields and production, and the quantities of grains and oilseeds stored on farms. In Georgia, the National Statistics Office measures stocks as part of its annual Sample Survey of Agricultural Holdings.

The measurement of on-farm stocks is an integral part of agricultural surveys in several African countries. Examples include:

• the Enquête Permanente Agricole in Burkina Faso;• the National Agricultural Sample Survey in the Gambia;• the Enquête Agricole de Conjoncture in Mali;• the Enquête de Prévision et Estimation des Récoltes; and• the Enquête Agricole Annuelle in Senegal.

These surveys are structured similarly: they were all designed as annual surveys, generally in two rounds: i) a provisional round to collect the data needed for provisional food balances; and ii) a second round for the production of final post-harvest estimates. With regard to stocks, most of the surveys combine direct measurement of stocks in granaries and interviews with producers to establish the levels of stored stocks.

The first approach – direct measurement– was regarded as more reliable, but the second was easier to administer. In view of the practical difficulties, the survey form for direct measurement was progressively abandoned in favour of the interview questionnaire, which is the current approach. The initial regularity of the surveys has not been maintained in all the countries.

The countries assessing stocks by means of modules included in household surveys are those involved in the LSMS-ISA – Burkina Faso, Ethiopia, Malawi, Mali, Niger, Nigeria, the United Republic of Tanzania and Uganda. The LSMS-ISA survey is modelled on the multi-topic household survey, which features questionnaires on household, agriculture and community matters. The agricultural questionnaire collects information on a core set of indicators, including some on seed and crop storage. The integrated surveys are structured slightly differently in each partner country, but the design ensures that the results are comparable. This is also the case with the stock-related indicators that can be derived from the surveys.

Lastly, we found that the Cost-of-Cultivation Survey in India measures the stocks of the principal crops stored on farms and determines the purpose of storage as part of its output. The questionnaire used in this annual survey is presented in Annex 4.


2.5 Main recommendations

Various best practices have been identified, but there is no single approach suitable for all situations. Numerous factors have to be considered in the selection of a survey strategy: specific data needs, the availability of human and budgetary resources and national statistics capacities are examples.

Abbott (2013) was of the view that the practice in the Philippines of conducting separate small stock surveys of commercial and on-farm agents was a best practice for developing countries. With regard to developed countries, the current practices of NASS-USDA and Statistics Canada, whereby commercial and on-farm stocks are assessed separately, are good models for stock surveys. The surveys of commercial agents are small-scale and limited to stocks, but the surveys of on-farm stocks include questions on areas planted, yields and production levels: the additional questions elicit information about other aspects of food supply and serve to double-check and contextualize the collected values for stocks.

The inclusion of on-farm stock modules in agricultural surveys, an approach used in many developing countries, could be an effective option in countries wishing to optimize existing survey programmes. But there is a danger that combining stock surveys with rural household surveys may reduce the emphasis on collecting stock data: questions about stocks may be omitted, and details of the timing of stock holdings are sometimes lost. Stock surveys must be implemented promptly at particular times in the crop year to capture annual carry-out stock figures.

Large-scale surveys of commercial, on-farm and public stocks are for various reasons seen as the most problematic: the wide scope of such surveys, for example, may delay the collection of results. The fact that this approach is in use in Brazil and Indonesia, however, suggests that this might be the most effective solution when dealing with a vast territory with complex food value-chains.

In view of the foregoing, our recommendation is to conduct separate surveys of on-farm and commercial stocks, recognizing that there will be some variation as to the agents surveyed reflecting the circumstances in each country. In situations where non-farm household stocks might influence food security, as is often the case in poor countries, data on stocks held by consuming household should also be collected. In cases where an agricultural survey is required but the country concerned lacks the financial and human capacities to develop an independent programme, the best alternative may be to survey on-farm stocks by means of a module in a more general survey.


Technical issues affecting stock surveys

3.1 Introduction

This section presents the main technical issues related to stock surveys. The interconnections among them can best be understood by referring to the conceptual framework in section 1.

3.2 Timing

Defining stocks in terms of the time at which they are held affects the survey approach in that: i) it affects the definition of stocks that are the subject of the survey questionnaire; and ii) it determines when and how often a survey should be carried out. If the interest is in capturing annual ending stocks, for example, surveys should be conducted at the beginning of each crop year. Where there are several crops during a calendar year, stocks should be surveyed more than once per year (Abbott, 2013). It should be noted that in considering concepts such as closing and opening stocks, it is essential to refer to the specific crop calendar: in this context AMIS has produced a document summarizing the crop calendars of maize, rice, soybeans and wheat in the main producing countries1.

In the stock surveys reviewed in section 2, the frequency of data collections varied substantially from the monthly stock surveys in the Philippines to the annual agricultural

1 Source: http://www.amis-outlook.org/fileadmin/user_upload/amis/docs/Crop_Calendar/121206-AMIS-online-crop-calen-dar_REDUCED3.pdf

3


surveys in many African countries. The timing of data collection varies significantly, as shown in Table 3.1.

Table 3.1Frequency and Periodicity of Stock Surveys

Frequency Periodicity Reference period Resulting Type of Stocks

USA-CS4 per year Mar, Jun, Sept, Dec 1st day of the month Closing stocks for each

trimester

USA-FS4 per year Mar, Jun, Sept and

Dec1st day of the month Closing stocks for each

trimester

Canada-CS3 per year Mar, Sept, Dec Last day of the reference

periodClosing stocks for each quarter

Canada-FS

4 per year Mar, Jul, Sept and Dec

Calendar year end (Dec), financial year end (Mar), crop year end (Jul/Sept)

Closing stocks for the calendar, financial and crop years

UK-CS2 per year Feb and Jun End of the reference

monthsClosing stocks for each semester

UK-FS2 per year Feb and Jun End of the reference

monthsClosing stocks for each semester

The Philippines-HS

Monthly Every last 2 days of the current month and the first two days of the succeeding month

1st day of the succeeding month

Closing stocks for each month

The Philippines-CS

Monthly First day of each reference month

1st day of the succeeding month

Closing stocks for each month

Brazil2 per year Jan-Mar/Jul-Sept 30 Jun and 31 Dec Ending stocks of each

semester

Burkina Faso-AS

Annual From the 15th to the 30th of September each year

30 Sept Closing stocks for each crop year

Senegal-AS

Annual From the 15th to the 30th of September each year

30 Sept Closing stocks for each crop year

AS = agricultural survey; CS = commercial survey; FS = farm survey; HS = household survey.


3.3 Targeting

Table 3.2 Types of private stakeholders surveyed in the countries considered.

Because of the number of agents potentially owning and holding stocks, any survey method will require a thorough analysis of the supply-chains in order to identify them all. Obviously such studies are specific to each crop and country because any market in any country has its own rules and links among the various actors.

In Figure 3.3 the main findings from a small-scale literature review of the rice and maize supply chains in Bangladesh, India, Indonesia, the Philippines, Thailand and the United States of America are shown in simplified form. The aim of the review was to identify the agents that should be included by a National Bureau of Statistics (NBS) or ministry of agriculture wishing to develop a stock survey, bearing in mind the various reasons for storing grain and the different roles of the various actors.

Households Farms Commercial agents Other agents

USA X X

Canada X X

Brazil X X

Ukraine X X X

UK X X

Georgia X

The Philippines X X X NFA public stocks

Indonesia X X X BULOG stocks

Burkina Faso X

Mali X

Niger X

Senegal X

Rwanda X

Togo X X

Uganda X


Figure 3.3 Simplified representation of the grain value chain

Figure 3.3 shows that the three sub-categories of agents that might hold stocks are:• producing stakeholders and households;• commercial stakeholders; and• public stakeholders.

They are linked by flows of products, and understanding the extent and the direction of the flows helps to identify subject who may own stocks and to forecast the quantity of stocks that the survey should be able to capture. The differences between the categories of farmers and mills shown in Figure 3.3 are, of course, context specific and so ad hoc definitions are required.

Table 3.3 sets out some types of stock that may be owned by the agents listed above: i) food-security stocks, which are held to ensure continuous consumption during a year; ii) speculative stocks, which are held by traders and commercial farmers to manage their marketing operations and iii) operative stocks, which are held by agents to ensure continuity in their work.


Table 3.3 Type of stock owned by different categories of stakeholders

Food-security stocks Speculative stocks Operative stocks

Farmers

subsistence ++ - -

commercial ++ ++ ++

Traders

assembly traders - ++ ++

wholesalers - ++ ++

Millers

small-scale + - ++

medium-scale - + ++

large-scale - ++ ++

Domestic distributors

retailers - - ++

International distributors

importers + ++ ++

exporters + ++ ++

Final users

non-producing households + - -

feed users - ++ ++

seed users - ++ ++

Note: + and ++ indicate the probability of finding certain types of stock in a given category of agents.


3.4 The selection of crops to be included

It is essential to define accurately the selection of crops to be included in the data-collection exercise and their state of processing. In this context it must be borne in mind that different countries adopt different approaches. In some cases a single crop is considered – the national stock survey in Indonesia, for example, is concerned only with rice reserves, whereas the surveys on Brazil, Canada and the United States cover a long list of crops (see Table 3.4).

Table 3.4 Crops included in stock surveys

USA CS

Barley, canola, corn, flax seed, mustard seed, oats, rapeseed, safflower, sorghum, soybeans, sunflower seed, wheat. Rice, rye, peanuts, Austrian winter peas, chickpeas (garbanzos), dry edible peas, lentils (in certain states)

USA FS Corn, sorghum, oats, barley, wheat, durum wheat, soybeans, rice, peanuts

Canada CSGrain corn and soybeans (main survey). Canary seeds, chickpeas, dry field peas, lentils, mustard seeds, sunflower seeds (survey of main special crops)

Canada FS

Barley, canary seed, canola, chickpeas, corn for grain (includes seed corn but excludes sweet corn), coloured dry beans, white dry beans, white peas, dry field peas, flax seed, lentils, linola (solin), mixed grains (two or more grains sown together), mustard seed, oats, spring and autumn rye, soybeans, sunflower seeds (includes sunola and other dwarf varieties), durum wheat, winter wheat, spring wheat

UK CS Wheat, barley, oats

UK FS Wheat, barley, oats

The Philippines HS Palay, rice, corn grains, corn grits

The Philippines CS Palay, rice, corn grains, corn grits

BrazilCotton (lint), cotton (seed), paddy rice, milled rice, rice seed, coffee (natural), coffee (beans), beans black (beans), coloured beans (grain), corn (grain), corn (seed), soybeans (beans), wheat (grain), wheat (seed)

Indonesia Rice

Burkina Faso AS Millet, sorghum, maize, rice, fonio

Togo AS Millet, red sorghum, white sorghum, maize, rice, fonio, wheat

Niger AS Millet, sorghum maize, rice, other cereals

AS = agricultural survey; CS = commercial survey; FS = farm survey; HS = household survey.


3.5 Main recommendations

TimelinessThere is a consensus that stocks should be measured as the quantities of a crop in storage at the point in the crop year when they are at their lowest level, or the first day of the month in which harvest begins. The aim of the survey is hence to estimate annual carry-out or equivalent carry-in stocks, which are the main variables that inform market outcomes. Quarterly surveys provide useful information because they inform market expectations and food-security decisions and help to meet reporting requirements. More frequent measurements such as the monthly assessments in the Philippines may provide only marginally improved information and may not justify the additional cost. In cases where several crops are harvested in a single year more frequent surveys are required to capture seasonal performance.

Accurate definitions of crop years and the start of harvests is important because they make it possible to identify stocks as annual or seasonal carry-out. Crop-year data reflect market and food security outcomes, whereas calendar-year data reflect multiple crop years and more than one production cycle. Calendar-year data do not inform market prices and are not clear indicators of food security.

Surveys must be carried out close to the reference date: this implies that questionnaires must be short and focused. Stock surveys are currently conducted over periods of four to six days on and after the target date of the survey. Comprehensive surveys tend to occupy long periods of time, and hence it becomes difficult to relate measured stocks to specific dates.

TargetingOn-farm stocks and stocks held by commercial agents should be surveyed. Households should only be surveyed if there is evidence that they hold significant stocks. Subsistence farmers may generate marketed surpluses when conditions permit, and they should be surveyed because their food security is dependent on their stocks.

These general conclusion need to be refined though analysis of: i) the selection of stakeholders, which is country-specific and crop-specific; and ii) national supply chains.

Selection of cropsAs a minimum, paddy and milled rice and wheat and coarse grain in grain-equivalent should be included. The items in questionnaires must clearly define and describe the crops concerned. Conversion factors are needed to convert data into a standard format and standard units of measure, and national concepts should be aligned where possible with international standards. Surveys should collect data on all major cereals and pulses, whether tradable or not: limiting them to grains and soybeans must be regarded as a fall-back strategy.


The main steps in designing stock surveys

4.1 Introduction

This section considers some of the main issues in designing a survey of stocks – development and the maintenance of the sampling frame, definition of the sampling design and preparation of questionnaires. On-farm and commercial stocks are discussed separately, with reference to lessons learned from experience in different countries.

4.2. Selection of the sampling frame and sampling design

The review of national practices for selecting sampling frames for stock surveys showed that the frames can be classified according to the three categories of stakeholders likely to own agricultural stocks – households, farms and commercial agents.

In the Philippines, one of the few countries that measures stocks at the household level, non-farming households are selected through the “right coverage” approach which has a fixed starting point; the start times are different in each barangay (village). The resulting list is maintained and reused for the next rounds of the survey. Table 3.8 in Annex 3 gives details.

In Indonesia, the list currently used for the selection of households was derived from the last population census in 2010.

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The following are examples of practices used with regard to farms and producing households:• In the United States of America, farm operations are selected from the area frame

and list frame maintained by USDA-NASS to produce multiple-frame estimates. The list frame contains the data required to identify, locate and contact farmers and agri-businesses; the sources are growers’ organizations, farm programme lists, state and local tax and licence records, lists from federal, state and local agencies, and newspaper and magazine articles. The census of agriculture and NASS surveys are used to update the data. The NASS area frame consists of the land area of the United States of America divided into segments with physical boundaries; farms, crops and animals are associated with the land in the segments.

• In the Philippines, the producing households involved in stock surveys are the farms in the Palay and Corn Production Surveys (PCPS). The list was derived from the 1991 census of agriculture and updated in 2007 and 2011.

• In the United Kingdom, the farms in the cereal stock surveys are selected from DEFRA administrative registers.

