the use of non-standard units for the collection of...

LSMS GUIDEBOOKJuly 2017

The Use of Non-Standard Units for the Collection of

Food QuantityA Guidebook for Improving the Measurement

of Food Consumption and Agricultural Production in Living Standards Surveys

Gbemisola Oseni, Josefine Durazo, and Kevin McGee

The Use of Non-Standard Units for the Collection of Food QuantityA Guidebook for Improving the Measurement of Food Consumption

and Agricultural Production in Living Standards Surveys

Gbemisola Oseni, Josefine Durazo, and Kevin McGee World Bank

ABOUT LSMSThe Living Standards Measurement Study (LSMS), a survey program housed within the World Bank’s Development Data Group, provides technical assistance to national statistical offices in the design and implementation of multi-topic household surveys. Since its inception in the early 1980s, the LSMS program has worked with dozens of statistical offices around the world, generating high-quality data, developing innovative technologies and improved survey methodologies, and building technical capacity. The LSMS team also provides technical support across the World Bank in the design and implementation of household surveys and in the measurement and monitoring of poverty.

ABOUT THIS SERIESThe LSMS Guidebook series offers information on best practices related to survey design and implementation. While the Guidebooks differ in scope, length, and style, they share a common objective: to provide statistical agencies, researchers, and practitioners with rigorous yet practical guidance on a range of issues related to designing and fielding high-quality household surveys. The Series aims to achieve this goal by drawing on the experience accumulated from decades of LSMS survey implementation, the expertise of LSMS staff and other surveys experts, and new research using LSMS data and meth-odological validation studies.

Copyright © 2017 The World Bank.

Rights and PermissionsThis work is available under the Creative Commons Attribution 3.0 IGO license (CC BY 3.0 IGO) http://creativecommons.org/licenses/by/3.0/igo. Under the Creative Commons Attribution license, you are free to copy, distribute, transmit, and adapt this work, including for commercial purposes, under the following condition:Attribution—Please cite the work as follows: Oseni, G., Durazo, J., & McGee, K. 2017. The Use of Non-Standard Units for the Collection of Food Quantity: A Guidebook for Improving the Measurement of Food Consumption and Agricultural Production in Living Standards Surveys. Washington DC: World Bank. DisclaimerThe findings, interpretations, and conclusions expressed in this Guidebook are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent. Living Standards Measurement Study (LSMS) World Bank Development Data Group (DECDG) [email protected] www.worldbank.org/lsmsdata.worldbank.org

Cover images: J. Durazo/World Bank; Ra Puji Wulandari Tungga Dewi/World Bank; Kevin McGee/World Bank Cover design and layout: Deirdre Launt

TABLE OF CONTENTS

ACKNOWLEDGMENTS .................................................................................................................................................................................... v

EXECUTIVE SUMMARY .................................................................................................................................................................................... vi

1. INTRODUCTION ........................................................................................................................................................................................... 1

1.1 Standard vs. non-standard units ...............................................................................................................................................................................................1 1.2 The market survey .........................................................................................................................................................................................................................3 1.3 The main survey ..............................................................................................................................................................................................................................4 1.4 This Guidebook ...............................................................................................................................................................................................................................42. METHODOLOGIES FOR REPORTING CONSUMPTION AND PRODUCTION QUANTITIES .......................................................5

2.1 Collecting data on food consumption ....................................................................................................................................................................................5 2.2 Collecting data on agricultural production ...........................................................................................................................................................................6 2.3 Importance of non-standard units in household surveys ...............................................................................................................................................6 2.4 Non-standard units in household surveys ............................................................................................................................................................................7 Benefits of allowing reporting in non-standard units ......................................................................................................................................................7 Challenges of allowing reporting in non-standard units ................................................................................................................................................8 How common are non-standard units in surveys? ...........................................................................................................................................................93. GUIDELINES AND PROCEDURES FOR CAPTURING AND USING NON-STANDARD UNITS ...................................................10 3.1 Market survey planning and preparation .........................................................................................................................................................................10 Timing of market survey ...........................................................................................................................................................................................................10 Selection of markets to visit ...................................................................................................................................................................................................11 Preparation of survey materials ............................................................................................................................................................................................11 3.2 Constructing the list of non-standard units .....................................................................................................................................................................13 Market survey before/independent of main survey .....................................................................................................................................................13 Market survey after main survey ..........................................................................................................................................................................................14 3.3 Collecting weights for conversion factors ........................................................................................................................................................................14 3.4 Collecting reference photos ...................................................................................................................................................................................................16 Which item-units require photos?........................................................................................................................................................................................17 Guidelines for reference photos ...........................................................................................................................................................................................18 Creating and using the photo reference album .............................................................................................................................................................23 3.5 How to use the non-standard units libraries ..................................................................................................................................................................234. BENEFITS OF USING COMPUTER ASSISTED PERSONAL INTERVIEWING (CAPI) .......................................................................25

4.1 CAPI for market surveys .........................................................................................................................................................................................................25 4.2 CAPI for food consumption and agricultural production survey ...........................................................................................................................265. CONCLUSION ..............................................................................................................................................................................................27

REFERENCES .....................................................................................................................................................................................................28

iv v

ANNEX 1: SURVEY INSTRUMENTS .............................................................................................. ................................... ............................29

NSU market survey: questionnaire (Nigeria)NSU market survey: manual (Nigeria)Household survey: reference photo album (Ethiopia)Household survey: consumption module (with NSUs)Household survey: training manual (excerpt)

* Additional examples available online

ANNEX 11: LIBRARY OF NONSTANDARD UNIT CONVERSION FACTORS AND REFERENCE PHOTOS..... .. ..................... ...... 61

Ethiopia: documentation and reference photographs

Malawi: documentation and reference photographs

Nigeria: documentation and reference photographs

Uganda: documentation

* All documents available online at www.worldbank.org/lsms

iv v

ACKNOWLEDGMENTSThis Guidebook was made possible by generous funding from UK Aid, through the grant “Improving Productivity, Gender and

Innovation Data in Low Income Countries.” The authors would like to thank Alberto Zezza, Olivier Dupriez, Kristen Hime-

lein, Heather Moylan, Talip Kilic, and Diane Steele for their inputs during the preparation and review of this Guidebook. The

supporting documentation in the Annexes was prepared as part of data-collection activities conducted in partnership with

the Central Statistical Agency of Ethiopia, the National Bureau of Statistics in Nigeria, the National Statistics Office of Malawi,

and the Uganda Bureau of Statistics. Our greatest appreciation goes to these partners for their dedication to the projects.

vi vii

EXECUTIVE SUMMARY

This Guidebook is a reference for survey practitioners, providing advice on how to incorporate non-standard units (NSUs) of measurement into household surveys for the collection of food consumption and production quantities. Food consump-tion and agricultural production are two critical components for monitoring poverty and household well-being in low- and middle-income countries. Accurate measurement of both provides better contextual understanding and contributes to more effective policy design.

At present, there is no standard methodology for collecting food quantities. In many household surveys, respondents are forced to estimate quantities in standard or metric units, typically kilograms or liters. This method requires respondents to convert from whatever unit they actually consumed (e.g., a bowl of rice) to a standard unit. This conversion process is often an unfamiliar or difficult task for respondents and can introduce measurement error. We argue that allowing respondents to report quantities directly in NSUs places less of a burden on respondents and will ultimately improve the accuracy of the information they provide.

Despite these benefits, there are some challenges with this approach. First, these NSU quantities must still be converted into standard units for aggregation and analysis. Often, conversion factors are not readily available and must be created, a process that involves its own data-collection effort. A second challenge is that NSUs are by their nature not necessarily stan-dardized across respondents. One person’s “bunch” of bananas could be half the size of another person’s “bunch.” Showing reference photos of “bunches” to respondents can ensure that the unit “bunch” is further standardized when reported. This requires that a photo reference album is also prepared. This Guidebook explains how to properly incorporate NSUs into data-collection activities—from establishing the list of allowable NSUs to incorporating all components into household surveys. A NSU-focused market survey is a critical part of preparing the conversion factors required for effectively using NSU data in analysis work. As such, the bulk of this Guidebook focuses on implementing the market survey and on calcu-lating conversion factors to ensure the highest-quality data when using NSUs.

Practical guidance on non-standard units, conversion factors, and reference photos

Although existing data must first be taken into consideration, establishing a baseline of properly documented NSUs will most often require conducting a market survey, whereby survey teams seek out item-unit combinations in the market to weigh and photograph. Both market outputs then become inputs to the main household survey: the reference photos are shown to respondents during interviews and the weights are used to create conversion factors that are applied to the reported NSU quantities, facilitating their use in data quality assurance and data analysis. Collectively, these components comprise what is referred to herein as the NSU library.

There are several important steps to follow in preparing the library: 1) Preparation—Plan the timing (relative to the main survey) and the locations of the market survey, prepare the necessary market-survey materials (instruments and manuals), and construct a list of item-unit combinations that will be allowed in the main survey; 2) Market survey implementation—Collect weights and reference photos, taking into account any sub-national variation; and 3) Data documentation for the main survey—Using the market data, create conversion factors for the NSUs and draft clear user protocols for enumera-tors (in terms of reference photos) and data users (in terms of conversion factors).

vi vii

Procedures for properly implementing these steps are summarized here, and are then covered in detail throughout the Guidebook.

a. In terms of planning and preparation, a list of valid item-unit combinations should first be constructed by reviewing, updat-ing, and supplementing as necessary any existing sources that contain information on common NSUs. Next, when planning the market survey, it is especially important to consider its timing relative to the main survey where consumption and agricultural production data will be collected. Ideally, the market survey should be conducted prior to the main survey in order to use the reference photos during the main survey. If necessary, a much smaller-scale market survey can be conducted after the main survey to collect missing weights for any unanticipated conversion factors. Finally, markets should be selected to ensure adequate coverage of NSUs in the relevant context. This is particularly important if NSUs differ across regions.

b. Following these preparatory steps and the detailed market-survey implementation guidelines herein will ensure that as many item-unit combinations are collected as possible, the weights collected are comparable and accurate, and the reference photos clearly demonstrate the actual size of the NSUs. Annex I contains sample survey instru-ments.

c. After the market survey, the information collected should be prepared for use with the main survey. A library of NSU materials should be compiled, starting with the calculation of conversion factors that can be applied to NSU consump-tion and production quantities collected during the main survey. These conversion factors are used to flag unreasonable quantities for further verification; when surveys are conducted using computer-assisted personal interviewing (CAPI), this can be done during the course of fieldwork. When the main survey is complete, the conversion factors can be used to calculate total consumption, analyze poverty, etc. The library should also include an album of refer-ence photos compiled from the photos collected in the market survey. This album should be used by the enumerators conducting the main survey to provide a reference size for NSUs. Finally, the library must include documentation of how the materials were prepared and how to properly use them during the main survey. We highly recommend that the library be made publicly available for use in other surveys in order to further standardize NSU reporting across data-collection efforts. The library can be continually updated as more information is collected.

Annex II to this Guidebook contains libraries for Ethiopia, Nigeria, Malawi, and Uganda, and is available online. Although they are targeted for use with LSMS-ISA surveys, the libraries are intended to be used by any researchers conducting simi-lar survey activities in these countries. The libraries should be considered living documents, to be revised and updated with each new data-collection effort given that available foods and commonly used units and quantities may vary over time. Even so, making NSU libraries publicly available for more countries will make it easier to implement surveys that allow NSUs and will therefore result in improved data-collection for quantities of food consumption and agricultural production.

1

1. Introduction

Measuring poverty often depends on measuring food—food that is both purchased and harvested from the field. In low- and middle-income countries especially, food consumption still constitutes the largest share of total household consumption. As such, constructing a food poverty line and using it to estimate the total poverty line is the preferred methodology for measuring the share of households that are poor, which in turn is one of the most common welfare-analysis indicators for developing economies. Another important element of welfare analysis is the productivity of income-generating activities. In many low- and middle-income countries, agriculture is a major source of livelihood, and measuring agricultural productivity requires adequately measuring the quantity of agricultural output. Data on food quantity is also important for the computation of unit values for food items and crops, which in turn is critically important for monitoring and analyzing prices. Despite the importance of this information, accurately measuring both the quantity of food consumed and the quantity of agricultural output can be very challenging.

1.1 STANDARD VS. NON-STANDARD UNITSOne important aspect of collecting information on food con-sumption and agricultural production is the choice of units in which respondents can report quantities. Many surveys require quantities to be reported only in “standard” units such as kilograms, pounds, liters, etc. In these cases, “local” or “non-standard” units are disallowed. Forcing respondents to report only in standard units simplifies the use of the data (since aggregation/analysis of food-item consumption often requires a common unit of measure) but it can impose a sig-nificant cognitive burden on the respondent, which in turn can reduce the accuracy of the resulting data.

Many respondents in low- and middle-income countries are more comfortable reporting their food consumption and pro-duction using familiar “local” or “non-standard” units instead of standard units. Forcing respondents to convert from these familiar units into standard units during an interview is a type

of cognitive task. Recent studies show that asking respon-dents to combine memory recall with cognitive tasks, such as abstracting consumption to a “typical week or month,” leads to less accurate self-reporting (Beegle et al., 2010).