• In Brazil, producing and non-producing units are selected from a panel list based on the register used for the warehousing and dry storage survey, which was carried out until 1984. This is augmented by agribusinesses identified in the economic and agricultural censuses, and by the records of public and private agencies with links to the sector.

Commercial stocks are generally surveyed by means of independent surveys that use list frames of commercial firms (see Table 4.1):

• In the Philippines, the NFA uses a list of 93 339 registered business companies operating in the country.

• In Indonesia, the list frame used for the selection of rice-milling businesses was obtained from the 2012 survey of the rice-milling industry. The list used for rice-trading business was developed from a register of companies trading in paddy/unmilled rice and rice. The sampling frame for industrial, accommodation and food-and-beverage businesses was obtained as a subsample of the 2015 staple food consumption survey frame.

• In the United States of America, the commercial survey is an enumeration of all known commercial grain-storage facilities, including 9 400 off-farm facilities.


Table 4.1 Sampling frames adopted for stock surveys in selected countries

In most of these cases administrative registers of business companies are used for commercial stock surveys, whereas list frames of agricultural holdings are used for on-farm stock surveys. The only exception is the USDA-NASS on-farm stock survey, which uses a multiple-frame approach.

It is also useful to distinguish between approaches used for surveying different categories of stakeholders: details of the sample designs adopted are provided in Annex 3.

Analysis of the practices adopted for on-farm stocks showed that countries generally adopt stratified random sampling designs, in some cases with complete coverage of large farms. When on-farm stocks are measured by means of modules in agricultural surveys, the samples can be either all or part of the stock held.

Surveys of commercial stocks are generally made by means of stratified designs covering all major commercial storage entities; the Philippines provides a good example. Table 4.2 shows that most of the commercial and on-farm surveys reviewed were sample surveys, and that only a few commercial stocks surveys were based on an entire population.

Sampling frame

List frame Area frame Administrative register

USA commercial survey x

USA on-farm survey x x

Canada commercial survey x

Canada on-farm survey x

UK commercial survey x

UK on-farm survey x

The Philippines household survey x

The Philippines commercial survey x

Brazil x x

Burkina Faso agricultural survey x

The Gambia agricultural survey x

Mali agricultural survey x


Table 4.2 Sample surveys or complete coverage of the target population

In most of these cases, stocks are assessed by means of sample surveys. Few commercial stock surveys cover all known commercial entities.

Type of investigation

Sample survey Complete coverage

USA commercial survey x

USA on-farm survey x

Canada commercial survey x

Canada on-farm survey x

UK commercial survey x

UK on-farm survey x

The Philippines household survey x

The Philippines commercial survey x

Brazil x

Indonesia x

Burkina Faso agricultural survey x

Mali agricultural survey x

Niger agricultural survey x


4.3. Preparation of survey questionnaires

National stock data systems have to account for different levels of stockholding. Survey questionnaires must reflect this often complex reality and therefore vary substantially from country to country; in some cases only the quantity of stock held by a farm or company is sought, but in others more sophisticated enquiries are made.

Among the best practices identified, simple questionnaires focusing on stock positions are adopted. Stock surveys do not need to be as comprehensive as other survey programmes, and questions that are not directly related to stocks should be avoided.

Stocks are generally measured in local units of measure, but interviewers can make conversions to standard units. Surveys should cover at least grains and oilseeds, and questions need to cover differentiated products such as white or yellow corn, or paddy rice or milled rice; conversion factors must be developed to compute grain equivalents (Abbott, 2013).

In cases where ownership of the crops storage is an issue, questions must be included to clarify matters such as whether stocks are owned by an agent such as a farmer but held in the facilities of another agent.

In developed countries questionnaires often ask about storage capacities, but the concept may not be relevant in developing countries where storage methods may be less developed.

It should be noted that countries that do not conduct surveys often state that stock positions are sensitive information that agents may be reluctant to reveal. This is not an issue in countries where stock surveys are carried out, and in any case prior testing of questionnaires is likely to highlight sensitive issues.

4.3.1 Questionnaires for commercial stock surveys

The questionnaires used to review commercial stocks in some countries are described below and summarized in Table 4.4. They can provide useful inputs for the preparation of questionnaires to elicit the status of stocks at the national level.

• The questionnaire used in Canada requires only the metric tonnage of stocks held in company storage facilities in the country. It is a good example of a survey addressing the ownership issue, in that it also requires respondents to separate the amount of stock owned from the amount held for farmers or other companies.

• The questionnaire developed by the USDA-NASS is more detailed in that it asks about the storage capacities of commercial facilities and for the quantities of crops stored.

• The Philippines questionnaire requires the volumes of palay, rice, corn grit and corn grain, expressed in numbers of 50 kg bags, on the reference day; sales and purchases of these crops during the preceding month and stock in transit on the reference date must also be stated.

• In Indonesia the survey uses separate and detailed questionnaires for all commercial


agents such as rice-milling and rice-trading companies owning or holding stocks. The questionnaires include questions on matters such as quantities, capacity, ownership and flows.

• The Togo survey assesses the quantities of stock held by commercial farmers and traders. The questionnaire elicits the quantities of maize, sorghum, millet and rice stored, expressed in numbers of 100 kg bags. Major producers are also asked to report the quantity of each cereal.

Table 4.4Questionnaire for commercial stocks

Questionnaires for commercial stocks can be fairly detailed: some ask only for quantities of particular crops in storage, but others ask about ownership of stocks and warehouse capacities.

Aspects covered by the questionnaires

Stock quantity Storage capacity Ownership Other

USA x x

Canada x x

UK x

Brazil x x x

Indonesia x x x x

The Philippines x x


4.3.1 Questionnaires adopted for on-farm stocks surveys

Examples of on-farm stocks questionnaires include the following (see also Table 4.5).

• The Canadian farm survey questionnaire contains a section on corn grain and soybeans in storage that seeks to elicit the amount of grain in storage on-farm at the end of the reference trimester, including: i) grains harvested in the current and previous year; ii) grains owned by other agents but stored on-farm; iii) grains purchased for animal feed or seed; and iv) the percentage of corn grain stored for the commercial market.

• The Philippines questionnaire seeks the quantities of palay, rice, corn grain and corn grits owned by households and stored on the property, in another house or in non-commercial granaries; stocks owned and stored in commercial warehouses are excluded. Questions on capacity are not included.

• The questionnaire used in the UK farm cereal stock survey elicits: i) tonnages of wheat, barley and oats in store in the holding on the reference date; ii) the quantities of these crops grown by the farm and in storage; and iii) the quantities of grain bought and stored for on-farm use.

• The Burkina Faso questionnaire measures stocks held in agricultural households by means of a module in the annual agricultural survey. This includes questions about each storage unit and the quantity of grain stock held, expressed in kg.

Table 4.5 Questionnaires for on-farm stocks

Questionnaires on households and farm stocks are generally limited to the quantities in storage on the reference date.

Aspects covered by the questionnaires

Stock quantity Storage capacity Other

USA x x x

Canada x x x

UK x

Brazil x x x

Burkina Faso x

The Philippines x x


4.4. Main recommendations

A list frame approach is better than an area-frame approach. If the available technology is adequate, list and area frames could be integrated to produce multiple-frame estimates. Lists for on-farm and commercial surveys must be regularly updated.

Lists for commercial surveys must include all agents along a supply chain who may hold stocks – traders, commercial storage operators and end users such as food processors and livestock feeders. Lists for on-farm surveys may come from population or agricultural censuses or surveys of rural households.

Public records may offer a starting point for lists, but an agency needs to be responsible for maintaining them because the relevant population will evolve over time, especially as a sector develops. If lists are thought to be outdated they can be updated at different levels: the Indonesian national survey of rice reserves, for example, includes questionnaires designed to update lists of households and non-household units. In the Philippines, maintenance of the frame is an integral part of the monthly surveys: a survey form for the sample households indicates the status of the sample and the result of the visit, whether the interview was successful or not. The completed forms are submitted to the central office and matched with the list of sample households in the production survey.

With regard to sampling design, full coverage of large commercial storage entities and large farms is recommended; for small-scale farmers and traders stratified samples are more cost-effective. The samples must be large enough to give nationally representative results, and the sample design should be based on “stock quantity at the end of the reference period” concept.

Non-farm households should be included in the sample only if there is evidence that they hold significant stocks.

Simple questionnaires should be developed that focus on stocks held at the time of interview. They should also be designed to elicit information about ownership and any public incentive to private stockholding. It is best to use local units of measure and provide conversion factors to the standardize results.

Storage capacity can be a relevant issue in developed countries, but it is less important in situations where storage structures are not well developed.

Annex 4 provides some of the reviewed questionnaires as examples of practices that countries could follow.


The main steps in stock surveys

This section provides guidelines for all phases of stock surveys – data collection, validation, processing and dissemination – and stresses the importance of providing complete documentation of each step. The recommendations are drawn from experience in the countries reviewed.

5.1 Data collection

In most of the countries considered, data on stocks are collected in interviews: examples include the agricultural surveys in Burkina Faso, Mali and Rwanda, the rice stock survey in Indonesia, the Brazilian stock survey and the household and commercial stock surveys in the Philippines.

In the United States of America, Canada and the United kingdom more sophisticated techniques such as electronic data collection and telephone surveys are used; NASS uses a hierarchical system to collect data on on-farm and off-farm stocks. The option of entering data online or using e-mails is offered, but because the response rates are generally low, questionnaires are often sent by surface mail with the option of replies by email or fax. If responses are not received, telephone interviews are conducted, and as a last resort interviewers may go to farms or companies in person to collect the data.

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Statistics Canada uses a similar mail and e-mail process, and also provides respondents with the option of telephone or electronic filing methods. If responses have not been received by a specified date, telephone calls, fax messages or e-mails are used to remind respondents to return the completed questionnaires.

In the United Kingdom, DEFRA uses postal surveys to assess on-farm and commercial stocks.

Objective measurements of quantities of crops in storage facilities is not a common practice.

Table 5.1 Summary of data collection practices.

Most of the countries survey stocks by means of personal interview. The United States of America and Canada combine electronic, telephone and surface mail approaches to maximize response rates. Statistics Canada occasionally visits storage facilities and measures stocks directly to assess the accuracy of the estimates.

Data-collection modalities

Interviews Postal surveys

Hierarchical approach

Direct measurement in the field

USA x

Canada x occasionally

UK x

Ukraine x

Brazil x

Indonesia x

The Philippines x

Burkina Faso x

Rwanda x

Senegal x

Mali x


5.2 Data processing and dissemination

When stock data have been collected, the information must be cross-checked against historical data and current crop statistics to obtain consistent and reasonable estimates. In many cases, on-farm and off-farm stock values are combined with public values after data processing to produce food-balance sheets.

For stock estimates to be useful, reports must be issued within a month of data collection. The underlying survey data should be made publicly available to maximize its usefulness, but this can be done later. Restrictions may be applied to protect the privacy of interviewees and respondents. Examples of the reports made in selected countries are given below.

• NASS-USDA produces reports every January, March, June and September giving data on on-farm, off-farm and public stocks of wheat, durum wheat, corn, sorghum, oats, barley, soybeans, flaxseed, canola, rapeseed and rye, and sunflower, safflower and mustard seed, by state and on-farm or off-farm storage1. The reports on grain stocks from 1973 to January 2016 can be downloaded from the NASS online library or obtained by e-mail subscription. The rice stock reports are available from January 1964 to January 20162.

• The reports and historical datasets from the United Kingdom cereal stock surveys are downloadable from a DEFRA website3. Its biannual Cereal Stocks publication provides the tonnages of wheat, barley and oats held on farms in England and Wales, and of wheat, barley, oats and maize stocks held at ports and by cooperatives and merchants. The information is updated twice a year to give stocks at the end of February and June: the stocks at the end of June in any year form the opening stocks for the following season.

• In the Philippines, stock data are published each month in brief reports of the values of household, commercial and public stocks. The data can be downloaded at aggregate levels from the CountryStat website4.

1 http://usda.mannlib.cornell.edu/MannUsda/viewDocumentInfo.do?documentID=10792 http://usda.mannlib.cornell.edu/MannUsda/viewDocumentInfo.do?documentID=11413 https://www.gov.uk/government/statistics/cereal-stocks 4 http://countrystat.psa.gov.ph/?cont=10&pageid=1&ma=A40PNCNV


5.3 Data documentation

In most of the cases considered, the documentation of stock survey methods and microdata are not publicly available or displayed synthetically. The presentation of NASS-USDA on-farm and off-farm survey documentation, for example, consists of a single page giving minimal details of the survey methods; the case is similar with regard to the United Kingdom survey programmes. In both cases, questionnaires were not available online except for the on-farm stock questionnaires of the United States of America. In the Philippines, the on-farm survey is documented more fully than the commercial survey: the survey methods and microdata for the former are accessible from the National Statistics Authority (PSA); the aggregated data for commercial stocks are available at the CountryStat Philippines website.

5.4. Main recommendations

A sequential approach starting with online data collection and subsequent personal interviews is the preferred option, though in developing countries the interviews will feature more prominently. In many cases direct measurement of a small sample would be a good strategy to validate the information obtained.

The main challenges encountered by data collectors in personal interviews are: i) locating the sample; and ii) finding the targeted respondents at the scheduled time. These considerations are significant because the data-collection period for stock surveys is relatively short. The problems can be minimized by communicating with the designated respondents before the survey takes place, or by mailing questionnaires to them for completion and return by mail or directly to survey staff. Online methods are the most cost-effective, followed by mail, telephone and personal interview; response rates improve in line with increasing cost.

Data collection for commercial stocks is likely to be easier, and the methods may evolve more rapidly. Interviews for on-farm surveys in developing countries could, for example, be implemented by means of computer-assisted personal interviewing technology. On-farm surveys should be conducted by groups with appropriate experience such as statistics agencies. Commercial stocks may be assessed under the authority of a regulatory agency, but this should be carried out in collaboration with an entity experienced in stock surveys.

For stock estimates to be useful, reports must be issued within a month and should include details of public, commercial and on-farm stocks. The data should be disaggregated at the regional and provincial levels, as is the case with most current reports. The reports should show public, commercial and on-farm or household stocks separately.

It would be useful to make underlying survey data public, but probably on a slower schedule. The metadata and documentation of the survey methods should also be made public.


ConclusionsThere is as yet no consensus as to the reasons behind the 2007/08 food-price spike: even now, eight years later, there is still debate with regard to the origins and consequences of the high agricultural and food prices at that time. But there is consensus that lack of good quality data on agricultural and food markets was a major reason for the failure to understand and prioritize the factors that provoked the crisis (Abbott, 2013). A significant recommendation of the G8/G20 examination of food security was that information about agricultural markets must be improved, particularly data on stocks of grain and oilseed.

This is the context in which the present paper was developed. Its purposes are to review national practices adopted for surveys of privately held stocks and to provide guidance and tools for developing and implementing such survey programmes in other countries. All the on-farm and commercial stocks surveys covered in the literature review are assessed in terms of their methods and approaches, and a set of recommendations is provided. A major source document was the 2013 report Improved Methodology for Estimation of Food Stocks by Philip Abbott of AMIS.

The following questions are addressed.

A) What to measure?Stocks should be measured as the quantity of a crop held in storage at the point of the crop year when they are at their minimum, coinciding with the first day of the month in which the harvest begins (Abbott, 2013). This will give an estimate of annual carry-out stocks. These numbers should be recorded separately for commercial, on-farm and public stocks.

For on-farm and commercial stocks, sample surveys are recommended. Reporting on public stocks is not usually a statistical problem, though there are exceptions such as the employment of an external parastatal organization – BULOG – by the Government of

6


Indonesia; in this case sample surveys have a place.

Data should be collected at least for paddy rice, milled rice, wheat and coarse grains, expressed in grain-equivalents. Data are needed on all major cereals and soybeans.

B) When and how often to measure?Stocks should be measured at the beginning of each crop year. If several crops are grown during the same calendar year, data should be collected more than once. Generally speaking, quarterly surveys constitute best practice. Annual surveys should be regarded as the minimum option.

It is important that stock surveys are carried out within a few days of the reference date. This objective can be achieved by means of short, focused questionnaires.

C) How to target the relevant agents for the survey?Most of the assessed surveys of commercial and on-farm stocks use a list frame approach, which is more suitable for stock estimates than an area frame approach. Area frame and list frames can of course be combined to produce multiple frame estimates, but this can only be done where adequate technology is in place.

Lists for on-farm stock surveys may be obtained from censuses and surveys of populations, agriculture and households. Lists of commercial entities may be drawn from sources such as business surveys and administrative records; they must include all commercial agents in a supply chain who may hold stocks, such as traders, commercial storage operators, food processors and livestock feeders1.

The identification of agents to be surveyed is different in for each country and crop; accurate analysis of grain value chains is essential. Households should only be surveyed if there is evidence that they hold significant stocks. Subsistence farmers should be surveyed because the may generate market surpluses under good conditions, and their food security is likely to be dependent on their stocks.

D) How to select the sample for the survey?The best practice cases analysed were usually based on full coverage of large commercial storage entities and farms, and on stratified samples of small farmers and traders. The samples must be large enough to ensure nationally representative results. The sampling strategy should focus on stock status, not the needs of an integrated survey. Samples taken over time are now a panel, with replacement when a sample is “lost”. Lists of commercial entities must be maintained to keep up to date with the establishment of new companies and the winding up of others. (Abbott, 2013).

1 Abbott, 2013.


E) How to prepare the questionnaires?Short questionnaires are needed to ensure that surveys are conducted promptly; they should focus on stocks held at the time of interview and should elicit information about ownership issues and public incentives to stock holding. Questions on capacity and storage infrastructures are less relevant in developing countries.

F) How to collect the data?The best practices in use in Canada, the except for the on-farm stock questionnaires of the United States of America. and other developed countries are recommended for countries with adequate economic resources. The recommended approach is to collect initial data online, with subsequent personal interviews. Direct follow-up such as direct measurement of quantities of stock held is needed to address the problem of missing responses. Data collection for commercial stocks is likely to be easier and the methods may evolve quickly; the fall-back strategy adopted in many developing countries is to resort to personal interviews only.

On-farm surveys should be conducted by entities with experience of stock surveys such as statistics agencies. Commercial stocks may be assessed under the authority of a regulatory agency, but this should be done in collaboration with a suitably experienced entity; the focus must be strictly confined to stocks (Abbott, 2013).

G) Documentation and results reportingSurvey documentation – the sampling design and sampling frames, sample size, the questionnaires and methods – should be made public to ensure transparency. To be useful for policymaking and food security, stock reports must be disseminated within a month of data collection and present disaggregated data for on-farm and commercial stocks. The publication of other information about stock surveys is useful, but this is likely to involve a longer timeframe. Restrictions should be in place to protect the privacy of interviewees and respondents.

We recommend that the conceptual, technical, human and budgetary issues related to stock surveys be handled by means of an approach based on the Generic Statistical Business Process Model summarized in Figure 6.1. This sets out the business processes needed to produce official statistics. In particular, it provides: i) a standard framework and harmonized terminology for statistics organizations, which helps them to modernize their processes and share methods and components; ii) a means of integrating data and metadata standards into a template for process documentation, thereby harmonizing computing infrastructures; and iii) a framework for quality assessment and improvement. The GSBPM is used by 50 statistics organizations worldwide.


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Notes


Abbott, P. 2010. Stabilization Policies in Developing Countries after the 2007-2008 Food Cri-sis. OECD Working Paper TAD/CA/APM/WP (2010) 44. OECD Publication: Paris. Available at: http://www.oecd.org/tad/agricultural-policies/46340396.pdf. Accessed on 14 September 2016.

Abbott, P. 2013. Improved Methodology for Estimation of Food Stocks. FAO Publication: Rome.

Abbott, P. 2014. Lessons from Recent Stocks Adjustments and their Measurement. FAO Pub-lication: Rome. Available at: http://www.fao.org/fileadmin/templates/est/meetings/stocks/Abbott-Lessons_from_Recent_Stocks_Adjustments.pdf. Accessed on 14 September 2016.

Australian Bureau of Statistics. 2015. Wheat Use and Stocks, Australia [Online]. ABS Publi-cation: Canberra. Available at: http://www.abs.gov.au/AUSSTATS/[email protected]/Lookup/7307.0Ex-planatory%20Notes1May%202010?OpenDocument. Accessed on 14 September 2016.

Bureau of Agricultural Statistics. Department of Agriculture, Government of the Philip-pines. 2015. CountrySTAT, Philippines [Online]. CountrySTAT Philippines Publication: Manila. Available at: http://countrystat.psa.gov.ph. Accessed on 14 September 2016.

Bureau Of Agricultural Statistics. Department of Agriculture, Government of the Philip-pines. 2014. Commercial Stocks Survey Questionnaire. CountrySTAT Philippines Publication: Manila. Accessed on 14 September 2016.

Bureau Of Agricultural Statistics. Department of Agriculture, Government of the Philip-pines. 2013m. Palay and Corn Stock Survey (PCSS) [Online]. CountrySTAT Philippines Publi-cation: Manila. Available at: http://countrystat.psa.gov.ph. Accessed on 14 September 2016.

Bureau Of Agricultural Statistics. Department of Agriculture, Government of the Philip-pines 2009. Palay and Corn Stocks Survey Questionnaire. CountrySTAT Philippines Publi-cation: Manila. Available at: http://beans.psa.gov.ph/index.php. Accessed on September 14 2016.

References


Chowdhury, N. 1992. Rice markets in Bangladesh: a study in structure, conduct and perfor-mance. USAID Report. USAID Publication: Dhaka. Available at: http://pdf.usaid.gov/pdf_docs/PNABS179.pdf. Accessed on 14 September 2016.

DEFRA. 2015. Cereal Stocks in June 2015. DEFRA Publication: London. Available at: https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/456492/cere-alstocks-statsnotice-27aug15.pdf. Accessed on 14 September 2016.

Dennis, K., Galván, P.K. & Kane, J. 2008. Rice in Western Hemisphere: Industry Dynamics and Opportunities for Waterbird Conservation. University of Maryland Publication: College Park, USA. Available at: http://hydrodictyon.eeb.uconn.edu/people/elphick/rice/Dennis_et_al_2007_UMD_rice_report.pdf. Accessed on 14 September 2016.

FAO. 2001. Food Balance Sheets: A Handbook. FAO Publication: Rome. Available: http://www.fao.org/3/a-x9892e.pdf. Accessed on 14 September 2016.

FAO, IFAD, IMF, OECD, UNCTAD, WFP, WOLRD BANK, WTO, IFPRI, and UNHLTF. 2011. Price Volatility in Food and Agricultural Markets: Policy Responses. FAO-OECD Publication: Rome and Paris. Available at: http://www.oecd.org/tad/agricultural-trade/48152638.pdf. Ac-cessed on 18 August 2016.

World Bank, FAO & UN. 2013. Global Strategy to Improve Agricultural and Rural Statistics. Available at: http://www.fao.org/fileadmin/templates/ess/documents/meetings_and_work-shops/ICAS5/Ag_Statistics_Strategy_Final.pdf. Accessed on 14 September 2016.

Food Planning and Monitoring Unit (FPMU). Bangladesh Ministry of Food and Disaster Management. 2014. Bangladesh Food Situation Report, June 2014. Bangladesh Food Situa-tion Reports. FPMU Publication: Dhaka.

Food Planning and Monitoring Unit (FPMU). Bangladesh Ministry of Food and Disaster Management. 2014. Fortnightly Foodgrain Outlook, September 2014. FPMU Publication: Dha-ka. Available at: http://www.nfpcsp.org/agridrupal/fortnightly-foodgrain-outlook. Accessed on 14 September 2016.

Hsu, H.H. & Gale, F. 2001. USDA Revision of China Grain Stock Estimate. In Hsu, H.H. & Gale, F., China: Agriculture in Transition (pp. 53-56). Available at: http://www.ers.usda.gov/media/904910/wrs012k_002.pdf. Accessed on 14 September 2016.

Instituto Brasileiro de Geografia e Estatistica (IBGE). 2015a. Systematic Survey of Agri-cultural Production [Online]. IBGE Publication: Brasília. Available at: http://www.ibge.gov.br/english/estatistica/indicadores/agropecuaria/lspa/default.shtm. Accessed on 14 September 2016.

Instituto Brasileiro de Geografia e Estatistica (IBGE). 2015b. Survey of Stocks [Online]. IBGE Publication: Brasília. Available at: http://www.ibge.gov.br/english/estatistica/indica-dores/agropecuaria/estoque/default.shtm. Accessed on 14 September 2016.


Jabbar, M.A. 2009. Estimation of Private Stock of Rice in Bangladesh: In Search of a Prac-ticable Methodology. Report prepared for the National Food Policy Capacity Strengthen-ing Program (NFPCSP). NFPCSP Publication: Dhaka. Available at: http://www.nfpcsp.org/agridrupal/content/estimation-private-stock-rice-bangladesh-search-practicable-methodolo-gy-0. Accessed on 14 September 2016.

Lowe, M. & Gereffi, G. 2008. A Value Chain Analysis of Selected California Crops. Centre on Globalization Governance & Competitiveness. Duke University Publication: Durham, NC, USA.

McCarthy, S., Singh, D.D: & Schiff, H. 2008. Value Chain Analysis of Wheat and Rice in Uttar Pradesh, India: Partnership for Innovation and Knowledge in Agriculture. ACDI/VOCA Publication: Washington, D.C.

NASS/USDA. 2013a. Surveys: Off-Farm Grain Stocks [Online]. NASS/USDA Publication: Washington, D.C. Available at: http://www.nass.usda.gov/Surveys/Guide_to_NASS_Surveys/Off-Farm_Grain_Stocks/. Accessed on 14 September 2016.

NASS/USDA. 2013b. Agricultural Survey Interviewer’s Manual, Chapter 10 – Grains and Oil-seeds in Storage. NASS/USDA Publication: Washington D.C. Available at: http://www.nasda.org/File.aspx?id=27025. Accessed on 14 September 2016.

Rashid, S. & Lemma, S. 2011. Strategic grain reserves in Ethiopia. IFPRI Publication: Wash-ington D.C.

Sharma, V., Giri, S. & Rai, S.S. 2013. Supply Chain Management of Rice in India: A Rice Pro-cessing Company’s Perspective. International Journal of Managing Value and Supply Chains, 4(1): 25-36.

Statistics Canada. 2013. Miller’s Monthly Report. Available at: http://www23.statcan.gc.ca/imdb/p2SV.pl?Function=getSurvey&SDDS=3403&lang=en&db=imdb&adm=8&dis=2. Ac-cessed on 14 September 2016.

Statistics Canada. 2015a. Survey of Commercial Stocks of corn and soybeans: Question-naire for country elevators and animal feed grain mills. Available at: http://www23.statcan.gc.ca/imdb-bmdi/instrument/3464_Q6_V14-eng.pdf. Accessed on 14 September 2016.

Statistics Canada. 2015b. Survey of Commercial stocks of the major special crops. Avail-able at: http://www23.statcan.gc.ca/imdb/p3Instr.pl?Function=getInstrumentList&Item_Id=226751&UL=1V&. Accessed on 14 September 2016.

Statistics Canada. 2015c. December Farm Survey General Information. Available at: http://www23.statcan.gc.ca/imdb-bmdi/instrument/3401_Q7_V14-eng.htm. Accessed on 14 Sep-tember 2016.

Stephens, E. C. & Barrett, C.B. 2011. Incomplete Credit Markets and Commodity Marketing Behavior. Journal of Agricultural Economics, 62(1): 1-24


World Bank. The Living Standard Measurement Study (LSMS). World Bank Publica-tion: Washington, D.C. Available at: http://econ.worldbank.org/WBSITE/EXTERNAL/EX-TDEC/EXTRESEARCH/EXTLSMS/0,,contentMDK:21610833~pagePK:64168427~piP-K:64168435~theSitePK:3358997,00.html. Accessed on 14 September 2016.

World Bank. The Living Standard Measurement Study – Integrated Surveys on Agriculture (LSMS-ISA). World Bank Publicatio: Washington, D.C. Available at: http://econ.worldbank.org/WBSITE/EXTERNAL/EXTDEC/EXTRESEARCH/EXTLSMS/0,,contentMDK:23512006~pageP-K:64168445~piPK:64168309~theSitePK:3358997,00.html. Accessed on 14 September 2016.

World Bank. 2011. Trusting Trade and the Private Sector for Food Security in Southeast Asia. World Bank Publication: Washington, D.C. Author: Hamid R. Alavi with Aira Htenas, Ron Kopicki, Andrew W.Shepherd and Romon Clarete Available at: https://openknowledge.worldbank.org/bitstream/handle/10986/2384/659560PUB0EPI105737B0Trusting0Trade.pd-f;sequence=1. Accessed on 14 September 2016.