The forced conversion from non-standard to standard units requires respondents to undergo the process depicted in Figure 1. Respondents 1) must have a good understanding of what a standard unit of a food item is (e.g., how much is a kilogram of rice), 2) must estimate how many standard units correspond to the NSU they know (e.g., how many kilograms fit into a cup of rice), and finally 3) using the conversion from 2, must calculate the quantity consumed in standard units (e.g., 1 cup of rice is about 0.5 kg, I consumed 1.5 cups of rice, so I consumed about 0.75 kg of rice). All three stages place a cognitive burden on the respondent and can lead to sizable measurement error. Allowing respondents to directly report consumption in NSUs would ease the burden on the respon-dents and will ultimately result in more accurate reporting of their consumption.

1. INTRODUCTION 2

Figure 1 — Forcing NSU Conversion vs. Allowing NSUs

We consumed 1.5 bowls of rice.How much rice is a kg? I am not really sure.How many kgs of rice are in a bowl? I guess about 0.5 kg.So then I guess we consumed 1.5 bowls of rice X 0.5 kg in a bowl=0.75 kg of rice!

We consumed 0.75 kg.

We consumed 1.5 bowls of rice.

This size.

Apply collected conversion factor of 0.689 kg of riceper bowl to get 1.0335 kg of rice consumed.

Was the bowlsimilar to thissize, or to thissize?

FORCING STANDARD UNITS: More burden on the respondent, less consistency in conversion factors

ALLOWING NSUs: Simpli�es respondent’s role, conversion factors are consistent

How many kilogramsof rice did you consumein the past 7 days?

How much rice did you consumein the past 7 days?

Source: World Bank, LSMS Team.

3 THE USE OF NON-STANDARD UNITS FOR THE COLLECTION OF FOOD QUANTITY

While allowing NSU reporting will eliminate some burdens for the respondent, it does not mean the issues of NSU con-version disappear. Instead, it falls to the survey or research team to acquire the necessary information to take NSU quantities from respondents and convert them to common standard units (i.e., undertake steps 1, 2, and 3 mentioned above). The most critical information required to make the conversions is a list of standard-unit conversion factors for each NSU as well as for each food item. These item-unit con-version factors can be applied to NSU quantities reported by respondents to convert them into standard units (typically kilograms and liters). In an ideal world, a list of such conver-sion factors would already exist for the relevant country or context. However, the current reality is that conversion fac-tors are not readily available in many low- and middle-income countries. When they are available, they are often limited in scope or poorly documented, making their applicability and reliability hard to determine. When reliable conversion fac-tors are not available, it is up to the national statistics agency or research team to collect the weights and calculate the conversion factors required to convert non-standard units into clearly and widely measurable standard units such as kilograms or liters.

Going about collecting the necessary information to prop-erly incorporate NSUs into a survey and make NSU quan-tities usable for analysis is not a trivial process. The varied nature of NSUs introduces significant challenges to any sur-vey or research team undertaking this task. For example, similarly named NSUs can vary significantly within countries or subnational regions. Even within the same locality, NSUs often come in more than one size (e.g. small, medium, large). The challenges are particularly significant for vaguely defined NSUs such as pieces, heaps, bunches, etc. A “heap” of toma-toes can vary dramatically in size, making it difficult to con-vert each respondent’s “heap” in a consistent and accurate manner. While these challenges are significant, there are no comprehensive guidelines on how to properly collect this information.

This Guidebook is meant to fill this gap by highlighting the necessary steps and best practices for collecting this information. Establishing a systematic, well-documented, and more precise set of conversion factors for non-stan-dard units—and using it to both inform survey design and to convert reported measurements—will go a long way toward increasing the accuracy of crop-output estimates and household consumption. This in turn will allow for more informed policymaking on important development issues

such as household and individual welfare as well as agricul-tural productivity.

1.2 THE MARKET SURVEYThere are a few methods for calculating conversion factors. One such method suggested by Capéau (1995) and Capéau and Dercon (2006) is to compare unit prices using econo-metric techniques to estimate conversion factors. While this method is fairly simple to implement, it suffers from some drawbacks. Primary among these is that unit prices can vary because of factors unrelated to the actual mass or volume of an item. For example, unit prices can vary because of quality differences (Deaton 1997) or because of price discounts on larger units (Attanasio & Frayre, 2006).1 In addition, unlike conversion factors, prices can be subject to significant volatil-ity due to market forces. These sources of variability in unit prices unrelated to mass or volume can result in distorted or imprecisely estimated conversion factors.

The main alternative method is to conduct a market sur-vey where non-standard units are sought out and directly weighed. This is a more intensive process than calculating conversion factors from unit prices, but will likely result in more accurate conversion factors. When conducting a market

1 Under this methodology, a numeraire unit price (usually kilograms or liters) is used to compare with other units. For larger units, there may be discount in the price per kilogram and thus applying the numeraire unit price would underestimate the conversion factor for larger units. The reverse is also true for smaller units.

Figure 2 — Vaguely Defined NSUs

How much?

One small pile.


1. INTRODUCTION 4

survey, there are certain protocols that must be followed to ensure the collected weights are accurate and usable for cre-ating conversion factors. For example, conversion factors for vaguely defined units (especially non-container units such as pieces, heaps, bunches, etc.) are most reliable when accom-panied by reference photos. These photos can be shown to the respondents to provide standardized reference sizes for a “small heap” of onions, for example. Without the photos, the “small heap” reported by the respondent could be con-siderably different from the “small heap” used to establish the conversion factors (see Figure 2). These reference pho-tos must therefore be taken and collected along with the weights.

1.3 THE MAIN SURVEYOnce all the requisite information is collected for proper implementation of NSUs in a survey, the interview process becomes much less taxing on the respondents, without additional burden on the enumerators. The bottom panel of Figure 1 depicts the revised process. The respondent is only required to think about consumption or production in the unit with which she is most familiar. The enumerator simply confirms this unit using the reference photo and then records the amount in NSUs. Afterward, conversion factors are applied to the reported NSUs to arrive at the correct standard weight.

1.4 THIS GUIDEBOOKThis Guidebook serves as a reference for preparing and using non-standard units: establishing a list of valid NSUs, collecting standard weights and reference aides for NSUs (usually via a market survey), calculating conversion factors from these weights, and incorporating NSUs into household and agriculture surveys. It also provides a library of local units, conversion factors, and photographic aids for selected countries. The Guidebook is structured as follows. Section 2 provides background on non-standards unit (NSUs), dis-cusses the importance of properly quantifying household consumption and production, and offers various methods of collecting this data. The section also details the bene-fits and challenges of NSUs and documents their use in the Living Standards Measurement Study-Integrated Surveys on Agriculture (LSMS-ISA) implemented by the LSMS team of the World Bank. Section 3 outlines the components of a high-quality NSU library as well as the necessary procedures for conducting a market survey to collect the components of the library. Section 4 discusses some of the important

benefits that are derived from utilizing CAPI survey meth-ods to both collect and use information contained in a NSU library. Section 5 offers concluding remarks. Annex I pro-vides a set of sample instruments for collecting and then using NSUs. Annex II is available online and provides librar-ies of NSU conversion factors from four countries (Ethiopia, Malawi, Nigeria, and Uganda).

THE LIVING STANDARDS MEASUREMENT STUDY–INTEGRATED SURVEYS ON AGRICULTURE (LSMS–ISA) is a household survey project to foster innovation and efficiency in statisti-cal research on the links between agriculture and poverty reduction in the region. Recognizing that existing agricultural data in Sub-Sa-haran Africa suffers from inconsis-tent investment, institutional and sectoral isolation, and methodolog-ical weakness, the LSMS-ISA proj-ect collaborates with the national statistics offices of its eight partner countries to design and implement household surveys with a strong focus on agriculture. In each part-ner country, the LSMS-ISA sup-ports multiple rounds of a nationally representative panel survey with a multi-topic approach designed to improve the understanding of the links between agriculture, socio-economic status, and non-farm income activities. The frequency of data collection is determined on a country-by-country basis, depend-ing on data demand and the avail-ability of complementary funding.

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2. Methodologies for Reporting Consumption and Production Quantities

Food consumption and agricultural production are two of the most important measurements in living standards surveys as well as in many other household surveys in low- and middle-income countries. Food consumption is the primary component for many measures of poverty, nutrition, and food security. Information on agricultural production provides important insights on agricultural performance as well as farm household income and own-food consumption. The critical importance of consumption and agricultural production quantities has led to the development of several different measurement methodologies. Each method has its merits and drawbacks and is not necessarily applicable in all situations. However, we argue that the use of non-standard units to measure quantity is widely applicable and strikes a fair compromise in terms of cost.

2.1 COLLECTING DATA ON FOOD CONSUMPTION The various methods of collecting food-consumption data are the subject of a large and well-established body of liter-ature. In general, consumption information is typically col-lected via respondent recall interviews or a consumption diary. For recall, respondents are asked to estimate their consumption of an item over a specified period, typically seven days. Under the diary method, respondents are asked to keep a daily diary of their consumption. Both methods require respondents to report quantities of food consumed. Though there is a broad range of survey-design issues (see Beegle et al., 2010 for a review of these issues), the discussion here will focus on collecting quantities, as this is the specific design focus of this Guidebook.

There are many methods used to collect information on the quantity of food consumed in a household survey. Smith & Subandoro (2007) discuss seven primary methods, sum-marized as follows:

1. Metric (i.e., standard) units: Respondents report quantities in metric units such as kilograms or grams. While this method is low cost and relatively easy to record, it can result in inaccurate esti-mates in some circumstances (see below).

2. Monetary value: Respondents estimate the mone-tary value of the quantity consumed or produced. This method requires additional collection of met-ric prices in order to estimate quantities, which can also be subject to significant errors.

3. Local (i.e., non-standard) units: Any unit of mea-surement that does not have an objective, univer-sal metric or standard weight. This includes items such as “pail,” “basket,” or “pieces;” the latter is discussed in #4 below.

4. As in #3, respondents report quantities in terms of non-standard units with which they may be more familiar. These methods ease the burden on the respondent (in terms of memory recall and conversion calculations), but can increase the cost of survey implementation.

2. METHODOLOGIES FOR REPORTING CONSUMPTION AND PRODUCTION QUANTITIES 6

5. Volumetric equivalents: Respondents demonstrate how much space the food they consumed would take up. Conversion factors would need to be ap-plied to convert to metric units.

6. Linear dimensions: Respondents provide linear measurements (length and width or circumference) of the amount of food consumed. As Smith & Subandoro (2007) point out, this method likely takes more time to complete as it requires physical measurement rather than a simple vocal response.

7. Food models: Respondents choose a two- or three-dimensional depiction of a food item that best corresponds to their consumption amount. This method can provide very accurate estimates, but it can be costly to prepare the models and cal-culate their weights.

While one method may be optimal for certain items, it may not be feasible or appropriate for others. Smith & Subandoro (2007) advocate using a combination of these methods. This Guidebook and the accompanying library will focus on four of these methods, which are complementary and compre-hensive: metric units, local units, including a count of pieces, with some two-dimensional depictions (i.e., reference pho-tos). Joint use of these four methods will minimize the burden on the respondent as well as on the enumerator, although it may require additional costs beyond the main survey visit.

2.2 COLLECTING DATA ON AGRICULTURAL PRODUCTION There are three prevailing methods for measuring agricul-tural production: farmer recall, whole plot harvest, and crop cutting (Sud et al., 2016). Under the recall method (as with recall for food consumption), farmers estimate how much of a particular crop they have harvested since a certain date. Both whole plot harvest and crop cutting are much more labor-intensive processes that attempt to eliminate the sub-jective bias or error inherent in farmer estimates. Under the crop-cutting method, a portion of a farmer’s crop is cut and measured by enumerators at the time of harvest. However, there are some potential sources of bias that arise in the crop-cutting method (Fermont & Benson, 2011). Whole plot harvest is similar to the crop cutting method, but the output of the entire plot is cut and measured. This is considered the most accurate yield measurement, but is also extremely

costly to implement on a large scale. While there are numer-ous issues associated with all three of these methods, they are largely beyond the scope of this Guidebook (see Fermont & Benson, 2011 and Sud et al., 2016 for a review). The focus here is on the collection of harvest quantities.

In principle, many of the consumption-quantity collection methods outlined by Smith & Subandoro (2007) are also applicable to the collection of agricultural-production quan-tities. However, there is one additional issue that is specific to the measurement of crop harvests. The condition of the crop—threshed, shelled, fresh, dried, etc.—can have a large impact on reported harvest quantities (Fermont & Benson, 2011; Diskin, 1999; Murphy et al., 1991). The weight difference is either due to discarding a portion of the crop via thresh-ing, shelling, or peeling, or is the result of a change in mois-ture content through drying. These processes are particularly important for cereals and legumes, which are quite often processed before being used or sold. It is therefore import-ant to ensure that when a harvested quantity is reported, the condition of the crop to which the quantity refers is also specified. When quantities are reported for various condi-tions, additional condition-specific conversion factors can be applied to render the quantities comparable.

2.3 IMPORTANCE OF NON-STANDARD UNITS IN HOUSEHOLD SURVEYS The methodological issue that is the focus of this Guidebook is the use of non-standard units in the collection of con-sumption and production quantities. But what exactly are “non-standard” versus “standard/metric” units? Both stan-dard and non-standard units are commonly used in markets or by households in many countries. Standard units are uni-versally constant, referring to a clearly defined weight and/or volume. A kilogram in Uganda is the same as a kilogram in France. Likewise, a kilogram of maize is the same weight as a kilogram of wheat. For the most part, “standard” encom-passes metric units, imperial measurements, and other inter-nationally standardized units that are easily converted into metric units. For example, the conversion between kilograms and pounds is constant regardless of region or item.

In contrast to standard units, non-standard units (NSUs) often vary greatly from item to item, region to region, and even village to village. Table 1 presents examples of some common standard units and NSUs.


Some NSUs are common across many locations. For example, throughout the world, bananas and other items are often measured in bunches. While this NSU is common, it is not standardized. The number and size of the bananas that are in a bunch are not standard; one bunch of bananas could be three times the size of another bunch. Likewise, a bunch of bananas is not equivalent to a bunch of herbs. The same is true for pieces, heaps, and other units. In addition to these common NSUs, there are also NSUs that are spe-cific to a country or region. Table 1 includes several NSUs commonly used in Uganda (far right column). Many of these units are locally familiar containers of a standard volume; however, the weight of the contents will vary depending on the item. For example, a Nido tin of rice does not weigh the same as a Nido tin of groundnuts. The use of local units can vary significantly within a country. As an example, Table 2 presents the distribution of local units in Nigeria observed

Table 1 — Examples of Standard and Non-Standard UnitsStandard Non-standard

Common Local (Uganda)

Kilograms Sack Jerrican

Grams Bunch Kimbo/Blueband tin

Liters Heap Nido tin

Centiliters Piece/number Cup/mug

Pounds Bucket Nice cup

Crate

Plastic basin

Table 2 — Regional Variation of NSUs in Nigeria

% of all NSU Observations in Zone

North Central North East North West South East South South South West

Mudu 56.7 62.4 17.4 0.0 0.7 0.0

Olodo 0.0 0.0 0.0 0.0 14.0 0.0

Congo 7.5 0.0 0.0 0.0 0.0 47.9

Paint rubber 3.9 0.2 0.6 12.1 0.0 2.7

Derica 0.4 1.3 0.2 2.5 16.1 13.8

Milk cup 27.3 8.9 21.4 21.6 42.6 28.8

Cigarette cup 0.5 0.0 0.1 60.7 22.3 0.0

Tiya 0.0 26.7 58.5 0.0 0.0 0.0

Kobiowu 2.8 0.0 0.0 0.0 0.0 0.0

in the second wave of the General Household Survey Panel (GHS-Panel) for each of the six geopolitical zones. Only one unit (milk cup) is common to all six zones. Most units are only found in two to three zones and are rarely or never observed in others. These complexities associated with NSUs create some challenges relative to standard units. However, there are additional factors that contribute to the relative merits of the methods, detailed further below.

2.4 NON-STANDARD UNITS IN HOUSEHOLD SURVEYS

BENEFITS OF ALLOWING REPORTING IN NON-STANDARD UNITSThere are trade-offs involved in deciding whether to allow respondents to report quantities in NSUs or to restrict respondents to reporting in only standard units. Although NSUs are subject to significant variation, there are tangible benefits to allowing respondents to report in NSUs. The most important and overriding benefit is that respondents will likely be better able to estimate quantities using NSUs. In rural areas especially, standard units may not be commonly used in markets and respondents may not regularly use stan-dard units in their daily activities. Even though respondents may know exactly what a kilogram of sugar looks and feels like (a very common sales unit for sugar), they may not know this for cassava, maize, or other items that are not typically traded in kilograms at the household level. Likewise, many items are not generally consumed in standard units. Often, fruit is sold by the piece instead of by weight; herbs are

Note: Shaded cells = Units rarely/never observed in that zone.Source: World Bank, LSMS Team.


2. METHODOLOGIES FOR REPORTING CONSUMPTION AND PRODUCTION QUANTITIES 8

sold by the bunch, regardless of weight variation; and home-grown fruits or vegetables are harvested and eaten without being weighed. When respondents are more familiar with NSUs for specific items, it may be too burdensome to expect them to know that item in terms of standard units.

Forcing respondents to report quantities in standard units often combines two self-reporting styles, each with its own potential for error: memory recall and cognitive reasoning. Household consumption modules typically ask respondents to recall a litany of food items eaten by numerous household members over a given period. Farming households are asked to recall and report on a variety of different crops harvested over a given period. The latter case is further complicated by the fact that key crops throughout the region (e.g., cassava, maize, and plantains) are typically harvested in small quanti-ties on a continual basis.

Both memory recall and ad-hoc unit conversions also require mathematical calculations that, while not necessar-ily complicated, are prone to errors when done in the field and on the fly—even more so when considering respondent and enumerator fatigue. Combining memory recall with unit conversion increases the number of calculations required of the respondent for each value, which further increases the potential for error (as shown in Figure 1). In general, allow-ing respondents to report in the units they can most easily quantify simplifies memory recall and will yield estimates that are more accurate.

CHALLENGES OF ALLOWING REPORTING IN NON-STANDARD UNITSAlthough there is a strong case for allowing respondents to report in NSUs, many surveys of consumption and agri-cultural production still restrict respondents to report-ing amounts in standard units. This is primarily due to the additional cost and challenges associated with properly implementing and operationalizing NSUs in a survey. The complexity of NSUs as well as the additional steps required for their use can increase the financial and temporal bur-den of conducting a survey. The challenges associated with using NSUs broadly fall into two categories: (1) those asso-ciated with the preparation and implementation of the sur-vey with NSUs, and (2) ensuring NSU measurements can be converted into comparable standard units.

One of the first challenges that survey designers face is identifying the units to be included in the survey. When respondents are limited to reporting in standard units, com-piling the code list is straightforward. However, compiling a list with non-standard units requires additional information about the common NSUs in the relevant country and/or regions. When such information is limited or not available, it will need to be collected via a market survey.

In addition to identifying the NSUs to include in the main survey, survey designers also need to ensure the clarity of the unit definitions. Some of the most common units that fall into this category are pieces, bunches, or heaps. For example, a piece of sweet potato could weigh 0.5 kilograms or 1.5 kilo-grams. Figure 3 below illustrates this problem: the pictured containers vary significantly in size but are all called dengu in Malawi. In order to obtain the most accurate estimates for these units, respondents should be provided with a refer-ence frame for the quantity. One way to do this is to pro-vide respondents with reference photos for these items. This resource can also be produced as part of the market survey and requires additional enumerator training (detailed below).

Figure 3 — Wide Variety of Dengus of Tomatoes in Malawi

The final and most significant challenge in using NSUs is that they must be accompanied by standard-unit conversion factors. In their raw form, quantities in NSUs are not compa-rable across units. To directly compare and aggregate quanti-ties, the data user must convert all quantities into a common standard unit such as kilograms. Converting between



standard units is relatively easy since the conversions are constant and well known. However, for NSUs, the conver-sion is different for each unit and often for each item. Com-plicating matters further, the standard weight for the same item-unit combination can vary, even within a country. For example, one study in Nigeria found that an average bundle of sorghum weighed between 26 and 49 kilograms depending on the area (Casley & Kumar, 1988). When this is the case, region-specific conversion factors should be acquired.

HOW COMMON ARE NON-STANDARD UNITS IN SURVEYS? In low- and middle-income countries, especially in Africa, NSUs are used quite regularly for the most important items. At markets in these countries, consumers encounter a wide variety of NSUs for their purchases. In addition, when given a choice between reporting quantities in standard or non-stan-dard units, respondents often choose to report in NSUs. For example, in the second wave of the Ethiopia Socioeco-nomic Survey from 2013/2014 when NSUs were allowed, nearly 50 percent of farmers chose to report their harvests in NSUs. In the Malawi National Panel Survey, respondents chose NSUs about 73 percent of the time. This provides a strong indication that many respondents are more comfort-able reporting quantities in NSUs.

While the challenges associated with including NSUs in a consumption or agricultural production survey can be sig-nificant, this Guidebook provides detailed instructions to help survey designers incorporate NSUs into their surveys.

Figure 4 — Recommended Steps for Using NSUs

Prepare to use NSUs1. Establish valid list of NSUs:create new or update existing list2. Plan Market Survey

Conduct Market SurveyCollect national/regional weights and photos. Skip this step ONLY IFexisting data is available and is current.

Create Tools for Main Survey1. Generate conversion factors (preload into CAPI if using)2. Compile photo reference guide3. Write user protocols

Finalize Data Documentation1. Clearly document all steps and NSU/CF data sources.2. If CFs are missing, conduct a brief follow-up survey and updatefinal NSU and CF.

Conduct Main SurveySee Annexed examples for

including NSUs in main survey.


10

3. Guidelines and Procedures for Capturing and Using Non-Standard Units

This section lays out the necessary steps and procedures required to collect the information necessary to implement and use NSUs in household surveys. Before NSUs can be used, a resource library for NSUs will need to be prepared. This library should include (1) a list of common/allowable NSUs; (2) national or regional conversion factors for all item-unit combinations; (3) a photo reference album based on an index of NSUs; and (4) clear protocols for using conversion factors and reference photos in agricultural and household surveys. The best way to collect the information for the library is to conduct a market survey to capture reference photos and the item-unit weights used to calculate conversion factors. In countries where surveys already allow reporting in NSUs, existing data (once updated, if need be) can complement the library. Taken together, these components will help researchers to adopt the use of NSU reporting; for countries with libraries provided in this Guidebook, the cost/burden of adoption is significantly eased. These libraries should not be treated as fixed, but should instead be continually updated with new NSUs and conversion factors.

There are several important steps to follow when collect-ing the components for an NSU conversion-factor library (see Figure 4): 1) Preparation—Plan the timing (relative to the main survey) and the locations of the market survey, prepare the necessary market-survey materials (instru-ments and manuals), and construct a list of item-unit com-binations that will be allowed in the main survey; 2) Market survey implementation—Collect weights and reference photos, taking into account any sub-national variation; and 3) Data documentation for the main survey—Using the market data, create conversion factors for the NSUs and draft clear user protocols for enumerators (in terms of reference photos) and data users (in terms of conver-sion factors). Each of these steps is covered in detail here.

3.1 MARKET SURVEY PLANNING AND PREPARATION

TIMING OF MARKET SURVEYThe data-collection schedule for the market survey should take into consideration the seasonal availability of items and existing data-collection schedules in each country. In some cases, market-survey data collection should be planned for two separate periods to ensure more complete coverage of seasonally available items. In general, the greatest variety of items and the greatest variety of crop conditions will be available during the harvest season, though some items may only be available during the lean season or after a secondary harvest season.


The timing of the market survey relative to the main sur-vey is important. Performing the market survey before the main survey (ex-ante or independently) has several advantages. First, reference photos can be taken and then used during the main survey, and conversion factors can be used to validate reported quantities during fieldwork, both helping to ensure more accurate NSUs estimates. Second, conducting the mar-ket survey ex-ante allows for the identification of additional NSUs that may be missing from any existing list of answer options. Identified in advance, these units can be incorporated into the unit list for the main survey.

However, there are also some drawbacks to conducting the market survey before the main survey. The primary one is that new units not included in the market survey could be reported in the main survey. When the market survey is per-formed after the main survey (ex-post), the unit list for the market survey can be constructed to include all item-unit (and item-unit-conditions) observed in the main survey, thus limiting any conversion-factor gaps.

Given these considerations, the ideal plan is to conduct two market surveys—one before and one after the main survey. Both market surveys need not be equally rigorous; one will likely be more comprehensive than the other. For example, the ex-ante survey could be limited, aiming to collect reference photos and weights (for conversion-factor calculations) for the most common NSUs, while the ex-post survey could com-prehensively collect weights for all additional NSUs reported during the main survey. Or the ex-ante survey could be inten-sive, aiming to collect as many conversion-factor weights as possible—especially when conducted independently—while the ex-post survey could be limited to collecting only those unanticipated item-unit combinations. In general, the intensive version of the market survey should coincide with the season when the most items will be available in the markets.

Many household surveys already conduct market surveys as part of their fieldwork to collect current pricing infor-mation on commonly consumed items. When surveys allow NSU reporting, the market surveys could also collect actual weights of allowable NSU combinations that can be used to calculate standard-unit conversion factors. However, in such cases where the market survey is conducted in parallel with the main survey, reference photos would most likely not be available for use during interviews.

SELECTION OF MARKETS TO VISIT Three main factors will influence the selection of markets for the survey: 1) the degree of regional diversity of units

and their respective weights; 2) the relative timing of market surveys (as explained above); and 3) the types of markets fre-quented by sample households.

Markets should be selected to ensure adequate coverage of regional units and items. For market surveys conducted after the main survey, coverage can be assessed using the item-units observed in each stratum. The strata where the widest diversity of regional units is observed are prime candidates for the market survey. If the item-units were reported in the stratum, it is likely that measurements for that item-unit can be obtained from a market in that area. If the market survey is conducted independent of or prior to the main survey, ade-quate coverage must be assessed using external information on regional variations in units as well as information from the pilot survey (if conducted).