Trostle, R. 2009. Fluctuating Food Commodity Prices: A Complex Issue With No Easy An-swers. Amber Waves, 6: 11-17.

UN High-Level Task Force (HLTF). 2009. Progress Report, April 2008-October 2009. UN HLTF Publication: New York, USA. Available at: http://un-foodsecurity.org/sites/default/files/09progressreport.pdf. Accessed on 14 September 2016.

UNECE. 2013. Generic Statistical Business Process Model, GSBPM ver 5.0. Available at: http://www.istat.it/it/files/2013/12/GSBPM-5_0.pdf Accessed on 14 September 2016.

WFP. 2015. Bangladesh Food Security Monitoring Quarterly Bulletin. Issue No. 21. WFP Publi-cation: Rome. Available at: http://documents.wfp.org/stellent/groups/public/documents/ena/wfp277273.pdf. Accessed on 14 September 2016.

Wiggins, S. & Keats, S. 2009. Grain stocks and price spikes. Overseas Development Insti-tute Publication: London.

William, J.C. & Wright, B.D. 1991. Storage and Commodity Markets. Cambridge University Press: Cambridge, UK.

Wright, B.D. 2011. The Economics of Grain Price Volatility. Applied Economic Perspectives and Policy, 33: 32-58.


Notes


Annex 1 Glossary for stocks data

1 2 3 4 5 6 7 8

1 Abbott, 2013.2 FAOSTAT Glossary: http://faostat3.fao.org/mes/glossary/E.3 To be discussed.4 FAOSTAT Glossary: http://faostat3.fao.org/mes/glossary/E.5 Adapted from Abbott, 2013.6 Adapted from Abbott, 2013.7 Adapted from Abbott, 2013.8 Adapted from Abbott, 2013.

Concept Definition

StocksQuantity of a commodity held in storage by any of the various agents along the supply chain, from farmers to consumers, at a given moment in time.1

Carry-in stocks (or opening stocks)

Quantity in stocks available at the beginning of the reference period irrespective of origin, i.e. including domestic production and imports. In principle, these should include stocks held at various levels between the farm and the level at which the “final consumption” of the commodity is measured. Thus, government stocks, stocks with manufacturers, importers, exporters and other wholesale merchants, transport and storage enterprises and stock on farms are included.2

Carry-out stocks (or closing stocks)

Quantity of stocks held at the end of the reference period and carried into the next irrespective of origin, i.e. including domestic production or imports. Carry-out stocks are equal to the Carry-in stocks of the following reference period.3

Stock variation (or Change in Stocks)

Changes in stocks occurring during the reference period at all levels between the production and the retail levels, i.e. including changes in government stocks, in stocks with manufacturers, importers, exporters, other wholesale and retail merchants, transport and storage enterprises and in stocks on farms4.

Working (or pipeline stocks)

Quantity of a commodity held in storage by a food processor, livestock feeder or other agent in the normal course of its activity to ensure continuous operations5.

Reserves (or buffer stocks)6

Quantity of storage in excess of working stocks. They can also be defined as the quantity of a commodity held in storage to influence market outcomes or maintain food supplies throughout the crop year.

Public stocks Quantity of a commodity held in storage by public agencies or parastatal farms, irrespective of final use (working stocks or reserves)7.

Private stocks Quantity of a commodity held in storage by any of the private agents along the supply chain, from farmers to consumers8.


Table of Internet links

Internet links for stocks

International Resources Links

FAOSTAT http://faostat3.fao.org/home/E

FAOSTAT-Food Bal-ance http://faostat3.fao.org/browse/FB/*/E

AMIS http://www.amis-outlook.org/

AMIS database http://statistics.amis-outlook.org/data/index.html#DOWNLOAD

LSMShttp://econ.worldbank.org/WBSITE/EXTERNAL/EXTDEC/EXTRESEARCH/EXTLSMS/0,,contentMDK:21610833~pagePK:64168427~piP-K:64168435~theSitePK:3358997,00.html

LSMS-ISAhttp://econ.worldbank.org/WBSITE/EXTERNAL/EXTDEC/EXTRESEARCH/EXTLSMS/0,,contentMDK:23512006~pagePK:64168445~piP-K:64168309~theSitePK:3358997,00.html

IHSN data catalog http://catalog.ihsn.org/index.php/catalog

USDA http://www.usda.gov/wps/portal/usda/usdahome

IGC http://www.igc.int/en/Default.aspx

Annex 2


National Resources Links

Brazil

IBGE http://www.ibge.gov.br/home/

IBGE-Survey of Stocks http://ibge.gov.br/english/estatistica/indicadores/agropecuaria/estoque/default.shtm

IBGE-Metadata Bank https://metadados.ibge.gov.br/consulta/defaultEstatistico.aspx

Canada

Statistics Canada http://www.statcan.gc.ca/start-debut-eng.html

Statistics Cana-da-SCSMSC http://www.statcan.gc.ca/eng/survey/agriculture/3476

Statistics Cana-da-SCSCS http://www23.statcan.gc.ca/imdb/p2SV.pl?Function=getSurvey&SDDS=3464

FCRS http://www23.statcan.gc.ca/imdb/p2SV.pl?Function=getSurvey&SDDS=3401

Indonesia

Statistics Indonesia http://www.bps.go.id/

The Philippines

CountryStat Philip-pines http://countrystat.psa.gov.ph/

PSA http://agstat.psa.gov.ph/

BEANS http://beans.psa.gov.ph/index.php/home

PCSS 2009 http://beans.psa.gov.ph/index.php/catalog/13

RCMTSI http://countrystat.psa.gov.ph/index.asp?cont=10&pageid=1&ma=A40PNCNV

NFA http://www.nfa.gov.ph/

United Kingdom

DEFRA https://www.gov.uk/government/organisations/department-for-environment-food-ru-ral-affairs

Cereal Usage and Stocks Collection https://www.gov.uk/government/collections/cereal-usage-and-stocks

United States of America

USDA-NASS http://www.nass.usda.gov/index.php

Off-Farm Grain Stocks Survey

http://www.nass.usda.gov/Surveys/Guide_to_NASS_Surveys/Off-Farm_Grain_Stocks/

Grain Stocks Reports http://usda.mannlib.cornell.edu/MannUsda/viewDocumentInfo.do?documen-tID=1079

Rice Stocks Reports http://usda.mannlib.cornell.edu/MannUsda/viewDocumentInfo.do?documen-tID=1141


Documentation of stocks surveys in countriesTable 3.1 ESTIMATION OF ON-FARM STOCKS IN BURKINA FASO

Identification

Country Burkina Faso

Title Enquête Permanente Agricole (EPA)

Study type Agricultural survey series with specific module/questionnaire for estimatingf cereal stocks

Series information

The EPA is a survey programme on agricultural production. In particular, it is a series of surveys having the main objective of estimating the annual volume of agricultural production.The survey is used mainly by policymakers to obtain:Forecasts of cereal production (October);Post-harvest estimates of agricultural production (March/April)Cereal stocks held on farms are measured every year with a specific form.

Overview

Type of data Agricultural survey data. In particular, the survey collects data on farm cereal stocks.

Unit of analysis Agricultural households.

ScopeThe questionnaire on stocks requires the code to be reported, to identify the storing facility, the type of cereal stored, the quantity stored in local units and the equivalent quantity (kg).

Geographic coverage The survey covers all rural areas in the country.

Primary investigatorDirection Général des Prévision et des Statistiques Agricoles/Direction des Statistiques Agricoles; Ministère de l’Agriculture, de l’Hydraulique et des Ressources Halieutiques

Annex 3


Sampling

Sampling procedure

The sample adopted for the agricultural survey has evolved since 1990 (when the programme was launched). Today, it includes 706 villages and 4,370 agricultural households. The module on stocks (Fiche 5: Estimation des Stocks Cerealiers) is distributed to 100 per cent of the sample used for the EPA.

Data collection

Data collection dateThe data collection period for the agricultural survey starts in August every year. In particular, the collection of data on the modules for cereal stocks and crop forecasting occurs between 15 and 30 September.

Data collection modality Face-to-face.

Data access

Release dates NA

Access URL NA

Access terms and conditions NA


Table 3.2ESTIMATION OF COMMERCIAL STOCKS IN THE UNITED STATES OF AMERICA

Identification

Country United States of America

Title Off-farm Grain Stocks Surveys

Study type Survey series for the direct estimation of grains, oilseeds and pulse crops stored in any commercial facility off the farm.

Series information

The primary objective of the survey is to obtain a detailed estimate of commercial stocks of grains, oilseeds and pulse crops. Data are used by commodity markets, educational institutions, state and federal agencies, farm and ranch operators, and others, for the purposes of market assessment, planning, decision-making, and ongoing research.

Overview

Type of data Off-farm stocks

Unit of analysis All commercial grain storage facilities

Scope

The types of information collected by the survey are the following:Storage Capacity: storage capacity of ALL reported locations (in Bushels), numbers of storage operations operated and reported for by the firm, changes in storage capacities since one year before (how much has been added, how much has been discontinued)Stored quantity: Quantity stored of the commodities mentioned above. Intention to purchase grain, oilseeds or dry beans directly from farmers during the following year (December questionnaire).

Geographic coverage

The off-farm survey is conducted in each State for barley, canola, corn, flaxseed, mustard seed, oats, rapeseed, safflower, sorghum, soybeans, sunflowers, and wheat. Grain stocks frequently move to areas other than those where they were produced, thus requiring coverage by all States to fully account for all off-farm stocks. Minnesota, North Dakota and South Dakota are the only States that estimate rye stocks. Austrian winter peas, chickpeas (garbanzos), dry edible peas and lentils are estimated in California, Idaho, Minnesota, Montana, Nebraska, North Dakota, Oregon, South Dakota and Washington.

Primary investigator United States Department of Agriculture, National Agricultural Statistics Service (USDA-NASS)

Sampling

Sampling procedureThe off-farm survey is an enumeration of all known commercial grain storage facilities. These include approximatively 9,400 off-farm storage facilities (with nearly 10.4 billion bushels of storage capacity).

Data collection

Data collection dates

The survey is conducted four times per year, namely in March, June, September and December. Rice stocks surveys are conducted in six States in March, August and December. California conducts an additional survey in October. Peanut stocks surveys are conducted monthly.

The reference date is always the first day of the respective month, except for peanuts, for which it is the last day of the previous month. Data for major crops (barley, corn, oats, soybeans, and wheat) are collected each quarter, while data for minor crops (flaxseed, mustard seed, rapeseed, safflower, and sunflowers) are collected once or twice a year.

Data collection modality

Data collection is performed through a hierarchical strategy. More cost-effective electronic data collection is attempted first, with fallbacks to mail surveys, telephone interviews, and personal interviews. Then, off-farm survey data are reviewed at State and national level together with on-farm survey data, to obtain reasonable and consistent estimates.


Data processing

Editing

After data collection, off-farm survey data are reviewed at State and national level together on-farm survey data, to obtain reasonable and consistent estimates. After estimates are made for on-farm and off-farm stocks, these totals are combined and evaluated by means of balance sheets. This method utilizes other sources of data to verify the reasonableness of the stocks estimates. Estimates of production, imports, exports, crushings, millings, and all other recorded uses of grains and oilseeds are reviewed to ensure that beginning stocks, production, utilization, and ending stocks are within a reasonable balance and present the best possible estimate of stocks.

Data Access

Publishing agency USDA-NASS http://www.usda.gov/wps/portal/usda/usdahome

Release dates

This publication is issued four times per year (January, March, June and September). For example, in 2016, the first report was released on January 12; the pending releases are scheduled on 31 March, 30 June and 30 September.

Access URLThe national report may be downloaded from the USDA-NASS publication website (http://usda.mannlib.cornell.edu/MannUsda/viewDocumentInfo.do?documentID=1079).

Access terms and conditions

The reports may be downloaded from the dedicated website; alternatively, it may be received by subscribing at the following link: https://usda.mannlib.cornell.edu/MannUsda/displayPatronSubscriptions.do?reports=0000. The conditions to access microdata are not specified.


Table 3.3 ESTIMATION OF ON-FARM STOCKS IN THE UNITED STATES OF AMERICA

Identification

Country United States of America

Title Crop/Stocks Surveys

Study type Crop survey series with specific module/questionnaire for the estimation of on-farm main crops.

Series information

The Crop/Stocks surveys provide detailed estimates of crop acreage, yields and production, and the quantities of grain and oilseeds stored on farms. The data are used by commodity markets, educational institutions, state and federal agencies, farm and ranch operators, and others, for the purposes of market assessment, planning, decision-making and ongoing research.

Overview

Type of data Agricultural survey data. In particular, the surveys collect information on the on-farm stocks of storable agricultural crops.

Unit of analysis Agricultural Holdings

Scope

Operators provide data on the total acres they operate, the acreage of each commodity of interest and the amount produced at harvest. The grain and oilseeds stored are asked in terms of the amount stored of each grain or oilseed. Each State is asked for a unique set of commodities, depending on which commodity is grown in the State and at what acreage level. Commodities are collected according to their growing season. For Example, data for a small grain, such as winter wheat, would be collected in December, March, and June, to determine acreage, and in September to determine production. On the other hand, data for row crops, such as corn, are collected in March and June for acreage determination and again in December, after the majority of the crop is harvested and the production has been determined.

Geographic coverage All States

Primary investigator United States Department of Agriculture, National Agricultural Statistics Service (USDA-NASS)

Sampling

Sampling procedure

Farm operations are selected from an area frame and a list frame to produce "multiple frame" estimates. Farm and ranch operators from the list frame are selected by size, depending on the proportion of the commodities of interest of the operation, compared to other operators on the list. The area frame sample is added to account for land that was not covered by the list frame. The sample targets producers of row crops and small grains, as well as farm operations with grain storage capacity.

Sample size targets are set for each commodity surveyed. The desired number of samples for each commodity is controlled with a minimum overall sample size. Total sample sizes range from approximately 65 000 in September to approximately 81 000 in June, because the number of crops of interest varies between quarters. In the Crops/Stocks survey, targeting is important for the row crops and small grains stocks panels, for rare commodities, and specialty crops. Specialty crops such as potatoes can also be summarized as a separate survey, to meet earlier publication dates.