In many countries, households may patronize various types of markets, including local outdoor markets and small shops, supermarkets, wet markets, and wholesale markets. Markets selected for the survey should cover the full range of markets commonly used by households or farmers in the sample area.

In general, the number and dispersion of markets selected for the survey is highly dependent upon the context. For a nationwide survey in a large and diverse country like Ethio-pia, it would likely be necessary to visit many markets across the country to ensure adequate coverage of NSUs, espe-cially if the market survey is conducted during or after the main survey. However, for a market survey limited to a single region/state or community, visiting only a few markets may be sufficient.

PREPARATION OF SURVEY MATERIALSOnce markets are selected, the survey materials (survey instruments and supporting manuals) can be prepared. While these materials should be designed according to the local con-text, Annex I includes examples from NSU-focused market surveys that were conducted to create the LSMS conver-sion-factor libraries for Ethiopia, Malawi, and Nigeria. Figure 5 depicts a snapshot of the market survey questionnaire for Ethiopia.

Though these survey instruments are specific to these countries, they also serve as examples of how to prepare instruments for any country/project. Each survey can collect the following key types of data:

• Market identification details: Name, location, GPS infor-mation, type of market, etc.

3. GUIDELINES AND PROCEDURES FOR CAPTURING AND USING NON-STANDARD UNITS 12

• Survey management information: Date, time, duration of surveys; codes for enumerator, supervisors, and (when applicable) data-entry staff.

• Data on pre-identified NSUs: Weights, prices, and basic metadata for common item-unit combinations that have been previously identified.

• Data on unexpected NSUs: Teams can collect the same type of data listed above for item-unit combinations that are not pre-defined, but that are present in the market. If such NSUs are commonly used in a regional market, it is likely that household survey respondents are purchasing,

and thus more readily able to report, in these quantities.

The Nigeria survey is split into two sections, allowing enu-merators to more easily divide and share the data-collection work during each market visit. Detailed instructions on how to collect the data and complete the questionnaires are in the training manuals (also included in Annex 1).

3.2 CONSTRUCTING THE LIST OF NON-STANDARD UNITS The first step in preparing the NSU library is to establish the list of common NSUs that will be used in the consumption and/

Figure 5 — Excerpt from a Market Survey QuestionnaireMODULE B: ITEM-UNIT MEASUREMENT - NONCONTAINERS

1 2 3 4 5 6 7 8 9

ITEM NAME

ITEM CODE

UNIT NAME

SIZE Was item measured?

YES...1(7)

NO..2

Why was item not measured?

NOT FOUND IN MARKET AT THIS TIME........................................................1CROP NOT COMMONLY FOUND IN THIS MARKET.................................2UNIT NOT COMMONLY FOUND IN THIS MARKET.................................3 SIZE NOT COMMONLY FOUND IN THIS MARKET.................................4

OTHER, SPECIFY..................................5

Item Sample #1 Item Sample #2 Which type of scale was used?

PERSONAL DIGITAL SCALE..................................1

MARKET SCALE WITH GOVERNMENT CERTIFI-CATION.............................2

MARKET SCALE WITH-OUT GOVERNMENT CERTIFICATION..............3

Weight(KGs)

Price(Birr)

Weight(KGs)

Price(Birr)

CEREALS AND GRAINS

BARLEY 1 ESIR Small

1 ESIR Medium

1 ESIR Large

1 CHINET Small

1 CHINET Medium

1 CHINET Large

1 SHEKIM Small

1 SHEKIM Medium

1 SHEKIM Large

MAIZE 2 PIECES Small

2 PIECES Medium

2 PIECES Large

2 ESIR Small

2 ESIR Medium

2 ESIR Large

2 CHINET Small

2 CHINET Medium

2 CHINET Large

MILLET 3 ESIR Small

3 ESIR Medium

ALL RESPONSES ( NEXT ITEM)



or production modules of the main survey. A list of common/allowable item-unit (and when applicable, item-unit-condi-tion) combinations for NSUs should include a comprehen-sive set of valid NSU combinations for each crop and each food item. Where applicable, crop/food condition (e.g., corn in husk or not, peanuts shelled or unshelled, fresh vs. dried cassava) should be considered, especially for reporting har-vested quantities, as the condition significantly impacts the weight-volume ratio. While it may be impossible to prede-termine all the possible combinations, the library should endeavor to include combinations that represent the vast majority of options (preferably higher than 90 percent). Even when the same crops are grown and the same foods are con-sumed in different countries, it cannot be assumed that the same NSUs will be used in both places.2

The best practice for compiling this list would be for national statistics agencies to establish a conversion-factor library independent of any specific household survey, which can then be made available for use with any new survey within the country. Unfortunately, many low- and middle-income countries have no such source for NSU conversion factors; when they do, documentation and other supporting materials are often limited or lacking. When a conversion-factor library is available and well documented, household survey teams may choose to optimize timeline and budget constraints by using this existing resource. When such a library does not exist, or if existing conversion-factor data are limited or outdated, an NSU-focused market survey must accompany the household survey. Instructions for the market survey are discussed in detail in the next section. When implementing a market sur-vey to fill these data gaps, the procedure for identifying the NSUs to include in the market survey will vary depending on the stage at which this step is performed.

MARKET SURVEY BEFORE/INDEPENDENT OF MAIN SURVEYWhen the market survey is implemented before or indepen-dent of the main survey, the first step is to seek any infor-mation on common NSUs within the country. Identifying common NSUs and the items they apply to can be quite chal-lenging, depending on the quality of information available to help guide selection. A best first source would be a com-prehensive review of NSUs within a country. The libraries

2 Cross-country comparisons may be used to check the consistency of allowable item-condition combinations and to reconcile food-weight densities for common crops. This cross-country harmonization will be the focus of future work in this series.

annexed in this guidebook are intended to be such a source, but there may be additional reviews available, such as Kor-mawa & Ogundapo (2004) in Nigeria.

When comprehensive reviews are not available, the next preferred source for common NSUs will be other surveys already conducted in the country of interest that have allowed quantities to be reported in NSUs. These could be either household-level surveys with consumption or agricultural components, or market surveys. For these outside sources, the survey designer must consider the comprehensiveness of the NSU list. Some surveys may include only a few of the most common NSUs and exclude less common though important ones. Likewise, the geographic coverage of the survey also needs to be taken into account. For example, surveys that only cover a small area may not contain NSUs that are com-mon in other areas of the country. Unless the selection of NSUs is clearly documented and comprehensive, the survey designer should seek additional information.

If resources and time permit, existing NSU lists can be val-idated with a small pilot survey to ensure the list is compre-hensive and current. The pilot survey can either be at the household or market level. Performing a household-level pilot has the advantage of capturing consumption units used by households, which may differ from the units used in market transactions. However, conducting even a limited market-level pilot survey will allow for the collection of a wide array of item-units in a single market, whereas it may take several households to acquire a comprehensive list. The pilot survey should be largely open ended, allowing respondents (either household members or market vendors) to report in the units with which they are most comfortable or in the units that are most commonly available.

Many units may be available in different sizes, such as the array of dengus shown in Figure 2. In this case, simply listing dengu in the selected unit list would not sufficiently help stan-dardize this NSU. When there is variation, the unit list should include the possibility of different sizes (e.g. small, medium, large) and the weights and reference photos for each size should be collected. This is particularly important for units such as pieces or heaps, which are subject to within-unit weight variation. When NSUs are coupled with reference photos depicting multiple measured sizes, it provides greater comparability across reported NSUs by standardizing the respondents’ reference points. For example, if tomatoes are scarce in only one region, what is considered a “large tomato” may be equivalent to a small one elsewhere; by providing standardized photo references, the respondent can point to


“their” tomato, thus ensuring its weight is converted in a standardized way, regardless of local variation.

Note that a key benefit of conducting an ex-ante market survey and using photo references in the main survey is that much of the regional variation can be eliminated, which in turn limits the scope and burden of the market surveys to be conducted. Without the ex-ante collection (which allows for greater standardization with fewer measurements), you will need to collect and compare NSU data from markets in all regions to avoid under or over-reporting consumption across regions with different concepts of reference sizes.

MARKET SURVEY AFTER MAIN SURVEY For market surveys conducted after the main survey, the NSU list can be constructed based on the units observed in the data. Constructing the list ex-post can shorten the list of weights needed to exactly those necessary to make use of the data while ensuring there are no gaps in the eventual conversion-factor data.

When constructing the list of item-unit combinations, the data should be examined for combinations that are commonly observed. Invalid combinations should be excluded. Ideally, every valid item-unit as well as crop condition observed in the data should be included in the list of units for the market survey. However, if the list of observed item-units is exten-sive and/or resources for conducting the market survey are limited, then the item-unit list can be shortened. The most obvious method is to eliminate the least commonly observed item-units. This will depend greatly on the survey, but in gen-eral only very infrequently observed combinations should be dropped.

The extent of regional variation in reported NSUs should also be assessed to determine at what level the market survey should be conducted. This can be done by comparing com-mon units at various geographic levels. If at most geographic levels the item-units are similar, then a national list can be constructed. However, if there is significant variation across regions, it may be more appropriate and feasible to disaggre-gate the item-unit lists to the regional level.

3.3 COLLECTING WEIGHTS FOR CONVERSION FACTORSThe two main purposes of the market survey are to col-lect weights in order to calculate conversion factors for consumption and production NSUs and to take reference

photos of item-unit combinations for respondent interviews. Although the procedure for collecting both these items may seem straightforward, strict protocols should be followed to obtain the most accurate conversion factors and produce useful reference photos.

A dataset of national or regional conversion factors for all allowable combinations will be the main analysis compo-nent of the library. The listed conversion factors should be provided at the lowest feasible (and representative) level of regional disaggregation. The general procedure for collecting weight measurements involves (1) finding vendors who have the necessary non-standard item-unit combination, (2) prop-erly weighing the item-unit, and (3) recording the weight of the item-unit.

Step 1: Finding item-units to weigh

Armed with the list of item-unit combinations to weigh, enu-merators should seek out each of the combinations from vendors in the market. Each item-unit measurement should be taken from multiple vendors to account for any varia-tion in vendors’ subjective assessment of what constitutes a unit amount as well as for possible enumerator error in the measurement itself. For each item-unit pair we recom-mend collecting measurements from three different vendors within each market if time, personnel, and budget constraints permit.

Survey teams need not limit measurements to the prede-termined list of item-units. If additional item-unit pairs are found at the market, record these as well. This will be partic-ularly beneficial when the market survey is conducted before the main survey as it will allow the new units to be incorpo-rated into the main survey.

If an item is available in the market, every effort should be made to collect all the listed unit options for that item. The greatest challenge at this stage will likely be that some items or units are not found due to seasonal availability of the item or limited use of a unit for sales. One solution is to search for the item-unit at vendors nearby who are outside the formal market. If the item-unit is found there, the alternative location should be noted by the enumerator.

The day of the market visit could also be an important determinant of NSU availability. In many communities, there are specific days designated as “market days.” On market days, a wide array of traders and farmers will participate in the market and thus, a greater selection of items and units will likely be available. However, there will also be more


activity on these days, making it harder to perform the mea-surements. Vendors may also be less willing to participate in the survey on a market day since they will be busier. Given this trade-off, we recommend survey teams visit the market first on a non-market day to acquire all the measurements available, and then again on a market day if any items or units are missing.

Since the focus of the survey is on consumption or produc-tion units and not specifically on market units, some contain-er-based units may not be found at the markets. This could especially be the case for some agricultural production units used by farmers but not typically sold by vendors. Enumera-tors can ask vendors about the units in which they themselves purchase items from farmers, asking them to demonstrate the appropriate quantity of the item-unit pair. Alternately, survey teams may be able to acquire such containers directly from the source, (i.e., nearby households or farms). Contain-ers may be purchased or borrowed and then brought to the market for filling and weighing.

Larger units, especially those used for measuring harvest quantities, may not be available from market vendors, but can be collected at the market scale station (further details below) or from wholesale traders in the market.

Locating a crop at the market in its various conditions will likely be difficult. Many crops will only be available in their final condition before consumption: cereals will likely be threshed; legumes will likely be shelled. In such cases, addi-tional weights may need to be acquired by conducting some measurements at the farm-household level. A limited number of condition-specific weights can be used to create conver-sion factors across item-unit-condition pairs.

Step 2: Weighing the item-units

Once an item-unit is located, it must be properly weighed. When weighing a container unit, the empty container’s weight must be excluded from the measurement. Many modern scales can automatically subtract the weight of a container (the “tare” weight) from the total weight. If the scale being used does not include the option to zero out the tare weight, then the subtraction must be done manually.

Enumerators must be properly trained in the use of scales, including how to identify appropriate (even) surfaces on which to use the scales. Scales should be calibrated regularly during fieldwork to ensure consistency across measurements. It is important that the scale be kept clear of any other objects, including any spillage from containers. For example, any grains

that fall out of a heaped container and onto the scale should be cleared before weighing.

Enumerators should not be responsible for determining the amount of the item with which a particular unit is filled. They should only weigh what vendors provide. This includes typical heaping practices for containers. If the local practice is to heap as much of an item into a container as possible, then that is what should be weighed; if leveling is common, then leveled containers should be measured. When container quantities are available heaped and level, both should be mea-sured and noted.

While most item-units will require physical weighing of the unit, in some cases no weighing will be required. This is true for item-units that are commonly purchased prepack-aged, with the weight printed on the container. Some com-mon examples are bags of rice, tinned or canned foods (e.g., tomato sauce), snack items, etc. Note that although these item-units need not be weighed, reference photos must still be taken since respondents may not remember the weight of the package but can identify which size/shape package they consumed.

For most consumption units, collecting the weights will be fairly straightforward. However, for larger units— especially those used for production—there may be additional chal-lenges. Heavier item-unit pairs are often beyond the maxi-mum range of the portable scales used for the survey. When this is the case, there are two potential solutions:

• Break up the unit into a series of smaller groups that can be weighed separately. Once all the groups have been weighed, they can be added together to acquire the total weight of the item-unit. Depending on the size of the item-unit and the maximum range of the scale used, this can be a laborious and time-consuming process. Further-more, vendors may be unwilling to open larger units (if sealed) and have them handled by enumerators.

• Make use of other scales that have a higher maximum weight. These can be either additional scales that enumer-ators bring with them to the market or higher-capacity scales found in the market. In many markets, there will be bulk traders or aggregators that purchase items from farmers for resale to market vendors. Since these traders deal in large quantities, they will likely have a scale that can measure these heavier weights. Making use of these market scales may be easier than breaking up the item-unit into multiple groups, but it does require an additional


step: calibrating the market scale. In general, market scales may not be as advanced or accurate as the main scales used for the survey. Any error in the market scale mea-surement must be estimated and corrected. That can be done by selecting an item that weighs close to the maxi-mum of the survey scale. This same item should then be weighed using the survey and the market scales and both measurements should be recorded. Comparing these two measurements will allow for error correction in the mar-ket scale’s measurement during the data-review process. Only one calibration is needed for every market scale. Since it may be impossible or at least impolite to adjust or even scrutinize the market’s scale, consider doing this after all unit measurements are collected. This procedure requires that the measurement tool also be noted: survey scales or a market scale. These scales will typically not be as precise as the smaller-capacity scales, but they are suf-ficiently precise for larger units. If higher-capacity market scales are not available or common in the market, then larger-capacity scales may be acquired for use by enumer-ators for larger units.

Another potential challenge for production units is the adjustment of weights by bulk traders or aggregators. In some cases, traders will purchase an item-unit from a farmer and adjust the weight before distributing it to market vendors. For example, a farmer may bring a sack with 115 kg of wheat, but after purchasing it, the trader might adjust the weight of the sack to an even 100 kg before selling it to market vendors. The purpose of the market survey is to acquire conversion factors for units reported by farmers, so every effort should be made to weigh the item-unit the farmer brings to the market (e.g., the 115-kg sack of wheat) before it is adjusted by the trader.

Step 3: Calculating the conversion factors

Calculating conversion factors can be a complicated process. Results from the market survey should be cleaned and outli-ers scrutinized. If there are relatively few measurements for each item-unit, outliers can distort conversion factors sub-stantially. If different sizes for a unit were allowed, the mea-surement data may require further processing. A problem may arise where classifications of a small, medium, and large versions of a unit could vary considerably. For example, the small size of a unit found in market X may be larger than the large version collected in market Y. These must be reconciled so that there is a standard classification of small, medium, and large within the relevant level of geographic aggregation (e.g., region, state). This can be done manually through review and

comparison of the reference photos and reassignment of size. However, this can be burdensome if there are many measure-ments. An alternative method is to classify measurements based on their position in the distribution of measurements for that particular item-unit pair. The most basic approach is to classify observations that fall below the 33rd percentile as small, between the 33rd and 66th percentile as medium, and above the 66th percentile as large. However, the number of sizes must be considered before applying this method. Some units may only be found in two relatively uniform sizes, in which case only small and large size should be assigned. If possible, a review of the photos is arguably a more compre-hensive approach, or at least a verification step, to solving this problem.

For some items, the additional component of condition will also need to be taken into consideration when calculat-ing conversion factors. In most of these cases, conversion factors should be applied not only for converting to kilogram amounts, but also to render the quantities comparable to each other. For example, maize/corn can be harvested on the cob (usually fresh) or without the cob in grain form (usually dry). The kilogram conversion reported for fresh, on the cob maize is not directly comparable with the kilogram results of dry maize grains. To compare all reported maize conditions with each other, the conversion between maize on the cob and maize dry kernels/grains is also needed.3

Once cleaned, the measurements must be aggregated to an appropriate level. The mean or median measurement for each container unit can be used. For non-containers, the con-version factor will be item specific and should correspond to the reference photo included in the library. If there is signifi-cant regional variation, then regional-level conversion factors should be given. Otherwise, national conversion factors are adequate. The conversion-factor database should be orga-nized so that there is a single conversion factor for each item-unit at the appropriate geographic level, though there may be some item-units not found in a particular region. Therefore, we recommend that national-level conversion factors also be provided even if there is significant regional variation. Figure 6 presents a subset of the conversion-factor library for Nigeria. In the figure, conversion factors are provided for the six geo-political zones as well as the national average.

3 The appropriate adjustment factors for this exercise are not part of the original set of libraries found in Annex 11, but could be considered in future conversion libraries and methodological research.


3.4 COLLECTING REFERENCE PHOTOSThe second element that must be collected during the mar-ket survey is a set of non-standard unit reference photos. After the market survey, all photos should be compiled and included in the library. This index should contain photos of all allowable item-unit combinations, with each one directly linked to the measurements used in the conversion-factor list. For example, the pieces of yam in a photo should be exactly the same pieces used to calculate the conversion

factors as described above, and something in the naming scheme of the photos should make this connection clear. This index of photos will be used to prepare the photo ref-erence album.

WHICH ITEM-UNITS REQUIRE PHOTOS?Ideally, each item-unit included in the survey (including pre-packed foods) will have a reference photo. Practically, surveys

Figure 6 — Excerpt from a Conversion Factor Library for Nigeria

NIGERIA GHS-PANEL WAVE 3CONVERSION FACTORS

ITEMCODE

ITEMNAME

UNITCODE

UNIT DESCRIPTION

UNIT SIZE

CONVERSION FACTOR (KG)

NATIONALAVERAGE

BY ZONE

NORTHCENTRAL

NORTH EAST

NORTH WEST

SOUTH EAST

SOUTH SOUTH

SOUTH WEST

GRAINS AND FLOURS

10 GUINEA CORN/

SORGHUM

11 Paint rubber 3.612 3.758 3.612 3.612 3.768 3.832 2.828

12 Milk cup 0.161 0.205 0.125 0.163 0.180 0.161 0.159

13 Cigarette cup 0.205 0.205 0.205 0.205 0.215 0.198 0.205

14 Tin 14.738 15.510 14.738 14.738 13.965 14.738 14.738

20 Congo Small 1.000 1.280 1.000 1.000 1.000 1.000 .720

21 Congo Large 1.978 1.978 1.978 1.978 1.978 1.978 1.978

30 Mudu Small 1.073 .978 1.103 1.145 1.073 1.060 1.073

31 Mudu Large 1.353 1.368 1.248 1.445 1.353 1.353 1.353

40 Derica Small 0.238 0.238 0.238 0.238 0.238 0.138 0.338

41 Derica Medium 0.639 0.639 0.612 0.639 0.639 0.639 0.745

42 Derica Large 1.587 1.587 1.587 1.587 1.813 1.587 1.361

43 Derica Very large 1.889 1.889 1.889 1.880 1.890 1.870 1.925

51 Tiya Medium 1.825 1.825 1.825 1.825 1.825 1.825 1.825

52 Tiya Large 2.650 2.650 2.650 2.650 2.650 2.650 2.650

60 Kobiowu Small 0.595 0.595 0.595 0.595 0.595 0.595 0.595

61 Kobiowu Medium 1.110 1.110 1.110 1.110 1.110 1.110 1.110

62 Kobiowu Large 1.210 1.210 1.210 1.210 1.210 1.210 1.210

11 MILLET 11 Paint rubber 3.765 3.672 3.765 3.765 3.767 3.805 3.840

12 Milk cup 0.153 0.153 0.145 0.165 0.150 0.153 0.155

13 Cigarette cup 0.210 0.210 0.210 0.210 0.215 0.205 0.210

14 Tin 15.060 15.685 15.060 15.060 14.435 15.060 15.060

20 Congo Small 0.924 1.160 0.924 0.924 0.924 0.924 0.688

21 Congo Large 1.437 1.437 1.437 1.437 1.437 1.437 1.437

30 Mudu Small 0,988 0,893 1,058 1,135 0,988 0,988 0,988

31 Mudu Large 1,260 1,260 1,210 1,323 1,260 1,170 1,260

40 Derica Small 0,243 0,243 0,243 0,243 0,243 0,145 0,340



may wish to limit the photo book to items that represent a significant portion of the total food consumed or total food expenditures. It is essential that separate item-unit pho-tos be taken for each non-container unit such as pieces or heaps. However, for container units (pails, plates, etc.), a single photo for each container may be sufficient since the volume of the container does not vary with the item it holds. Item-specific photos of containers are useful if the fill level (heaped/level) varies significantly across each item. If units are expected to differ by region (e.g., only the North uses baskets, or the object called a pail in the West is different from the pail used in the East) then different photos must be taken in each region as well. However, for units that are relatively uniform across the survey area, only one photo need be taken.

GUIDELINES FOR REFERENCE PHOTOSThe primary purpose of these photos is to compile a ref-erence album for use during household survey data collec-tion. With this tool, respondents can estimate quantities in relation to the related reference size. For example, when shown a reference photo of a potato during the household survey, a respondent can say she ate three potatoes of the size shown, or consumed one potato that was about half the size of the reference potato. Additionally, the photos serve an internal purpose in the creation of the conversion factors, as they can be used for verification/validation of weight mea-surements collected by the market team. The photo quality, while important for both applications, is far more critical for

the reference album that will be shared with respondents. When enumerators are instructed to take photos of all mea-surements, the research team will have multiple pictures to choose from when compiling the photo reference guide.

For the reference photos to be useful, they must depict the referenced quantities in a way that can be easily under-stood and interpreted by survey respondents. Regardless of the enumerators’ general familiarity with taking photos, ample time should be allotted for training enumerators on the photo requirements for this exercise. Effective and eas-ily interpreted reference photos should adhere to these guidelines:

• Photos should be well lit so that respondents can easily see the items and differentiate between the item and its shadow or background.

• When possible, a plain background should be used for each photo. This could be a piece of paper, a sheet, or some other material. The plain background will serve to better highlight the item, especially when its color con-trasts with the item color.

• Each photo should contain only one food item or one food unit. For example, a photo of shelled groundnuts should not include unshelled groundnuts or maize; a picture of pails (a unit used for various items) should not include bunches or piles of a particular food.

• For units that come in various sizes (e.g., small, medium, large), all sizes of the item-unit must be present in the

Figure 7 — Correctly Photographed Sahins of Rapeseed

The near horizontal side angle shows the containers are filled in a "heaped" style, allowing for better understanding of the volume.



same photo to help respondents differentiate between sizes. The items should always be in the same size order (i.e., left to right, ordered from small to large) in the picture. However, some units may be too large to include the size variations in a single photo. For such units, spe-cial care must be taken to ensure that the photos of the different sizes are directly comparable – this means that they are taken from the same angle and same distance

and include the exact same reference item (positioned the same way relative to each item-unit).

• A size reference item must be included in the picture to illustrate the relative size of the main objects. The item should be something that generally comes in one standard size, is easily identifiable to respondents, and could be brought to interviews by enumerators. Exam-

Figure 8 — Correctly Photographed Tasas of Sunflower Seeds

Figure 9 — Correctly Photographed Heaps (Medebs) of Papaya

Plain white background contrasts nicely with the items pictured.

Reference item is included. It is placed next to item for easy com-parison, and is an appropriate size given the size of the item-unit.

Photo taken from the side angle shows the items stacked underneath, helps in under-standing the volume of the heap.




Figure 10 — Correctly Photographed Empty Pails (to be used as unit reference for multiple items)

Photo includes only one reference unit to avoid confusion for respondent.

To reduce enumerator error in recording responses, items are pictured in order (small, medium, large), which is done consistently across all photos.

ples include a water or soda bottle, a writing pen, a box of matches, etc. This is a critical component of the photo. Without it, respondents may not be able to accurately judge the size of the item-unit in the photo.

• The dimension or volume of the item-unit must be clear. Usually this means taking the picture from a side angle, either directly horizontal to the item, or slightly above horizontal. For some non-container units such as pieces, aerial photos (taken from directly above) may be accept-able or sometimes preferred. The key is to ensure that the volume of the item is conveyed in the photo.