Data collection


Crops/Stocks surveys are conducted four times a year. The farmers’ planting intentions are collected in March. The acres planted and acres expected for harvest are collected in June. The small grains acres harvested and production are collected in September, and row crop and hay production in December. Information on grain and oilseeds on-farm stocks for major commodities (corn, soybeans, wheat, sorghum, barley and oats) are collected in all four quarters, while specialty crops such as rye, flaxseed, rapeseed, safflower, mustard seed, canola and hay are collected once a year in selected producing States. Other specialty crops, such as sunflowers, dry edible peas, Austrian winter peas, lentils and chickpeas (garbanzo) are surveyed twice a year in selected producing States.Data are collected for approximately two weeks, beginning on the last day of the month prior to the survey reference date.


Modes of data collection include electronic data reporting (Internet) mail, telephone, Computer-Assisted Telephoning Interviewing (CATI) and personal interviewing. Over the 75 per cent of the data are collected by phone and CATI.

Data processing

Editing

The on-farm stocks data are reviewed at State and national level together with the off-farm stocks data, using historical data and current crop status, to obtain reasonable and consistent estimates.After estimates are made for on-farm and off-farm stocks, these totals are combined and evaluated by means of balance sheets. This method utilizes other sources of data to verify the reasonableness of the stocks estimates. Estimates of production, imports, exports, crushings, millings and all other recorded uses of grains and oilseeds are reviewed, to ensure that beginning stocks, production, utilization, and ending stocks are within a reasonable balance and present the best possible estimate of stocks.

As for survey reliability, on-farm stocks estimates are subject to sampling variability, because not all the operations holding on-farm stocks are included in the sample. This variability, as measured by the relative standard error at the US level, is approximatively 3.6 per cent for corn, 11.8 per cent for soybeans, and 2.9 per cent for all wheat.

Data Access

Publishing agency USDA-NASS http://www.usda.gov/wps/portal/usda/usdahome

Release dates

This publication is issued four times a year (January, March, June and September). For example, in 2016, the first report was released on January 12; the pending releases are scheduled for 31 March, 30 June and 30 September.

Access URLThe national report may be odwnloaded from the USDA-NASS publication website (http://usda.mannlib.cornell.edu/MannUsda/viewDocumentInfo.do?documentID=1079).

Access terms and conditions

The reports may be downloaded from the dedicated website; alternatively, it may be received by subscribing at the following link https://usda.mannlib.cornell.edu/MannUsda/displayPatronSubscriptions.do?reports=0000. The conditions to access microdata are not specified.


Table 3.4ESTIMATION OF ON-FARM, COMMERCIAL AND PUBLIC STOCKS IN INDONESIA

Identification

Country Indonesia

Title National Survey on Rice Stocks (NSRS) 2015

Study type First round of a survey series on the rice stocks held by all agents along the rice value chain.

Series Information

The NSRS was launched in 2015, with the following objectives:Provide a direct estimate of one of the food balance voices (stocks) used to estimate rice consumptions; Identify the amount of rice stored in the households (both producers and consumers) and outside the households (commercial stocks); andEstablish the amount of national rice reserves.

Overview

Type of data On-farm, commercial, non-producing households, and public stocks.

Unit of analysis

Households Units: Producer households engaged in planting rice crops; and consumer households, i.e. households other than those engaged in cultivating rice crops.

Non-Household Units: Micro- and small-sized businesses; medium- and large-sized businesses; accommodation services (hotels, guesthouses, etc.); food and beverage businesses (restaurants, food stalls and catering services); hospitals; correctional centres; rice milling businesses and rice trading businesses; and the Indonesian Food Logistic Company (BULOG).

Scope

The NSRS is based on 5 groups of questionnaires: the questionnaires for households, those for rice milling units, those for industry and food and beverages businesses, those for rice merchants and the questionnaire for BULOG.

Geographic coverage

The survey provides complete national coverage. The enumeration areas comprise 20 provinces and 114 districts/municipalities around the country. The provinces are Aceh, North Sumatra, West Sumatra, Jambi, South Sumatra, Lampung, Riau Islands, Jakarta, West Java, Banten, Central Java, Yogyakarta Special Region, East Java, Bali, West Nusa Tenggara, West Kalimantan, South Kalimantan, Central Sulawesi, South Sulawesi and Maluku. To obtain data from BULOG, data collection was carried out in Regional Divisions across 34 provinces throughout Indonesia.

Primary investigatorDirectorate of Food Crops, Horticulture, and Plantation Statistics, Deputy for Production Statistics of BPS (Central Statistical Agency), and Centre for Food Availability and Crisis, Food Security Agency, Ministry of Agriculture.


Sampling

Sampling procedure

The survey adopted two categories of sampling frame:A) Sampling frame for household units. The sampling frame adopted in the first stage of the sampling consists of a list of census blocks, resulting from the updating of an online village master file. The list frame adopted to select the households was derived from the most recent population census. This list was updated using a specific questionnaire.B) Sampling Frame for company/business units.The sampling frame for rice milling businesses was obtained from the Rice Milling Industry Survey of 2012. The rice milling businesses were stratified by size. The sampling frames for the rice trading businesses, divided into a first-stage sampling frame (list of census blocks) and a second-stage sampling frame (list of buildings/households/businesses in selected census blocks). The sampling frame for industry, accommodation and food and beverages businesses was a subsample of the 2015 Staple Consumption Survey.

The total sample consisted of: 2 000 producing households, 10 000 consuming households, 10 000 hotels/restaurants/catering services, 10 000 rice trading businesses, 5 257 rice milling industries and 2 000 other rice businesses.

Data collection


The NSRS 2015 was the first edition of this rice stocks survey. Data collection was scheduled three times during the year, i.e. the first two weeks of April, July and September. On each occasion, the reference dates were the last day of the preceding month and the first day of the current one (for example, in April, the reference days for reporting stocks were 31 March and 1 April). In Indonesia, rice is harvested from February to April (for the main season) and from July to September (for the secondary season).


Data are collected through direct interviews with respondents. For the household stocks, respondents are the household heads. If these are unavailable, then household members who are well-acquainted with the household’s storage practices are asked. As for companies/businesses, interviews are conducted with company representatives who have information on the company’s storage practices.

Data Access

Publishing agency Statistics Indonesia (http://www.bps.go.id/ and Ministry of Agriculture).

Release dates NA

Access URL NA



Table 3.5ESTIMATION OF ON-FARM STOCKS IN THE UNITED KINGDOM

Identification

Country United Kingdom

Title Cereal Stocks Surveys

Study type On-farm stocks survey in England and Wales.

Series information

The Cereal Stocks Surveys are conducted to determine the stocks of key cereals held on farms in England and Wales. The information provided by this survey, combined with those obtained through the Ports, Co-operatives and Merchants Surveys, is used by the UK government, the EU and FAO as evidence for assessing market conditions and evaluating agricultural policies. Other users include food and farming industry, academia and the general public.

Overview

Type of data On-farm stocks

Unit of analysis Agricultural holdings

Scope

The survey questionnaire asks – for wheat, barley and oats – for the tonnages that the holding holds in storage on 28 February, including grain that has already been sold but is still stored on holding. It also asks how much grain purchased for on-farm use was stored by the holding.

Geographic coverage United Kingdom (England and Wales)

Primary investigator Department of Environment, Food and Rural Affairs, UK

Sampling

Sampling procedure

The holdings selected for the survey are stratified into four groups, based on the total area of wheat, barley and oats declared in the most recent June Survey of Agriculture and Horticulture. Then, the survey’s positive respondents are considered to constitute the sample of the Cereal Stocks Survey. For example, the February 2014 Cereal Stocks Survey was a postal survey sent to 1 750 agricultural holdings in England. The survey obtained a response rate of 76 per cent (1 332 usable responses). The June survey was sent to the 630 holdings that had indicated their willingness to take part in this investigation in their responses to the February survey. Finally, responses were received from 570 of these holdings – a response rate of 91 per cent.

Data collection

Data collection datesAn initial survey is sent to selected holdings in England in February every year. A follow-up survey is then sent to those respondents who have agreed to participate in the round held in June of the same year.

Data collection modality The Cereal Stocks Survey is a postal survey.


Data processing

Editing

The response data are subject to rigorous validation checks (e.g. to verify extreme values or large year-on-year changes) to identify any questionable values. Any records that have not been cleaned by the results production stage are excluded from the analysis.For each survey item, the production of totals for England and Wales requires estimation, to account for non-sampled and non-responding holdings. The results for the stocks of own-grown grain are produced with the technique known as “ratio-raising”. For each stratum, the trend between the June stocks tonnages in the sample (the response data) and the corresponding February stocks declared in the previous year’s February Cereal Stocks Survey (the base data) is calculated. Then, the ratio is multiplied by the value of stocks published for February for the entire population within each stratum. Finally, the resulting figures for each stratum are added to provide an estimate of own-grown stocks held on farms in June for the entire territory of England and Wales.Values for holdings that were not selected or that failed to respond are estimated, which adds a degree of uncertainty to the results. The results of this survey are based entirely on the responses given by holdings in England. The estimates for Welsh holdings use areas from the Welsh June Survey of Agriculture and Horticulture, but rely on the assumption that the relationship between cereal stocks and the cereal area is identical in England and in Wales.

Data Access

Publishing agency Department for Environment, Food and Rural Affairs, https://www.gov.uk/government/organisations/department-for-environment-food-rural-affairs

Release datesThe results of this survey and those of the Ports, Co-operatives and Merchants Survey are issued in a combined statistical release, to provide cereal stocks information for February/March and June.

Access URL https://www.gov.uk/government/statistics/cereal-stocks

Access terms and conditionsThe reports may be downloaded from the website created for the purpose, as well as the aggregated data. The conditions to access microdata are not specified.


Table 3.6ESTIMATION OF COMMERCIAL STOCKS IN THE UNITED KINGDOM

Identification

Country United Kingdom

Title Ports, Co-operatives and Merchants Survey

Study type Commercial Stocks Surveys

Series Information

This survey series was developed to replace the separate Agricultural Co-operatives and Ports Cereal Stocks Survey and the Importers and Dealers Cereals Stocks Survey. The new survey series is conducted to determine the stocks of cereals held at ports, co-operatives and merchants in the United Kingdom.

Overview

Type of data Commercial Stocks

Unit of analysis Ports, Co-operatives and Merchants

Scope

All facilities contacted are asked to record the grain stored on the survey date. For ports, grain that has been cleared by customs for import is included, as well as grain for export that has not been cleared by customs. Grain for import that has not cleared customs is not included, because this grain may be re-exported and thus unavailable for use in the UK.

Geographic coverage United Kingdom (England and Wales)

Primary investigator Department of Environment, Food and Rural Affairs, UK

Sampling

Sampling procedure

The survey consists in two voluntary postal surveys per year. In February or March, all known storage facilities (approximately 130 ports, co-operatives and merchants) are contacted. In June, a reduced sample of storage facilities (approximately 70) is contacted. The survey has a response rate of approximately 98 per cent.The survey adopts a stratified sampling design, using the storage capacity of the commercial entity as an auxiliary variable for stratification.

Data collection

Data collection dates The survey is performed twice a year in February or March and June, and records stocks of wheat, barley, oats and maize.

Data collection modality Voluntary postal survey

Data processing

Editing

The response data are checked in multiple ways, to identify potentially incorrect or outlying data (verifying e.g. extreme values or large year-on-year changes). The sample for the June part of the survey requires estimation, to account for any non-sampled and non-responding stores. The results for both stocks of homegrown and imported cereal are produced using the technique known as ratio-raising, in which the trend between the sample data and base (previous response) data is calculated for each stratum. The calculated ratio is then applied to base data for the non-responding stores data, to obtain UK-level estimates.


Data Access

Publishing agency Department for Environment, Food and Rural Affairs https://www.gov.uk/government/organisations/department-for-environment-food-rural-affairs

Release datesThe results of this survey and those of the Cereal Stocks Survey are issued in a combined statistical release, providing cereal stocks information in February/March and in June.

Access URL https://www.gov.uk/government/statistics/cereal-stocks

Access terms and conditions The reports are downloadable from the dedicated website along with the aggregated data. Microdata access conditions are not specified.


Table 3.7ESTIMATION OF COMMERCIAL STOCKS IN THE PHILIPPINES

Identification

Country The Philippines

Title Commercial Stocks Surveys (CSS)

Study type Off-Farm Stocks Survey

Series information

The CSS series is a monitoring system that was adopted by the NFA to generate estimates of the commercial rice stocks inventory held by the commercial sector at national, regional and provincial levels. In January 1980, the National Economic and Development Authority (NEDA) has recognized it as an official series of statistics in the Philippines.

The CSS’s main objectives are to:Determine the apparent grains stock inventory for rice held by the commercial sector, which would serve as inputs vital to government policy- and decision-making;Obtain, from NFA-registered grain businessmen, realistic and reliable statistics to be used an indicator for food security purposes in the country.

Overview

Type of data Commercial stocks

Unit of analysis NFA-registered businessmen

Scope

The survey asks to report:1) The volume of palay, rice, corn grits and corn grains stocks as of the

first day of the following month (ending stock inventory of the current month), measured in 50-kg bags;

2) The volume (in 50-kg bags) the source and the destination of the purchases and sales of palay, rice, corn grits and corn grains during the current month;

3) The purchased stocks (of rice, palay, corn grains and corn grits) in transit as of the first day of the following month.

Geographic coverage National

Primary investigator NFA

Sampling

Sampling procedure

The list frame adopted for the CSS is a list of approximately 93 400 NFA-registered businessmen operating nationwide. The adopted sampling design is a stratified systematic sampling process using two levels of stratification. The first level of stratification divides the sampling units into four categories: Retailers (R), Wholesalers (W), Combined Retailers and Wholesalers (R/W), and Warehousemen (Wh). The second level distinguishes, within sub-groups, among big, medium and small businessmen. Then, each group is assigned a particular inclusion probability:15 per cent of big, medium and small Retailers are selected;25 per cent of big, medium and small Wholesalers; 25 per cent of Combined Retailers/Wholesalers;100 per cent of big Warehousemen; and50 per cent of medium and small Warehousemen.

Data collection


The CSS is a monthly survey conducted on last two working days of the current month and the first two working days of the following month. The reference period for stocks reporting is the first day of the following month (ending stock inventory of the current month).

Data collection modalityData on commercial stocks are collected by directly interviewing the NFA-registered businesses. The interviews are conducted by the provincial enforcement and investigation officers.


Data processing

Editing

The data are collated and summarized by the provincial office every third and fourth working day of the month. Then, the final report is prepared by the NFA provincial office and transmitted to the NFA Central Office by the eighth day of the month. The consolidation and processing of the final results is performed over the next 10 days. Finally, the preparation, finalization and submission of the CSS final report to the NFA Administrator takes place between the 19th and the 21st day of the month.Stocks are first estimated by stratum (big, medium and small Retailers, Wholesalers, combined Wholesalers/Retailers and Warehousemen) and then aggregated, to produce an estimation of the total value of stocks.

Data Access

Access authority Philippine Statistics Authority

Contacts

Mario M. PadrinaoChief, Crops Statistics DivisionPhilippine Statistics AuthorityTel.: +6323762022Fax: +6323762022Email: [email protected][email protected]

Access conditions

The results of the survey are combined with the results of the Palay and Corn Stocks Survey to produce a monthly report that may be openly accessed on the BAS website, http://agstat.psa.gov.ph/?ids=downloads_view&id=881. The aggregated data may also be downloaded from the online database: http://countrystat.psa.gov.ph/?cont=10&pageid=1&ma=A40PNCNV.

Data Access

Publishing agency Philippine Statistics Authority, https://psa.gov.ph/

Release dates The reports are published on the BAS website after the 10th day of each month.

Access URLAggregated data: http://countrystat.psa.gov.ph/?cont=10&pageid=1&ma=A40PNCNV; microdata, reports and survey documentation. http://beans.psa.gov.ph/index.php/home.

Access terms and conditions Microdata may be downloaded by registering with the BAS Electronic Archiving and Network Services.


Table 3.8ESTIMATION OF ON-FARM STOCKS IN THE PHILIPPINES

Identification

Country The Philippines

Title Palay and Corn Stocks Survey (PCSS)

Study type On-farm stocks survey

Series information

The general purpose of the Palay and Corn Stocks Surveys is to gather information on the current level of stocks maintained by farming and non-farming households. The data to be generated from the survey seek to serve the following objectives:To generate estimates of current stocks of rice and corn in farming and non-farming households;To serve as inputs in the analysis of the seasonal trends and variations in the supply of rice and corn;To assist policymakers in the formulation, implementation and administration of agricultural economic programs; andTo guide farmers in decision-making relating to agricultural activities.

Overview

Type of data On-farm stocks of palay/rice and corn

Unit of analysis Producing and non-producing households

Scope

The scope of the PCSS includes:Geographic Classification (Province, Municipality, Barangay, Province), Household Classification (Farming and Non-Farming) and Household Characteristics;Quantity of Palay in the house as of the reporting month, as at 6:00 am in the local unit; Quantity of Rice in the house as of the reporting month, as at 6:00 am in the local unit;Quantity of shelled Corn in the house as of the reporting month, as at 6:00 am in the local unit; andQuantity of Corn Grits (Yellow/White) in the house as of the reporting month, as at 6:00 am in the local unit.

Geographic coverage National. The survey covers all provinces except Batanes, but includes Zamboanga City and Davao City.

Primary investigator Bureau of Agricultural Statistics (BAS)


Sampling

Sampling procedure

The survey’s domain is the province. The sampling procedure used in the PCSS uses of one replicate of the Palay and Corn Production Survey (PCPS). The sample is selected in two stages: at the barangay level and at the household level. The province's classification is taken into consideration in the classification of barangays sampled.For pure palay provinces, or for provinces whose major crop is palay, all 10 sample barangays from one replicate of the Palay Production Survey (PPS) are covered.For pure corn provinces, or for provinces whose major crop is corn, all 10 sample barangays from one replicate of the Corn Production Survey (CPS) are covered.For palay and corn (overlap) provinces, or provinces in which both palay and corn are the major crops, five barangays are drawn from the PPS sample barangays and another five from the CPS sample barangays.For minor provinces, or provinces whose major crop is neither palay nor corn, five sample barangays are drawn.

For each sample barangay, all PCPS sample households are enumerated. However, since the PCPS covered only farming households, five non-farming households from the same barangay were selected to complete the sample for the barangay. The sample of non-farming households was selected using the right coverage procedure, with a pre-defined starting point and random start.Right coverage is the procedure through which the data collector looks for qualified sample households along the existing path-structure in a given barangay. The procedure requires that at the established starting point, the data collector's standing position is such that his or her right shoulder points to the main entrance of the starting point. He or she then moves along this path, choosing households along the road or passage way. A range of alleys or eskinitas along, or main roads intersecting, on the right side shall be penetrated in a serpentine manner. Extensions and any other areas to be covered must be adjacent to the original spot and should be penetrated in the same manner.

Data collection


The PCSS is conducted on a monthly basis. The personal interviews are performed by staff from the Provincial Operation Center on the first day of each reference month. The information collected is the level of Palay and Corn household stocks as at 6:00 AM of the first day of the reference month (ending stocks of the previous month).


The field staff visits the sample villages and households at the beginning of each month, and collects the information through personal interviewing. In particular, the field staff asks the respondents for their stock stored in the household, in another household or in non-commercial granaries.

Data processing

Editing The answers to the queries are entered on a pre-formatted questionnaire. Then, the field staff edit, compile and summarize the completed forms.

Data Access

Publishing agency Philippine Statistics Authority, https://psa.gov.ph/

Release dates The reports are published on the BAS website after the 10th day of each month.

Access URLAggregated data: http://countrystat.psa.gov.ph/?cont=10&pageid=1&ma=A40PNCNV; microdata, reports and survey documentation: http://beans.psa.gov.ph/index.php/home.

Access terms and conditions Microdata may downloaded by registering with the BAS Electronic Archiving and Network Services.


Table 3.9ESTIMATION OF ON-FARM AND COMMERCIAL STOCKS IN BRAZIL

Identification

Country Brazil

Title Stock Surveys

Study type On-farm and commercial stocks survey

Series information

The stocks survey is designed to provide statistical data on the volume and spatial distribution of the stocks of basic storable agricultural products, and to track their trends in time. The survey covers establishments that have warehousing units (building or facilities constructed for the purpose of storing agricultural products) with a capacity of at least 2 000 m3 or 1 200 tonnes, and may be associated with any type of activity except supermarkets.

Overview

Kind of data On-farm and off-farm stocks

Unit of analysis Establishments (commercial, industrial, for services or for agricultural production) that possess at least one storage unit.

Scope

The survey content consists of data collected in each establishment on firm ownership, and on the establishment’s activity and conditions, storage mode, capacity, and existing stocks on the reference date. Stocks are surveyed for the following products: cotton (lint), cotton (in husk), cotton husk, cotton seed, rice (paddy), milled rice, rice seed, coffee (cherry), coffee (bans), black beans, red beans, maize (grain), maize seed, soybean (grain), soya seed, wheat (grain) and wheat seed.

Geographic coverageThe survey covers the entire national territory, with results being reported at the level of Brazil as a whole, as well as in terms of major regions, federative units, homogeneous micro-regions and municipalities.

Primary investigator Instituto Brasileiro de Geografia e Estatística (IBGE)

Sampling

Sampling procedure

The stocks survey covers establishments that possess at least one storage unit. These units are buildings or facilities constructed or adapted to store agricultural products and that meet the following criteria:Agricultural establishments – those with storage units having a total usable space of at least 2 000 m3 or 12 000 tonnes (t);Self-service commercial establishments (supermarkets) – annexed deposits are surveyed as well as central warehouses, with a useful capacity of at least 2 000 m3 or 1,200 t;Commercial establishments (other than supermarkets), industrial and warehousing services – establishments having storage units with a useful capacity of at least 400 m3 or 240 t.The selection of units is performed by means of a panel list based on the register used for the Warehousing and Dry Storage Survey that was held until 1984. The list is augmented with establishments identified in the economic census and agricultural census, as well as with records of other public and private agencies with links to the sector.


Data collection

Data collection datesThe Stocks Survey is a semiannual survey. For the first semester, the data collection is performed from January to March; for the second, from July to September.

Data collection modality Face-to-face interviews

Data Access

Publishing agency IBGE (http://ibge.gov.br/home/default.php)

Release dates At the beginning of each semester, a report is published for the previous semester.

Access URL http://ibge.gov.br/english/estatistica/indicadores/agropecuaria/estoque/default.shtm



Selected questionnaires of stocks surveys

Annex 4


Annex 4.1 Questionnaire of the USA’s Commercial Stocks Survey

Annex D Selected questionnaires of stocks surveys

Annex D.1 Questionnaire of the USA’s Commercial Stocks Survey


Annex 4.2 Questionnaire of Canada’s Commercial Stocks Survey Annex D.2 Questionnaire of Canada’s Commercial Stocks Survey


Annex 4.3 Questionnaire of the Philippines’ Palay and Corn Stocks Survey

An

nex

D.3

Qu

esti

on

nai

re o

f th

e P

hili

pp

ines

’ Pal

ay a

nd

Co

rn S

tock

s S

urv

ey


Annex 4.4 Questionnaire of the Philippines’ Commercial Stocks Survey Annex D.4 Questionnaire of the Philippines’ Commercial Stocks Survey


Annex 4.5 Stocks module of Burkina Faso’s Agricultural Survey

Annex 4.5 Stocks module of Mali’s Agricultural Survey

MODULE SP3: ESTIMATION DU STOCK PAR LES PAYSANS (des greniers)

Annex D.5 Stocks module of Mali’s Agricultural Survey

MODULE SP3: ESTIMATION DU STOCK PAR LES PAYSANS (des greniers)

N° du

grenier

Prénom et nom du responsable du grenier

Code cultures

Quelle est la situation stock actuel au niveau des [GRENIER] ?

Quelle a été la situation du stock un an auparavant au niveau des [GRENIERS] ?

Code

ULM

Nbre ULM

Eq.ULM

en kg

Quantité stock(123x1

24)

Code ULM

Nbre ULM

Eq en kg

Qté de stock (127x128)

115 116 121 122 123 124 125 126 127 128 129

I__I I__I

I__I I__I

I__I I__I

I__I I__I

Annex D.5 Stocks module of Burkina Faso’s Agricultural Survey


Annex 4.6Stocks module of Niger’s Agricultural Survey

An

nex

D.6

Sto

cks

mo

du

le o

f N

iger

’s A

gri

cult

ura

l Su

rvey

RE

PU

BLI

QU

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R

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ultu

re

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irect

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tistiq

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Agr

icol

es

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PE

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sion

et E

stim

atio

n de

s R

écol

tes

Cam

pagn

e Ag

ricole

:

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|___

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___|

____

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e 5

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cks P

aysa

ns

No

m d

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nquê

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____

____

____

____

____

____

___

Da

te d

u pa

ssag

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____

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____

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____

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(

jour)

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r :

_

____

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tion

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parte

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t

|___

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3 Ce

ntre

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|___

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Annex 4.7Brazil’s Stocks Survey

Annex D.7 Brazil’s Stocks Survey

A Surveys Directorate – Agriculture Coordination Unit

STOCKS SURVEY OBLIGATORY STATUS AND CONFIDENTIALITY OF INFORMATION. Current legislation, pursuant to Federal Decree 73.177 of 20 November 1968 as amended by Law 5.878 of 11 May 1978, provides for the obligatory status and

confidentiality of the data collected by the IBGE, which are intended exclusively for statistical purposes, may not be used for certification purposes and shall not have a legal effect as evidence. Attention: In the case of doubt when completing the questionnaire, please consult the instructions manual

Year SEMESTER UF Agency Municipality

Establishment Firm

UF: UF:

Municipality: Municipality:

Establishment code: Firm code:

Name: Name:

CNPJ:

Address: Address:

CEP: TEL: FAX: CEP:

Email: DDD: TEL: FAX:

Respondent: Respondent phone: Email:

Activity:

Situation: Ownership:

Reasons for extinction:

Conventional warehouse: Bulk grain warehouse: Silo:

Cadastral data (complete only in the case of cadastral change or new establishments)

Identification of the Establishment

Location of the establishment: UF Municipality

Name

Address

Type Yard

Complement CEP DDD Telephone Fax

CNPJ Collection agency code E-mail

Respondent Respondent phone

Preferred collection mode

In person

Telephone

Online questionnaire

Email

Identification of the Firm

Location of the establishment: UF: Municipali

ty:

Name:

Address:

Type: Yard:

Complement: CEP: DDD: Telephone: Fax:

E-mail:


Ownership of the Firm

Government (federal, state, or municipal): Private enterprise: Cooperative: Mixed ownership:

Activity of the Establishment

Commerce (excluding supermarket): Industry: Service (including general store): Agricultural producer:

Situation of the establishment

What was the establishment’s status on ___/___/_____ ? Active: Inactive (still complete the storage modality): Defunct:

If defunct, indicate the reason:

Change in the use of the facilities:

Other:

Premises demolished:

(Report new use in comments)

(Justify in comments)

Storage Modality

Storage unit Useful capacity (m3) Storage unit Useful capacity (t) Storage unit Useful capacity (t)

Conventional, structural or inflatable warehouse Grain warehouse

Silo

or

(for grains)

Bulk

warehouse

STOCKS EXISTING IN THE STORAGE UNITS, ON ___/___/______:

Products Quantity (kg) Products Quantity (kg)

COTTON (lint)

BLACK BEAN (in grain)

COTTON (in husk)

RED BEAN (in grain)

COTTON HUSK

MAIZE (in grain)

COTTON SEED

MAIZE SEED

RICE (in husk)

SOYA (in grain)

MILLED RICE

SOYA SEED

RICE SEED

WHEAT (in grain)

WHEAT SEED

ARABICA COFFEE (in grain)

ROBUSTA COFFEE (in grain)

OTHER GRAINS AND SEEDS

OTHER QUESTIONS ON STORAGE:

WERE ANY OF THE PRODUCTS LISTED ABOVE BEING STORED IN BAG SILOS IN THE ESTABLISHMENT AREA ON ____/____/______? Yes No

WHAT WAS THE TOTAL USEFUL CAPACITY (t) OF THE BAG SILOS USED IN THE ESTABLISHMENT WITH THE PRODUCTS LISTED ABOVE ON ____/____/______ ?