Several example photos are shown in this section. Figures 7 through 10 (above) are examples of photos that follow these guidelines. Each photo has a reference object (a soda bottle in this case), a plain background, sizes shown in the appropriate order, and all taken from an angle that allows respondents to accurately gauge the size/volume of the unit.

Figures 11 through 14 are examples of photos that were not taken correctly and will be difficult for respondents to interpret. Figure 11 shows a direct overhead view, whereby the volume of the container cannot be accurately gauged. The photo could be of a shallow plate or a very deep

bucket, but it is impossible to tell from the photo. The item is also not photographed in its original container, which makes it more difficult to understand the volume.

Figure 12 features three different sizes, but the direct over-head angle may be misleading for piles of vegetables. Does the large pile have only the five pieces shown, or are there more stacked underneath? How many pieces are really in the medium pile? There is also no reference item, so it is impossi-ble to tell if the small items are the size of golf balls or tennis balls. Finally, the items are in reverse order (large to small); assuming the other photos and the questionnaire list/label units from small to large (as is most commonly done), then photos that do not follow this pattern will increase the likeli-hood of enumerators incorrectly recording (transposing) the unit size of the item shown during data collection.

In Figure 13, all three sizes are included, as is a reference item. However, the background adds a lot of unnecessary dis-traction. And the inclusion of onions in the photo may confuse respondents.

In Figure 14, the items are also in reverse order. More prob-lematic, though, is that the small basket (on the right) was pho-tographed separately using different backgrounds, angles, and



Photographed in a different container. Since the mudu is not in the picture, it loses context for respondents.

Figure 11 — Incorrectly Photographed Mudu of Gari

Figure 12 — Incorrectly Photographed Heaps of Sweet Potato

Shallow pan or deep bucket? Overhead view makes it impossible to related volume.

The background color is not ideal—the item blends into the background.

A reference item is missing; it is unclear if this sweet potato is longer or shorter than a common pen, for example.

Photo is large-to-small; if all the others are small-to-large, this may lead to mix-ing up small and large codes in responses.



White Gari One Mudu 1.25kg

Sweet Potatoes (heap) 3.57kg 2.23kg 1.0kg


Figure 13 — Incorrectly Photographed Heaps of Green Peppers

Figure 14 — Incorrectly Photographed BasketsTwo different pictures are joined together, each taken from a different angle and distance. This makes it harder to relate the size of objects in the different pictures.

Not clear which basket is small, which is medium, which is large.

The items in the background are very distracting. Photos should focus on only the item in question, to avoid confusion.




distances from the camera for both the basket itself, as well as for the basket in relation to the reference item. All these details make the small basket in the photo visually similar (or greater) in appearance than the medium basket. This is not a useful ref-erence for a respondent and will compromise the accuracy of the data reported.

To comply with the guidelines discussed above, survey teams will often need to have access to a large staging area in which to take photos, especially for larger units or when more than one size of a unit is photographed at once. In compact or crowded markets, this can be a significant challenge. Enumerators may not have enough space to position the camera sufficiently far away to capture all elements in the photo. Similarly, enumera-tors may block passages in the market when taking the photos. This can cause disruption in the market and create animosity from vendors or market patrons. If the market is crowded or very compact, enumerators should try to find a staging area where they can take photos without much difficulty or distur-bance. They should then attempt to collect as many measure-ments from vendors near the photo staging area.

CREATING AND USING THE PHOTO REFERENCE ALBUMPhotos collected from the market survey should be scru-tinized. The best photo should be selected for each item-unit combination for inclusion in the bank of reference photos. This reference tool will be used to establish a clear connection between the respondent’s reporting and the established con-version-factor database. If the size of the reference album must be limited, focus on the most commonly reported NSUs. Ref-erence aides should be printed in color, using a durable material that will withstand fieldwork (such as cardstock, or laminated paper), or should be shown on tablets if the survey is conducted using computer-assisted personal interview (CAPI) technology. The list of reference photos should be organized to match the survey sequence and thus facilitate its use in the field. Forcing enumerators to flip through a multitude of pages of photos to find a particular item or unit will waste time and result in frustra-tion on the part of both the enumerator and the respondent. Both CAPI and paper-based surveys can benefit from printed photo ref-erence albums, which can sometimes be more easily shared with respondents during an interview.

When administering the consumption or agricultural produc-tion questionnaire, the enumerator should allow the respondent to report quantities in the unit with which the respondent is most familiar. The enumerator should not provide the respondent with

the list of allowable item-unit combinations, but should instead refer to the list to ensure that the item-unit provided by the respondent is indeed valid. If the unit the respondent gives is not listed, then the enumerator should use his or her judgement regarding its validity. After the respondent has specified the quantity in the preferred unit, the enumerator should check to see if there is a reference photo for the item-unit. If there is, the enumerator should show the photo to the respondent and verify that the pictured unit is similar to that referred to by the respondent. If applicable, the enumer-ator should also ask which size of the unit most closely matches. The respondent may need to re-estimate his or her consumption/production in terms of the reference photo.

3.5 HOW TO USE THE NON-STANDARD UNITS LIBRARIESOnce all the necessary components are assembled into the NSU library, protocols should be drafted to provide guidance to both enumerators and data users on how use the library. Clear pro-tocols for using NSUs and reference photos must be provided to field teams for the primary household and agriculture sur-veys. Likewise, clear protocols for using the conversion factors must be provided to data users. Each NSU library should include clear, coherent, and concise documentation so that the libraries can easily be used by researchers and field teams. Incorporation of NSU materials into household and agriculture surveys will require additional preparation, which can be done by the house-hold survey team or as a final step in completing part of the NSU library documentation, in which case each household survey team will need to evaluate the available materials in order to adapt them to its needs. This preparation includes revising the consumption (and when applicable, harvest) questionnaire sec-tions to include NSUs and crop conditions; preparing the photo reference guides to be used by teams; and providing instructions to enumerators on how to effectively incorporate these new resources. Annex I contains examples of documents used to incorporate NSUs into the Ethiopian Socioeconomic Survey: the food consumption section of the household survey, including a code sheet for reporting NSUs; a photo reference guide to be printed, bound, and used by enumerators during their interviews; and a sam-ple section of an enumerator training manual that provides instruc-tion to enumerators on the use of the questionnaire and the photo reference guide. A snapshot of the Ethiopia consumption question-naire that incorporates NSUs is shown in Figure 15.

The LSMS team has created conversion-factor libraries for Nigeria, Ethiopia, Malawi, and Uganda, with more planned for Tanzania, Niger, Mali, and Burkina Faso. They are provided


online in Annex II as they were used to support LSMS data-collection efforts in each country. The process of com-piling these libraries has made it possible to further refine the guidelines and best practices outlined herein.

Although some of these libraries may not have the complete set of recommended items or may have some photos that do not meet all the stated recommendations, they can still serve as valu-able resources. Both partial and completed libraries can be used by researchers and fieldwork teams to help increase the accuracy of reported quantities in their own work, without incurring the significant time-cost burden required to establish a new set of con-version factors. Even so, the libraries should be considered living documents, to be revised and updated with each new data-collec-tion effort. Available foods and commonly used units and quantities may vary over time, so even complete libraries should be reviewed and piloted prior to their use on a new project.

Researchers conducting their own fieldwork can begin by includ-ing the existing lists of allowable item-unit pairs into consumption and production questionnaires, training enumerators on the proper use of photo reference aides, and incorporating the provided data-set of NSU conversion factors into interview and data entry checks. When possible, research teams should do a brief pilot test of the commonly-available NSUs in their survey area, as these may change over time or vary across regions; conversion-factor data and pho-tos would only need to be collected for any newly available combi-nations. For research projects focused on analysis of existing data, where that data allowed for NSU reporting but conversion factors may not be available, the LSMS libraries can help increase the num-ber of usable observations. Annex II provides additional information and user instructions on each of the available libraries.

Figure 15 — Excerpt of a Household Survey Allowing for NSU Reporting

CONSUMPTION UNITS

UNIT SIZE UNIT CODE

Kilogram 1

Gram 2

Litres 4

Centilitres 5

Jog 8

Melekiya 9

Birchiko Small 31

Birchiko Medium 32

Birchiko Large 33

Esir Small 61

Esir Medium 62

Esir Large 63

Festal Small 71

Festal Medium 72

Festal Large 73

CEREALS

1 Teff

2 Wheat

3 Barley

4 Maize

5 Sorghum

SECTION 5A: FOOD LAST 7 DAYS

FOOD

ID

1. 2. 3.Over the past one week (7 days), did you or others in your household consume any [ITEM]?

INCLUDE FOOD BOTH EATEN COMMUNAL-LY IN THE HOUSEHOLD AND THAT EATEN SEPERATELY BY INDIVIDUAL HOUSEHOLD MEMBERS

YES...1 NO...2 NEXT ITEM

How much in total did your household

consume in the past week?

SEE UNIT CODES ABOVE

How much came from purchases?

IF NONE

RECORD 0

SEE UNIT CODES ABOVE

QUAN-TITY

UNIT CODE

QUAN-TITY

UNIT CODE


25

4. Benefits of Using Computer-Assisted Personal Interviewing (CAPI)

Materials collected to support the use of NSUs can be used with both paper-based and computer-based surveys. However, some aspects of the information collected for use with NSUs can be greatly enhanced when used with computer-assisted personal interviewing (CAPI). CAPI provides unique benefits when conducting a market survey, particularly with respect to the ability to directly link weight measurements with reference photos. When conducting the main food consumption or agricultural production survey, CAPI can make better use of collected reference photos as well as conversion factors (to identify outliers). Both these aspects are discussed in turn here.

4.1 CAPI FOR MARKET SURVEYSMarket surveys are ideal candidates for collection using com-puter-assisted personal interview (CAPI) technology. Per-haps the strongest advantage that CAPI collection has over paper is that photos can be directly linked to measurements. When conducting a market survey using paper, one must ensure that the photos can be linked to the correct weight measurement observation. One way to ensure this link is to apply a rigorous naming scheme for the photos, referenc-ing the item-unit, the market in which it was taken, and the measurement observation it refers to (if there are multi-ple measurements within the same market). Renaming these photos while conducting the survey can be time consuming for enumerators and can lead to mistakes. However, when using CAPI software (such as Survey Solutions), photos can be taken immediately after recording the measurement and can be directly linked to that measurement observation. The photo is automatically named with a reference to that spe-cific case. In addition, CAPI software can provide a prompt to enumerators to take a photo of the measured item. This can help ensure that there is at least one photo taken for every item-unit measurement collected.

In addition, CAPI technology also makes the collection of additional metadata much easier. For example, GPS

coordinates where each specific measurement is taken (or at least the more general market location) can be automatically captured by the CAPI device. Likewise, the date and time the measurement was taken can also be automatically recorded.

Collection using CAPI also allows for on-the-fly consis-tency checks. Since relatively few measurements will be taken within a market, it is important to limit the potential for error when collecting weights in standard units. For exam-ple, the current measurement can be compared with previ-ous measurements and flagged if it is significantly different. Likewise, a predetermined reasonable range for a particular item-unit can be applied. These bounds must be made flexible and must only account for the most egregious mismeasure-ments. For example, for very small units, any measurement over X kg would be unreasonable. These kinds of checks can identify some common errors such as reporting weights in grams instead of kilograms.

However, there is at least one potential drawback to using CAPI to conduct a market survey. In some cases, it could be more difficult to move between item-units within the listing on a CAPI survey. While conducting a market survey, the enumerators will not go item-unit by item-unit. Instead, they will move within the market collecting what item-units they see, not necessarily in order. For the CAPI program to be

4. BENEFITS OF USING COMPUTER-ASSISTED PERSONAL INTERVIEWING (CAPI) 26

usable in the market setting, enumerators must be able to move easily between item-units in the list. Survey Solutions CAPI allows for such flexibility; evaluation of other software options should take this into consideration.

4.2 CAPI FOR FOOD CONSUMPTION AND AGRICULTURAL PRODUCTION SURVEYSAll the reference library resources detailed above can be used with both paper-based and computer-assisted per-sonal interviews (CAPI). Several CAPI-based programs have capabilities that allow photo references to be incorporated into the interview, so that an enumerator can share relevant images with the respondent as an item is being discussed. In several cases, programs connect the photo directly to the item-unit combination represented, so that “selecting” the photo automatically defines the conversion factor for the item reported.

The importance of collecting data on allowable item-unit combinations and calculating their conversion factors prior to the start of fieldwork is made even more critical with CAPI. When used with CAPI, these tools can create more dynamic in situ validation checks for enumerator use. Allow-able combinations can be programmed into CAPI, so that only these options can be selected for any given item. The full set of such combinations is usually far more than an enu-merator can be expected to recall during an interview, so

building them into the parameters of the survey reduces the number of invalid observations reported during data collec-tion. By applying conversion factors to data as they are being collected, reporting errors can be flagged and reviewed with respondents at the time of the interview, further reducing the number of invalid observations and eliminating the need for costly follow-up visits. CAPI programs can include checks of each item, including confirmation that price per kilogram and/or total and per capita standard-unit quantities are within reason. Some CAPI programs can also generate checks and reports compiled across multiple items entered, creating a summary list of all crop harvests in kilograms, listed in order of quantities, that enumerators can review with households for on-the-spot validations, ensuring that top-reported crops match farmer’s expectations, for example. When collect-ing data on household consumption, caloric values can be included to generate food-consumption summaries; enumer-ators can review these immediately with household mem-bers, checking, for example, that the average caloric intake of household members is within reason, and that the ranking of foodstuffs by caloric share of diet makes sense.