IF NONE OF THE PRODUCTS LISTED ABOVE WAS BEING STORED ON ____/____/______, WERE ANY OF THEM IN STORE AT ANOTHER TIME DURING THE SEMESTER? Yes No

WERE THERE ANY PRODUCTS BEING STOCKED OUTSIDE THE WAREHOUSING UNITS (IMPROVISED STORAGE) IN THE ESTABLISHMENT AREA AT ANY TIME IN THE SEMESTER? Yes No

WHAT PERCENTAGE OF USEFUL CAPACITY WAS ACTUALLY BEING USED IN THE ESTABLISHMENT ON ____/____/______ ? INDICATE ONE OF THE RANGES SHOWN BELOW

0% to 25% Over 25% to 50% Over 50% to 75% Over 75% to 100%

COMMENTS:


AUTHENTICATION RESPONDENT

PERSON RESPONSIBLE FOR DATA COLLECTION

Name (in capitals) Name (in capitals)

Name of the collection agency

/ / / /

Date of the information Signature

Date of the information Signature SIAPE


Annex 4.8 Stocks module of Togo’s Agricultural Survey

An

nex

D.8

Sto

cks

mo

du

le o

f T

og

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ricu

ltu

ral S

urv

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la p

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(4)

(5)

(6)

(7)

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__|_

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__|_

_|__

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__|


In

form

atio

ns r

elat

ives

à la

pro

duct

ion

céré

aliè

re d

es a

utre

s pr

oduc

teur

s du

mén

age

Prod

ucte

ur N

° ../.

. N

om e

t pré

nom

……

……

……

……

……

……

……

……

N° d

u gr

enie

r ou

du

mag

asin

C

éréa

le

Nom

de

l’uni

té

loca

le d

e m

esur

e (U

LM)

Qua

ntité

s to

tale

s ré

colté

es

Qua

ntité

s ré

elle

s en

sto

ck

Nom

bre

d’U

LM

Equi

vale

nt e

n ki

logr

amm

e gr

ain

Nom

bre

d’U

LM

Equi

vale

nt e

n ki

logr

amm

e gr

ain

(1)

(2)

(3)

(4)

(5)

(6)

(7)

|__|

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_|__

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NB :

- Pou

r la

colo

nne

2, m

ettre

le c

ode

corr

espo

ndan

t à la

cér

éale

cité

e pa

r le

prod

ucte

ur M

aïs

1 ;

mil

: 2 ;

sor

gho

: 3 ;

riz

: 4


Annex 4.9 Togo’s Commercial stocks survey

An

nex

D.9

To

go

’s C

om

mer

cial

sto

cks

surv

ey

EVA

LUA

TIO

N D

ES S

TOC

KS

CER

EALI

ERS

(MA

ÏS, R

IZ, S

OR

GH

O E

T M

IL) D

ISPO

NIB

LES

AU

PRES

DES

MEM

BR

ES D

ES

GR

OU

PEM

ENTS

DE

PRO

DU

CTE

UR

S

(CA

MPA

GN

E 20

09 /

2010

et 2

010

/ 201

1)

N°

d’or

dre

NO

M E

T PR

ENO

MS

DES

MEM

BR

ES

DU

GR

OU

PEM

ENT

PR

OD

UIT

S en

sac

s de

100

kg

M

AÏS

R

IZ

SOR

GH

O

MIL

Stoc

k to

tal

du m

embr

e du

gr

oupe

men

t

*Qua

ntité

re

stan

te

du s

tock

Stoc

k

2010

-20

11

Stoc

k to

tal d

u m

embr

e du

gr

oupe

men

t

*Qua

ntité

re

stan

te

du s

tock

Stoc

k

2010

-20

11

Stoc

k to

tal d

u m

embr

e du

gr

oupe

men

t

*Qua

ntité

re

stan

te

du s

tock

Stoc

k

2010

-20

11

Stoc

k to

tal d

u m

embr

e du

gr

oupe

men

t

*Qua

ntité

re

stan

te

du s

tock

Stoc

k

2010

-20

11

2009

-20

10

20

09-

2010

2009

-20

10

20

09-

2010

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

(1

1)

(12)

(1

3)

(14)

Tot

al A

*Il s

’agi

t du

rest

e du

sto

ck d

e la

cam

pagn

e ag

ricol

e 20

09-2

010.

Il fa

ut l’

insc

rire

si c

ela

exis

te e

ncor

e.


Info

rmat

ions

rela

tives

à la

pro

duct

ion

céré

aliè

re d

es g

ros

prod

ucte

urs

agric

oles

N

om e

t pré

nom

……

……

……

……

……

……

……

……

N° d

u gr

enie

r ou

du

mag

asin

Cér

éale

N

om d

e l’u

nité

loca

le d

e m

esur

e (U

LM)

Qua

ntité

s to

tale

s ré

colté

es

Qua

ntité

s ré

elle

s en

sto

ck

Nom

bre

d’U

LM

Equi

vale

nt e

n ki

logr

amm

e gr

ain

Nom

bre

d’U

LM

Equi

vale

nt e

n ki

logr

amm

e gr

ain

(1)

(2)

(3)

(4)

(5)

(6)

(7)

|__|

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EVA

LUA

TIO

N

DES

ST

OC

KS

CER

EALI

ERS

(MA

ÏS,

SOR

GH

O,

MIL

ET

R

IZ

LOC

AL)

D

ISPO

NIB

LES

AU

PRES

D

ES

CO

MM

ERC

AN

TS D

AN

S LE

S M

AR

CH

ES D

E R

EFER

ENC

E

N0 o

rdre

NO

M E

T PR

ENO

MS

DES

CO

MM

ERC

AN

TS

PRO

DU

ITS

(EN

SA

CS

DE

100

KG

)

MA

ÏS

SORG

HO

MIL

RIZ

LO

CA

L

(1)

(2)

(3

(4)

(5)

(6)

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__|_

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__|_

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__|_

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__|_

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__|_

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__|_

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__|_

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__|_

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__|_

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__|_

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__|_

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__|_

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__|_

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__|_

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Tota

l |_

_|__

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_|

|__|

__|_

_|__

|__|

|__|

__|_

_|__

|__|

|__|

__|_

_|__

|__|


Annex 4.10 Stocks module of Senegal’s Agricultural Survey

80

Annex D.10 Stocks module of Senegal’s Agricultural Survey

REPUBLIQUE DU SENEGAL MINISTERE DE L' AGRICULTURE

____________________

Direction de l'Analyse, de la Prévision et des Statistiques Division des Statistiques, de la Documentation et de l'Information Agricole

Système Permanent de Statistiques Agricoles

Campagne Agricole 2008/09

QUESTIONNAIRE 13 : Stocks paysans de céréales Nom de l'enquêteur : ____________________________________________________________________ Date du passage : |____|____| |____|____| |____|____|

Nom et visa du chef de bureau : ____________________________________________________________ Date du contrôle : |____|____| |____|____| |____|____|

Nom et visa du chef de Service départemental : _________________________________________________

Section 1 : Eléments d'identification

N° Elément d'identification Nom Code

1 Région |___|___|

2 Département |___|

3 Strate |___|

4 Arrondissement |___|

5 Communauté rurale |___|

6 District de recensement |___|___|___|

7 Village/Hameau |___|___|___|

8 Numéro de l'exploitation |___|___|

9 Chef d'exploitation


Annex 4.11 Stocks module of India’s Cost of Cultivation Survey

81

An

nex

D.1

1 S

tock

s m

od

ule

of

Ind

ia’s

Co

st o

f C

ult

ivat

ion

Su

rvey

Sect

ion

2 : E

valu

atio

n de

s st

ocks

pay

sans

de

céré

ales

1. L

'exp

loita

tion

est-e

lle c

once

rnée

par

les

stoc

ks d

e cé

réal

es d

e la

list

e ci

-des

sous

?

Insc

rire

le co

de d

e la

répo

nse

obse

rvée

dan

s la

case

de

droit

e

1

Oui

2

N

on

I___

I

2.

Si l

a ré

pons

e po

ur le

type

de

céré

ale

conc

erné

est

Oui

, ins

crire

le p

oids

ou

le n

ombr

e de

bot

tes

au c

ours

de

la c

ampa

gne

agric

ole

2007

/08

Type

Ca

tégo

rie

Mod

e de

stoc

kage

de cé

réale

de

dét

ente

ur

Stoc

kage

en

sac

Stoc

kage

dan

s un

gren

ier

Autre

mod

e de

stoc

kage

de

stoc

k de

céré

ales

Poids

tota

l No

mbr

e Po

ids to

tal

Poids

tota

l

Nom

Co

de

Code

No

m

(kg)

de

bot

tes

(kg)

(k

g)

1 2

3 4

5 6

7 8

Mil

1 1

Ense

mble

du

mén

age

|___

_|__

__|_

___|

____

| |_

___|

____

|___

_| |

____

|___

_|__

__|_

___|

|__

__|_

___|

____

|___

_|

1

2 En

sem

ble d

es fe

mm

es

|___

_|__

__|_

___|

____

| |_

___|

____

|___

_| |

____

|___

_|__

__|_

___|

|__

__|_

___|

____

|___

_|

Sorg

ho

2 1

Ense

mble

du

mén

age

|___

_|__

__|_

___|

____

| |_

___|

____

|___

_| |

____

|___

_|__

__|_

___|

|__

__|_

___|

____

|___

_|

2

2 En

sem

ble d

es fe

mm

es

|___

_|__

__|_

___|

____

| |_

___|

____

|___

_| |

____

|___

_|__

__|_

___|

|__

__|_

___|

____

|___

_|

Maï

s 3

1 En

sem

ble d

u m

énag

e |_

___|

____

|___

_|__

__|

|_

___|

____

|___

_|__

__|

|___

_|__

__|_

___|

____

|

3

2 En

sem

ble d

es fe

mm

es

|___

_|__

__|_

___|

____

|

|___

_|__

__|_

___|

____

| |_

___|

____

|___

_|__

__|

Riz

4 1

Ense

mble

du

mén

age

|___

_|__

__|_

___|

____

| |_

___|

____

|___

_| |

____

|___

_|__

__|_

___|

|__

__|_

___|

____

|___

_|

4

2 En

sem

ble d

es fe

mm

es

|___

_|__

__|_

___|

____

| |_

___|

____

|___

_| |

____

|___

_|__

__|_

___|

|__

__|_

___|

____

|___

_|

Fonio

5

1 En

sem

ble d

u m

énag

e |_

___|

____

|___

_|__

__|

|___

_|__

__|_

___|

|__

__|_

___|

____

|___

_| |

____

|___

_|__

__|_

___|

5

2 En

sem

ble d

es fe

mm

es

|___

_|__

__|_

___|

____

| |_

___|

____

|___

_| |

____

|___

_|__

__|_

___|

|__

__|_

___|

____

|___

_|


Annex 4.12 Indonesia’s Stocks survey

83

A

nn

ex

D.1

2 I

nd

on

esi

a’s

Sto

cks

surv

ey

Up

dat

ing

Per

iod

: A

pri

l

301.

101.

Province

302.

102.

District/Municipality*)

303.

103.

Sub-district

304.

104.

Village/K

elur

ahan

*)305.

105.

Village/k

elur

ahan

Classification

306.

106.

CensusBlockNumber

307.

107.

SampleCodeNumber

308.

108.

SLSNumberandNam

e309.

201.

OfficerCode

202.

OfficerNam

e

203.

Updating/ExaminationDate

204.

Signature

*)cro

ssout

which

ever

doe

sno

tap

ply

(1)

BLOCKIV.NOTES

NATIONALSU

RVEYONRICERESERVES2015

HOUSEHOLDUPDATE

BLOCKII.INFORMATIONONOFFICER

Description

1.Urban2.Rural

Description

Nam

e

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stpagedetailccolumn(8)]

Numberofcom

monfarm

inghouseholds

[Cop

iedfr

omB

lock

Vla

stpagedetailccolumn(9)]

NumberofriceRTUTwiththeharvestedareaduringMay2014-April2015

<0,50ha

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84

EnumerationPeriod: April

1. Province :

2. District/Municipality :

3. Sub-district :

4. Village/Kelurahan :

5. Census Block Number

6. Sample Code Number

9. Enumerator's Name for Household Update :

* Enumeration Information Code1, Successfully interviewed 3, Unable to be interviewed to the census deadline2, Move outside census block 4, Refused to be interviewed ( …………………………………………………..)

VKCB15-RPP.DS1

1

4321

Enumeration Information*

Address

Copied from list (VKCB15-RT.P)

II. SAMPLE LIST

CENTRAL STATISTIC AGENCY and MINISTRY OF AGRICULTURE

(1) (10)(9)(8)(7)(6)(5)(4)(3)(2)

Name of the Head of Household Physical

BuildingCensus Building Household

Consecutive NumberNo.

BLOCK I. PLACE ORIENTATION

RICE PRODUCER-HOUSEHOLD SAMPLE LISTNATIONAL SURVEY ON RICE RESERVES 2015


85


1. Province :

2. District/Municipality*) :

3. Sub-district :

4. Village/Kelurahan *) :



7. Household Consecutive Number

8. Sample Consecutive Number

9. Name of the Head of Household :

10. Phone Number/ Cell phone :

1. Officer's code KSK -1 BPS Staff -2 Partner -3

2. Officer's Name

3. Date

4. Signature

1. Ownership and utilization of rice field during census (m2)

a.Rice field owned :

b. Rice field originating from other party :

c.Rice field located in other party :

d.Controlled rice field (a+b-c) :

2. Information harvest in the past year:

a. January - April 2015 i.

ii.

b.September - December 2014 i.

ii.

c. May - August 2014 i.

ii.

RICE PRODUCER HOUSEHOLD1


II. OFFICER INFORMATIONDescription Enumerator

VKCB15-RPP.S1

CENTRAL STATISTIC AGENCY and MINISTRY OF AGRICULTURENATIONAL SURVEY ON RICE RESERVES 2015

Supervisor/Auditor

…………………………………… ……………………………………

/ / / /

III. INFORMATION ON FARMING ACTIVITY WITHIN HOUSEHOLD

Harvested dry rice grains product (kg)

(4)

Self-harvest

Purchased/shared

Self-harvest

Purchased/Shared

Self-harvest

Harvest area (m2)

(3)

Period

(1)

Harvest methodology

(2)

Purchased/shared


86

1 Do you own rice barn/silo to store unmilled rice/rice?yes -1 no -2 (straight to detail 3)

2. Barn/silo capacity ……….. quintal (straight to detail 4)

3. If you don't own barn/silo, the unmilled rice/rice are usually stored in :the house -1 Communal barn/silo -2 Others (......................) -3

4.unmilled rice and rice condition 1-31 March 2015 (in accordance with production form)

a. How much unmilled rice/rice ow ned in 1 March 2015?

b. How much unmilled rice/rice ow ned in 31 March 2015?

c.Did you conduct the harvesting?