As with any survey using CAPI, it is worth emphasizing the importance of dedicating sufficient additional time and resources to ensure the CAPI program is well programmed and that all checks and validations are incorporated before fieldwork—and even before training and piloting—begins. This additional up-front time will ensure that interviews run more smoothly, save time, and produce less data errors.

27

5. Conclusion

Food consumption and agricultural production are two of the most important and commonly measured quantities for welfare analysis in low- and middle-income countries. Both are critical inputs into poverty estimates for these countries and agricultural production is essential for estimating farmer productivity. Many strides have been made in improving several aspects of these estimates, but until recently the challenge of converting non-standard (NSUs) has received less attention.

The usual practice has been either to limit households to reporting in standard units or to have enumerators estimate the conversion to a standard unit on an ad-hoc basis, both of which can be very problematic and lead to poor estimates. The use of NSUs can increase the accuracy of reported quantities in food-consumption and agricultural-production surveys. Reliably documented conversion factors for NSUs ensure that data robustness is not reduced by the loss of valid observations.

The objective of this Guidebook has been to provide advice to survey practitioners on incorporating non-stan-dard units into their surveys, along with practical guidance

on how to create a complete NSU library resource for coun-tries where one does not currently exist. In addition, the Annexes to this Guidebook include sample questionnaire instruments as well as resource libraries from the LSMS-ISA project (Nigeria, Ethiopia, Malawi, and Uganda). The librar-ies can be of use when working on any surveys or with any survey data in the selected countries. The Annexes include the allowable item- (and condition-) unit combinations for each of the countries and all photo references collected. The Stata files containing the conversion factors are available at www.worldbank.org/lsms under Publications/Guidebooks.

28

REFERENCESAttanasio, O., & Frayne, C. (2006). Do the poor pay more? Presented at: Eighth BREAD Conference on Development

Economics. Ithaca, New York.

Beegle, K., De Weerdt, J., Friedman, J., & Gibson, J. (2012). Methods of household consumption measurement through surveys: Experimental results from Tanzania. Journal of Development Economics, 98(1), 3-18.

Capéau, B. (1995). Measurement error and functional form: a proposal to estimate prices and conversion rates from the ERHS1994. Mimeo.

Capéau, B., & Dercon, S. (2006). Prices, unit values and local measurement units in rural surveys: an econometric approach with an application to poverty measurement in Ethiopia. Journal of African Economies, 15(2), 181-211.

Casley, D. J. & Kumar, K. (1988). Collection, analysis and use of monitoring and evaluation data. Baltimore, MD: The John Hopkins University Press.

Deaton, A., (1997). The Analysis of Household Surveys: a Microeconometric Approach to Development Policy. Washington D.C. and Baltimore: The World Bank and Johns Hopkins University Press.

Deaton, A., & Dupriez, O. (2011). Spatial price differences within large countries. Manuscript, Princeton University.

Diskin, P. (1997). Agricultural Productivity Indicators Measurement Guide. Food and Nutrition Technical Assistance Project. Washington, DC: US Agency for International Development.

Fermont, A., & Benson, T. (2011). Estimating yield of food crops grown by smallholder farmers. IFPRI Discussion Paper. Washington DC: International Food Policy Research Institute.

Fiedler, J. L., Carletto, C., & Dupriez, O. (2012). Still waiting for Godot? Improving Household Consumption and Expenditures Surveys (HCES) to enable more evidence-based nutrition policies. Food & Nutrition Bulletin, 33(Supplement 2), 242S-251S.

Kormawa, P. & Ogundapo, A.T. (2004) Local weights and measures in Nigeria: A handbook of conversion factors. IITA Monograph. Ibadan, Nigeria: International Institute of Tropical Agriculture.

Murphy, J., Casley, D. J. & Curry, J. J. (1991). Farmers’ Estimations as a Source of Production Data. World Bank Technical Paper 132. Washington, DC: World Bank.

Smith, L. C., & Subandoro, A. (2007). Measuring food security using household expenditure surveys (Vol. 3). IFPRI Technical Guide. Washington DC: International Food Policy Research Institute.

Sud, U.C., Ahmad, T., Gupta, V.K., Chandra, H., Sahoo, P.M., Aditya, K., Singh, M., & Biswas, A. (2016). Research on Improving Methods for Estimating Crop Area, Yield and Production under Mixed, Repeated and Continuous Cropping. Global Strategy: Improving Agricultural and Rural Statistics, Working Paper No. 5. Rome: Food and Agriculture Organization of the United Nations.

ANNEX 1 SURVEY INSTRUMENTS

NSU MARKET SURVEY: QUESTIONNAIRE (NIGERIA)

NSU MARKET SURVEY: MANUAL (NIGERIA)

HOUSEHOLD SURVEY: REFERENCE PHOTO ALBUM (ETHIOPIA)

HOUSEHOLD SURVEY: CONSUMPTION MODULE (WITH NSUs)

HOUSEHOLD SURVEY: TRAINING MANUAL (EXCERPT)

* Additional examples available online

29

NSU

MA

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4

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(on

the

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Mill

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Rice

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port

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8,9

Gar

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Plan

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Cass

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egg/

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aste

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17

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helle

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sh (h

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6

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r nut

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d (h

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26,2

7

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nut

27

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on s

eeds

27,2

8

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NTE

NTS

ITEM

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Obg

onno

(gro

und)

28,2

9

Ogb

onno

(ung

roun

d)29

,30

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nut

30

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on p

ea30

Pum

pkin

, see

d30

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bea

ns31

,32

Whi

te b

eans

32,3

3

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ado

33

Bana

na33

Date

pal

m (d

eben

u)33

Man

go33

,34

Mel

on34

Ora

nge

34

Paw

paw

34,3

5

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ot35

Cucu

mbe

r35

Gar

den

egg/

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lant

35,3

6

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lic36

Okr

a - d

ried

36

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a - f

resh

36,3

7

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on37

Pepp

er37

,38

Pepp

er (g

roun

d)38

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er (r

odo)

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ied

38,3

9

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er (r

odo)

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sh39

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er (t

atas

he) -

drie

d39

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er (t

atas

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fres

h39

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tain

s, fre

sh40

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tain

s, dr

ied

40

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pkin

, fru

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,41

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ato

41

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fufu

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ooke

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uits

42

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42

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ze p

aste

42

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NTE

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E

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hum

pas

t42

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ato

pure

e (c

anne

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sh (k

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4

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r44

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ans

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ME.

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.

NSU MARKET SURVEY: MANUAL (NIGERIA)

Living Standards Measurement Study- Integrated Surveys on Agriculture (LSMS-ISA): NON STANDARD UNITS MARKETS

SURVEY

National Bureau of Statistics

Manual for Interviewers and Monitors

15/06/2015

Contents1. Introduction ................................................................................................................................................ 32. The field officers role ................................................................................................................................... 32.1. Enumerators ............................................................................................................................................. 32.2. Monitors .................................................................................................................................................. 43. Understanding the Survey Questionnaire ....................................................................................................... 43.1.Suggested States for Market Survey ............................................................................................................ 43.2.Administering the Market Survey ................................................................................................................ 63.3.Survey instrument administration ............................................................................................................... 63.4.DESCRIPTION FOR MARKET SURVEY QUESTIONNAIRE ................................................................................... 84.Use of tablets and troubleshooting ............................................................................................................... 15GENERAL NOTE ........................................................................................................................................ 15

1. IntroductionIn developing countries like Nigeria there are several nonstandard units (NSUs) which are used to quantify the amount of various items. These nonstandard units are mostly common in rural areas where they are used to measure the amount of land and commodities which are usually consumables. Studies that are aimed to analyze household welfare are mainly based on household survey data particularly on household expenditure data. Information on household expenditure is important to analyze living standard, cost of living, level of poverty and consumer behavior which allow to crate appropriate polices (Disney et al., 2001). Majority of surveys in developed countries use price information to measure the welfare of household which means income or expenditures are stated in monetary units. However, most surveys in Nigeria (see e.g. the Nigerian General Household Survey (GHS)) use quantities to measure expenditure and these quantities are mainly reported in NSUs. Any analysis using these quantities requires the conversion of the NSUs in to standard units and such conversion is not straightforward. Previous experience shows that communities use variety of units and these are often not easily comparable across communities or easily expressed in to standard units. Also, in some cases local units with similar name found to differ in size.

Establishing accurate conversion units is thus vital to produce valid measures thereby ensuring the quality of studies based on the measures and, conclusions and inferences made from the findings of the studies. World Bank has announced to conduct a market survey to establish accurate measurement of NSUs for the various crops and food items which are available in the GHS data. NBS therefore takes interest in conducting this survey assuring the effectiveness of the work given its vast experience in undertaking large scale surveys.This survey aims at collecting market data for non-standard measurement from all six geopolitical zones (NC, NE, NW, SS, SW, SE). The survey plans to visit approximately 12 states and 24 market places throughout the country. In each place, items with non-standard measurement, including food production items-in open market places-and consumption food items-in household, are measured in kilogram.

2. The field officers role

2.1. EnumeratorsThe enumerators are expected to complete the main market place and household questionnaire and using laptops/tablets. The instructions and troubleshooting tips working with computer assisted personal interview (CAPI) are given in part 4 of this manual. The way you act will affect the accuracy of the information that you collect, as well as public perception of this exercise. Be willing to listen, be patient, polite, positive and friendly. Introduce the survey in a way that encourages the respondent: The introduction to the interview gives the respondent an idea of what the study is all about and why they should give up their time to participate. You will also have a letter to show that you are working for NBS and its collaborators.

In general, as an enumerator, you need to: · be patient and tactful when interviewing household members in order to win their cooperation and trust;· ensure interviewed households and or vendors of items to be measured complete confidentiality of all collected data: If the

respondent hesitates about answering the questions, or asks what the information will be used for, repeat that the information will be kept completely confidential.

· follow the instructions established during enumerators’ training;· know the content of the survey manual;· follow the instructions given by the team supervisor;· identify the required food items from the recognized market place and household

· identify the kind of non-standard measurements used for the identified item · measure each item at least two times in kilogram· take a picture for all measured items· record the GPS address of each market places

2.2. MonitorsThe Monitor will

· Contact with appropriate zonal and state level government offices and identify local potential assistance persons in each market place that can facilitate the process of identifying the intended items and the corresponding non-standard measurements.

· Keep communicating with the zonal coordinators and the data manger

· Ensure that the logistics are done appropriately to facilitate the movement of the interviewers

· In collaboration with the core survey team, training of enumerators before the survey

· Ensure the questionnaire has been filled appropriately

3. Understanding the Survey Questionnaire The questionnaire is designed aiming to capture and measure with standard unit measurement for all production and consumption foods used in specific states and markets.

3.1.Suggested States for Market SurveyKwara, Benue, Gombe, Bauchi, Kano, Kebbi, Enugu, Ebonyi, Delta, Rivers, Ondo and Lagos

Table 1. States and markets

LIST OF MARKETS

S/NO STATE URBAN RURAL

1 GOMBE CENTRAL MARKET KWA DOM MAIN MARKET

2 ONDO OJA - OBA OKE-IGBO

3 KWARA OFFA MARKET AJASE IPO

4 DELTA OGBE OGONOGO ISSELE- AZAGBA MARKET

5 BAUCHI MUDA LAWAL MARKET BAYARA

6 KANO RIMI MARKET BADUME

7 BENUE MAKURDI MARKET WANNUNE

8 EBONYI ABAKPA IBOKO

9 LAGOS MILE 12 AIYETORO

10 ENUGU ARIA ORIRE UGWOGO

11 RIVERS NKPOLU MILE 3 MBIAMA

12 KEBBI BIRIN KEBBI MARKET MIAMA

3.2.Administering the Market Survey

This survey involves three major activities

1. Identifying and measuring nonstandard units as well as completing the survey instrument. 2. Taking pictures of the measured item-units3. Taking GPS coordinates of the market center

3.3.Survey instrument administration

This subsection gives you important information on the instruments, how to administer the questionnaire, how to deal with the market survey respondents, etc.

Before you go to a selected market, you should ensure that you are ready to start the market survey data collection. That is make sure that you have all the necessary equipment such as, CAPI notebooks, GPS phone, Weighing scales, paper questionnaires and pen. Moreover,

Make sure that you have the correct location (zone, state) and Market identification code of the selected market center. You will start completing module A (cover page of the instrument) and this section will be completed by the field officer. All Questions of Module A will be completed by the field officer without asking any respondent. You may encounter some unusual cases during the data collection. If you encounter a different or unusual case in a particular section or sections for a market and are not sure what to do, write all of the details down on the computer/questionnaire or in your notebook. Obtain as much information as possible to enable you to complete the questionnaire efficiently when you leave the market. After collecting data from the market, check this manual for guidance. If the solution cannot be found in this manual, you should consult your Field Monitor.