- 1 No -2

i. Date of harvest:

ii. How much harvested unmilled rice is produced ?

iii. l How much unmilled rice is shared?

d.Did you purchase:i. unmilled rice:Yes- 1 No -2

ii. Rice: Yes- 1 No -2

e.

i. unmilled rice:Yes- 1 No -2


f. Did you sell unmilled rice/rice?i. unmilled rice:Yes- 1 No -2

ii. Rice: yes - 1 No -2

g.How much rice is consumed?

h.

i. unmilled rice:Yes- 1 No -2


5.a. How much rice/glutinous rice flour is owned in 1 March 2015? , Kg

b. How much rice/glutinous rice flour is purchased in March 2015? , Kg

c. i. Did you give rice/glutinous rice flour to other party during March 2015?yes -1 no -2 (straight to detail 5.d)

ii. How much rice/glutinous rice flour did you give to other party in March 2015? , Kg

d. How much rice/glutinous rice flour is consumed in March 2015? , Kg

e. How much rice/glutinous rice flour is owned in 31 March 2015? , Kg

Do you give unmilled rice/rice to other party?

Did you receive unmilled rice/rice from other party?

V. NOTE

(4)

Harvested dry rice grains (kg)

Ground dry rice grains (kg) Rice (kg)Description

Yes

(1) (2) (3)

IV. INFORMATION ON unmilled rice (rice in the husk) / RICE STORAGE


87


1. Province :


3. Sub-district :




1. Number of consumer household sample

2. Number of interviewed sample

3. Number of sample moved outside census block

4. Number of sample unable to be interviewed to the end of enumeration timeline

5. Number of samples refused to be interviewed

1. Officer's code

2. Officer's Name

3. Date of Enumeration/Examination

4. Signature

CENTRAL STATISTICS AGENCY and MINISTRY OF AGRICULTURE


CONSUMER HOUSEHOLD SAMPLE LISTNATIONAL SURVEY ON RICE RESERVES 2015

BLOCK II. ENUMERATION RECAPITULATION

VKCB15-RTK.DS2

1

BLOCK III. OFFICER INFORMATIONDescription Enumerator Supervisor/Auditor

......... / ............ ......... / ............ to ......... / ............to ......... / ............


88

*) Code for Block V Column (7) Enumeration Note:1. Successfully interviewed Unable to be interviewed to the end of enumeration timeline2. Move outside census block Refused to be interviewed

(5)

Name of The Head of Household

(7)

Enumeration note*)Address

BLOCK IV. SAMPLE LIST

Sample Consecutive Number

(1)

Physical Buidling

Census Building

Household

Consecutive No.

(2) (3) (4)

Copied from (VKCB15-RT.P)

(6)

3.4.


Reg

istr

atio

n Pe

riod

: Apr

il

301.

101.Province

302.

102.District/Municipality*)

303.

103.Sub-district

304.

104.Village/K

elurahan*)

305.

105.CensusBlockNumber

306.

106.SampleCodeNumber

307.

308.

201.Officer'sCode

202.Officer'sName

203.DateofRegistration/Examination

204.Signature

BLOCKIV.NOTE

*)Crossoutwhicheverdoesn

otapply

Numberofenterprise/householdsellingunmilledrice,rice,orriceflour

[CopiedfromlastpageofBlockVdetailccolumn(8)]

unmilledrice,rice,orriceflourretailerwithturnoverof<2,5billionrupiahperyear


unmilledrice,rice,orriceflourretailerwithturnoverof≥2,5billionrupiahperyear


unmilledriceorricecollectormerchantwithturnoverof<2,5billionrupiahperyear


unmilledrice,rice,orriceflourwholesalerwithturnoverof≥2,5billionrupiahperyear


unmilledrice,rice,orriceflourwholesalerwithturnoverof<2,5billionrupiahperyear


unmilledriceorricecollectormerchantwithturnoverof≥2,5billionrupiahperyear


BLOCKII.OFFICERINFORMATION

Supervisor/Auditor

Enumerator

Description

BLOCKI.PLACEINFORMATION

BLOCKIII.RECAPITULATION

Description

Name

Code

Numberofenterprise/household

[Copiedfrom

BlockVlastpag

ecolumn(5)]

1

CONFIDENTIAL

NATIONALSURVEYONRICERESERVES2015

BUILDING,BUSINESS,ANDHOUSEHOLDREGISTRATION

CENTRALSTATISTICAGENCYandMINISTRYOFAGRICULTURE

VKCB15-UP.L 3


90

EnumerationPeriod: April Page……of……pages

1. Province :


3. Sub-district :




9. Census Officer's Name :

* Enumeration Note1, Successfully interviewed 3, Unable to be interviewed to the end of enumeration timeline2, Move outside census block 4, Refused to be interviewed ( …………………………………………………..)

(10)(1) (2) (3) (4) (5) (6) (7) (8) (9)

II. SAMPLE LIST

No.

Copied from list (VKCB15-UP.L) Enumeration Information*Consecutive Number

Name of Enterprise/Head of Household AddressPhysicial

BuildingCensus Building Household 1 2 3 4

3

CENTRAL STATISTIC AGENCY and MINISTRY OF AGRICULTURE

NATIONAL SURVEY ON RICE RESERVES 2015

1TRADING BUSINESS SAMPLE LIST



91

Enumeration Period: April 1* Objective

* Objek Survei

* Legal BasisThe activity is executed based on the Law Number 16 of the year 1997 on Statistic.

* Confidentiality

1. PROVINCE

2. DISTRICT/MUNICIPALITY *)

3. SUB-DISTRICT

4. KELURAHAN /VILLAGE *)

5. CENSUS BLOCK NUMBER (CBN)

6. SAMPLE CODE NUMBER (SCN)

7. COMPANY/BUSINESS CONSECUTIVE NUMBER

8. Company/business full name : . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

9. Name of Person responsible for the company/enterprise: . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

10. Company/business full address : . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Phone number : ( . . . . . . . . . ) . . . . . . . . . . . . . . . . . . . . . . . .area code

Fax number : ( . . . . . . . . . ) . . . . . . . . . . . . . . . . . . . . . . . .area code

1. Officer's code: KSK -1 BPS Staff -2 Partner -3

2. Name

3. Date

4. Signature*) Cross out whichever does not apply

TRADING BUSINESS

To obtain estimation data on food reserve, specifically rice

Company/Enterprise that sells gabah or rice

NATIONAL SURVEY ON RICE RESERVES 2015CENTRAL STATISTIC AGENCY and MINISTRY OF AGRICULTURE

Confidentiality of the provided data is guaranteed by the Law Number 16 of the year 1997 Article 21, on Statistic

zip code

phone number

(2)

fax number

BLOCK I : PLACE ORIENTATION(1) (3)

(2) (3)

BLOCK II : OFFICER INFORMATION

DESCRIPTION ENUMERATOR SUPERVISOR/AUDITOR(1)


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94

EnumerationPeriod: July Page……of……pages

1. Province :


3. Sub-district :




1. Number of Small Micro Industry (Industri Mikro Kecil/ IMK) sample

2. Number of Food and Beverages Provider (PMM) Sample

3. Number of Successfully interviewed samples

4. Number of sample move outside census block

5. Number of samples unable to be interviewed to the end of enumeration timeline

6. Number of sample refused to be interviewed

1. Officer's Code

2. Officer's Name

3. Enumeration/Examination Date

4. Signature

*) Code for Block IV column (10) Enumeration Note:1. Succesfully Interviewed Unable to be interviewed to the end of enumeration timeline (closed, not found, etc.)2. Move outside census block Refused to be interviewed

2



IMK, HOTEL AND F&B PROVIDER SAMPLE LISTNATIONAL SURVEY ON RICE RESERVES 2015

BLOCK II. ENUMERATION RECAPITULATION

(10)

Enumeration Note*)

Copied from VKCB15-IMKPMM.P List

Nama of the Business/ Head of the Household

Name of the Businessman/

Business owner/ART who runs a

busines

Address

Consecutive Number

Segment

Phy sical

Building

Census Building

Business/enterp

rise

BLOCK IV. SAMPLE LIST

BLOCK III. OFFICER INFORMATIONSupervisor/AuditorEnumeratorDescription

......... / ............ to ......... / ............ ......... / ............ to ......... / ............

Consecutive

No.for IMK

Sample

Consecutive

Number for PMM Sample

(3) (4) (5) (6) (7) (8) (9)(1) (2)

3.4.


95

EnumerationPeriod: July Page……of……pages

1. Province :


3. Sub-district :




*) Code for Block IV column (10) Enumeration Note:1. Succesfully Interviewed Unable to be interviewed to the end of enumeration timeline (closed, not found, etc.)2. Move outside census block Refused to be interviewed


NATIONAL SURVEY ON RICE RESERVES 2015 IMK, HOTEL AND F&B PROVIDER SAMPLE LIST

2

BLOCK I. PLACE ORIENTATION (Copied from page 1 )

BLOCK IV. SAMPLE LIST (Continued)

Consecutive

Number for IMKk Sample

Consecutive

Number for PMM Sample

Copied from VKCB15-IMKPMM.P List

Enumeration Note*)

Consecutive No,Name of Business/head of

Household

Name of business owner/household

member who runs a business

AddressSegment

Phy sical

Building

Census Building

Business/House

hold(10)(1) (2) (3) (4) (5) (6) (7) (8) (9)

3.4.


96

Enumeration Period: April 1* Objective

* Survey Object

* Legal BasisThe activity is executed based on the Law Number 16 of the year 1997 on Statistic.

* Confidentiality

1. PROVINCE

2. DISTRICT/MUNICIPALITY *)

3. SUB-DISTRICT

4. KELURAHAN /VILLAGE *)

5. CENSUS BLOCK NUMBER (CBN)

6. SAMPLE CODE NUMBER (SCN)

7. COMPANY/BUSINESS CONSECUTIVE NUMBER

8. Company/business full name : . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

9. Name of Person responsible for the company/business: . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .


. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .



1. Officer's code: KSK -1 BPS Staff -2 Partner -3

2. Name

3. Date

4. Signature*) Cross out whichever does not apply

(2)

(2) (3)

BLOCK II : OFFICER INFORMATION

DESCRIPTION ENUMERATOR SUPERVISOR/AUDITOR(1)

fax number

BLOCK I : PLACE ORIENTATION(1) (3)

phone number

RICE MILL INDUSTRY

zip code


To obtain estimation data on food reserve, specifically rice

Rice mill industry

Confidentiality of the provided data is guaranteed by the Law Number 16 of the year 1997 Article 21, on Statistic


97

1. Legal form/business entity form/authorization form:PT (Limited Liability Company) - 1 CV - 2 Cooperative - 3 Personal - 4 Others (........…………….) - 5

2. Year it started producing commercially: ……………………………………..

3.

Yes - 1 No - 2

4.

Permanent - 1 Travelling - 2

5. a. The scale of rice mill company/business:

-1-2-3

b. Average realisation of production capacity in Marh 2015: ................................ kg/hour

6. Origin area of milled rice in March 2015:

a.

b.

c.

d.

1 0 0

7. The amount of ground dry rice grains (GKG) in March 2015 : .......................... quintal

8. The amount of rice produced in March 2015: ................................ quintal

1. unmilled rice and rice stock in March 2015:

a. unmilled rice

b.Rice

c. Rice with inner bran layer [PK]

d. Broken rice grains (Menir)

a. unmilled rice

b.Rice

c. Rice with inner bran layer [PK]

d. Broken rice grains (Menir)

(5)

Per 31 March 2015Stock (quintal) Price (per quintal)

Per 1 March 2015Stock (quintal) Price (per quintal)

(3)

BLOCK V : NOTE

BLOCK IV : UNMILLED RICE/RICE STOCK INFORMATION

a. Within one district/cityb. Different district/city, in one province

d.Overseas

c. Different province

: ........... %

: ........... %

: ........... %

: ........... %

Type of Stock/Supply

Type of Stock/Supply

(1) (4)

Is it harvesting time when the census is conducted?

The location of rice mill company/business is:

BLOCK III : COMPANY/BUSINESS INFORMATION

(1)

Large scale (> 3 ton rice/hour)Medium Scale (1,5 - 3 ton rice/hour) Small Scale (< 1,5 ton rice/hour)

(2)


98

Enumeration Period: April 1

1. :

2. Company's full name : . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .


. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .



4. Contact Person

a. Full name : . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . .. . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

b.Position : . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . .. . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

c. Phone Number/Cell phone: . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . .. . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

d. E-mail : . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . .. . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

January

February

March

January

February

March

2. Name/NIP (Officer's ID Number)

3. Date

4. Signature

Province :

phone number

fax number

(1)ENUMERATOR

(2)SUPERVISOR/AUDITOR

(3)DESCRIPTION

BLOCK III : OFFICER INFORMATION

(1) (2) (3) (4) (5)

Month Early Stock Procurement/Purchase Channeled Last Stock

BLOCK II : UNMILLED RICE AND RICE INFORMATION

Information on unmilled rice owned by Divre BULOG ......................................... Year 2015 (ton)

BLOCK I : PLACE ORIENTATION

zip code

Information on Rice owned by Divre BULOG......................................... Year 2015 (ton)

Month

(1)

ChanneledProcurement/PurchaseEarly Stock Last Stock

(2) (3) (4) (5)

DIVRE BULOG (Regional Division for National Logistics Agency)



Notes

The capacity-building component of the Agricultural Market Information System (AMIS) project, funded by the Bill & Melinda Gates Foundation, provides for the development of guidelines and methodologies to improve crop production forecast estimates, data on market prices and stocks statistics.

Reliable data on stocks will help decision makers to understand food availability, plan the necessary interventions on market stabilization, and address issues related to food insecurity.

This document is intended for statisticians and managers of national statistics offices who wish to develop or improve survey programmes for the direct measurement of grain and other food stocks.

It provides guidance and tools for direct measurement of food stocks, discusses current and best practices for stock estimation through sample surveys, reflects on conceptual, technical, human and budgetary issues related to stock surveys, and provides examples and tools for countries wishing to develop their stock survey programmes.

These Guidelines have been prepared on the basis of assessments of the methods currently used by countries to produce data on stocks, and seek to help countries design and implement both on-farm and off-farm stocks.

CONTACT

AMIS projectStatistics Division (ESS)Food and Agriculture Organization of the United Nations (FAO) Viale delle Terme di Caracalla, 00153 Rome, Italy

guidelines for designing and implementing grain stock surveys

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