Your Interactions with the Local administrators and Community: As you will be working intensively for few days in the city/ town with community members in carrying out the survey, it is vital that you establish a good working relationship with local administrators as well as Vendors in the market center.

Your work is not to be secretive. Please explain what it is you are doing to all community members and local administrators who ask about your activities. You should be respectful, courteous, and patient with everyone in the locality/ market center. The quality of your work is to a large degree dependent on the level of cooperation you receive from the local administrators, members of the communities in which the market is located.

Getting support letter from regional and local administrators: You must always have a clearance letter from the state administrators and village heads. This must be done before you start to collect any data or reach to the market centers. Since the market centers are located in local government areas getting clearance will not take much time.

3.4.DESCRIPTION FOR MARKET SURVEY QUESTIONNAIRE

This subsection will provide you brief description of the market survey questionnaire. The sections in the Household questionnaire are organized as follows:

· MODULE A: MARKET IDENTIFICATION· MODULE B: ITEM UNIT MEASUREMENT· MODULE C: OTHER ITEM UNIT MEASUREMENT

General Notes: There are two groups of items in this questionnaire. One is for container units and the second group is non container nonstandard units. The weight and price of container units will be collected from each market and from two vendors in each market. Non Container unit will be collected once in each zone. Please also note the following points during the data collection:

· If some of the non-containers are not available in the market please create the units yourself. For example if you cannot find three sizes of sweet potato heap. That is if only one heap is available in the market, please create the other two and make them big medium and small heaps. That is, the market heap will be small heap and twice of the market heap will be medium and three times of the market heap will be large.

· For all items will be collected from each market and from two vendors. · In the market you might find a variety of sizes of containers. For instance you might find 10 different sizes of sack. In such

cases please use the container that is commonly used by the farmers or by the local community. You might purchase these containers and ask the vendor to give you item filled in with similar size of containers.

Module A: Market Identification: this section mainly aimed to collect information about the location of the market, staff detail and interview details. This section is mainly completed by the field officer without asking any respondent. Both are identification and names of field staffs are coded in the CAPI and field officers are supposed to complete this section before they have started any market data collection.

Q0 Market Identification number: each market will have a unique identifier to be assigned by your field monitors so please enter/record market id in the space provide

Q1-Q3. These questions are mainly focused on area identification of the market survey. Enter/record the name and the area code of the zone/state/LGA of the selected market center. These codes are also preceded in the CAPI and select the correct code from the option lists

Q4-Q5 Staff details: In this part of the questionnaire, spaces are provided for the field officers and field monitors involved in this field work activities. Names of all field staffs are pre-coded in the CAPI.

Q6-7 date and time of interview: there is a space provide for date and time of interview in the CAPI. However this section will be automatically filled in by the CAPI from the machine time and date. Hence please make sure that the date and time of your machine is properly working. Please also remember that this question is protected and don’t try to change and modify these questions

Q8 - 9. GPS Coordinates: Record the GPS coordinates (latitude and longitude) of the selected market center. GPS coordinates will be taken form the center of the market not from corners of the market. Please also refer to the section that explains on how to use GPS devices.

Module B: Item Unit Measurement

Q1-Q2 ITEM CODE AND ITEM NAME: Both item code and item name are pre filled in or prepopulated in the CAPI and there is no need to record codes and names for these questions

Q3 UNIT NAME: All local unit names for each item type is also prefilled in or prepopulated in the CAPI and there is no need to record names for this question

Q4 SIZE: All the size options for the nonstandard units are also prefilled in the CAPI and there is no need to be completed by the field officer.

Q5 WAS ITEM MEASURED? Record if the item local unit combination is measured. If the item is measured record Yes (1) if the item is not recorded Record No (2)

Q6 Why was item not measured?: If the answer for Q5 is no record the reason why the item is not measured in the space provided and skip to the next item

Q7a and Q8a Item Sample Weight #1 and Item Sample Weight #2: if the answer for Q5 is yes record the weighing result of each item in the space provided. Each item will be measured twice and the first result is recorded in Q7a and second result is recorded in Q8a. Please see the measuring procedures and instruction below

Q7b and Q8b Price for Item Sample Weight #1 and Price for Item Sample Weight #2: if the answer for Q5 is yes record the price for the measured item in the space provided. The price of each item measured will be recorded twice from two different vendors. Price from vendor 1 will be recorded in Q7b and price from vendor 2 will be recorded in Q8b.

NOTE: Please note that for each item and unit combination two weights will be taken from two different vendors. Therefore weight 1 (weight from Vendor 1) and price of weight 1 (price from Vendor 1) will be recorded in Q7a and 7b respectively. Weight 2 (weight from Vendor 2) and price of weight 2 (price from Vendor 2) will be recorded in Q8a and 8b respectively

Q9: Which type of scale was used? : Record the type of scale used to measure each listed items in the space provided

MODULE C: OTHER ITEM UNIT MEASUREMENT Module C (Other item unit measurement) is only to collect nonstandard unit that are not listed in Module B. When we go to the market we could find some local units that are common to measure the list of items in Module B. These new local units/ nonstandard units must be listed in module C. In module B the item name, item code, unit name and size was prefilled but for this module the item name, unit name and size must be completed by the field officer.

Q1 ITEM NAME: Both item code and item name are to be selected from the options provided. The item names and codes are not prefilled and must be completed by the field officer.

Q2 UNIT NAME: Please complete the nonstandard unit that you have found in the market but not in the list.

Q3. SIZE: if the local unit has different sizes please select the different size from the option provided. For example if the local unit has Large, medium, and small sizes you have to select the item three times to be measured using these different sizes.

Q4 WAS ITEM MEASURED? This will not be asked for this module. The field is protected and will be skipped to the weight

Q5 WHY WAS ITEM NOT MEASURED? This will not be asked for this module. The field is protected and will be skipped to the weight

Q6a and Q7a Item Sample Weight #1 and Item Sample Weight #2: record the weighing result of each item in the space provided. Each item will be measured twice and the first result is recorded in Q6a and second result is recorded in Q 7a. Please see the measuring procedures and instruction below

Q6b and Q7b Price for Item Sample Weight #1 and Price for Item Sample Weight #2: record the price for the measured item in the space provided. The price of each item measured will be recorded twice from two different vendors. Price from vendor 1 will be recorded in Q6b and price from vendor 2 will be recorded in Q7b.

NOTE: Please note that for each item and unit combination two weights will be taken from two different vendors. Therefore weight 1 (weight from Vendor 1) and price of weight 1 (price from Vendor 1) will be recorded in Q6a and Q6b respectively. Weight 2 (weight from Vendor 2) and price of weight 2 (price from Vendor 2) will be recorded in Q7a and 7b respectively

Q8: Which type of scale was used? : Record the type of scale used to measure each listed items in the space provided

Selecting Items to Weigh: The two measurements of a given item should be collected from two different vendors. When selecting an item/unit combination to measure in the markets, confirm with the seller that the unit is consistent with your identification.

The order of items listed on the questionnaire does not have to be followed. You may skip around as necessary to complete the market questionnaire most efficiently. If there are any common units you notice are missing from the list, please take the measurement and add the item-unit to Module C.

Availability:When an item is available at a market, you should try to collect as many of the listed unit measurements as possible. Even if an item-unit combination is not for sale at the market, it should still be weighted. All item/unit combinations may not be available in the market.

Weighing Items & Scale Operation:The digital scales used for the market survey are ADAM (LBK SERIES). These are accurate but are not ideal for rough conditions. Great care must be taken when applying them in the field. Keep scales clean and dry.

All weights taken will be recorded in kg.

Note: the maximum weight on the scales is 30 kg. If you suspect the item to exceed this limit break the load into two or more batches and record the sum of the measurements. If a large scale is available for use in the market, you may use this for larger units (fees for use of scale will be provided when necessary). When using the market scales, ensure the scale is calibrated correctly by checking the balance is at “0” with nothing on it. If more than one scale is available, select a scale that has a government certification stamp.

1. Place the scale on a stable flat surface. The scale must be as level as possible before weighing items.2. Press [O / I] to turn the scale on. The Scale will run a brief check and once the scale is stable, the display will show “0.000Kg”.

Note: If the display does not show the weighing unit as Kg then the scale was not configured correctly for the last item/s weighed. Press [UNITS] to select the correct unit (KG) to be used and reweigh previous item if necessary.

Note: Some items may require the use of a container to hold the item on the scale. When a container is used, place the empty container on the scale and wait for a stable reading. Once a stable reading is displayed press [T] button and the display will read “0.000Kg”.

3. Add items to scale, wait for stable reading and record weight displayed.

Unit PhotosIn addition to collecting conversion factors, photos will also be taken of each unit. These photos will serve two purposes: (1) to provide data users with a more accurate perception of what the NSUs actually are (e.g. a basket, cup) and their relative size, and (2) be used in future waves of the GHS to aid in respondents’ estimation of quantities in NSUs. In the latter case, the photos will be particularly useful in standardizing units such as a “bunch” or “heap” that are not clearly defined.

Required photos:Photos are required for every item/unit combination that is measured. Since the photos will be linked to specific measurements, this means we need a photos for each measurement (in every market, for both vendors). However, the different sizes of an item unit can be photographed together. For example the small, medium and large mudu of millet can be in a single photograph.

General guidelines for taking photos:· Photos should be well lit so that the items can be easily seen and you can differentiate between the item and its shadow or

background.· For photos of containers that are commonly used to measure a large number of items, the containers could be photographed

empty or filled with one of the items it is used to measure.· For all photos, the weighed quantity should be photographed. For example, the potatoes used to weigh a heap should be the

exact same potatoes photographed for the heap.· Each photo should contain only one food item or unit.· A size reference item must be in the picture to illustrate the relative size of the main objects. This should be something that

generally comes in one standard size and is easily identifiable to respondents. Example small Eva bottle water (75 CL). .

· The dimension or volume of the item must be clear. Usually this means taking the picture from a side angle, either directly horizontal to the item, or slightly above horizontal. With single items (one tomato, but not a heap of tomatoes) aerial photos (taken from directly above a container, for example) may be fine. Aerial photos of containers or items that are in a heap are generally not useful.

(Please see the sample pictures from Ethiopia for Reference)

Filing and Naming of photoOnly a single photo will be taken for consumption items that are measure using non containers like heap, pieces, bunch, etc. We must take a photo for every container or local units such as sack, mudu, tiya, etc .

The entire photo taken from the market must be filed and named consistently through the survey. The following is the procedure you must follow to file and name the photo taken from each market:

1. For all markets we must have one photo folder. This folder must be named by the name of the market. For example if the market is Gombe central market the folder mast be named as “1501 - Gombe”

2. Each market folder must have two sub folders and must be named as market name and vendor number. For example for KARU market we must have two folders Named “Vendor 1” and “Vendor 2”

3. All the Market folders and subfolders must be created before they go to the market (even before they go to the field).

4. After the folders and subfolders are created all the photos taken from each market must be kept in each subfolder. The photo names must also be consistent throughout the survey. The file name must include market name, item name, local unit, size and vendor number. For example if you have measured and taken a photo from Gombe central market and the item is millet in small mudu from the first vendor then the photo name must be “1501 millet mudu small v1” and the same filing procedure will be made to other items. However, if the photo for all sizes is in one photo then the file name must be “1501 millet mudu v1”

5. The photo for all sizes should be taken together if possible. That is a single photo containing large, medium and small size local units. In some case it could be difficult to find all sizes in one vendor. In such situation you can take different photo for different sizes of the same local/ nonstandard units. But you must indicate the size of the unit in the file name.

6. Please also note that you must take the photo for all items with the items filled in the container. Moreover, you must take one sample empty containers for all sizes in each market.

4.Use of tablets and troubleshooting

GENERAL NOTE1. Make sure that you have the following equipments for the survey.

Note or tablets – Two per team with the following:· bag · External GPS unit

USB Internet Routers (or Dongles) for all Monitors- these are availableField bags – for field officers/monitors to carry their field equipmentManuals – All survey Related Manuals1. Before you start your interview, make sure that the device you are using:

Properly functioning with batteries. Batteries are fully charged.Has correct settings (such as time, date and partitions, etc.).The CAPI instrument has been loaded with all of the right software (such as CSPro software’s, etc.). USB dongles for internet are working properly.

NOTE: 1. Every night batteries should be charged.2. Keep the CAPI Device away from heat.

ቀይ ሽ

ንኩርት

፣መደብ

(Oni

ons:

Med

eb)

ትንሽ

(131

), መ

ካከለኛ

(132

), ት

ልቅ

(133

)

Page

1

በቆሎ

፣ቁጥ

ር(M

aize

: Pie

ces)

ትንሽ

(141

), መ

ካከለኛ

(142

), ት

ልቅ

(143

)

ቃርያ

፣መ

ደብ(G

reen

Chi

li Pe

pper

: Med

eb)

ትንሽ

(131

), መ

ካከለኛ

(132

), ት

ልቅ

(133

)

በርበሬ

፣መ

ደብ(R

ed P

eppe

r: M

edeb

)ት

ንሽ(1

31),

መካከ

ለኛ(1

32),

ትል

ቅ(1

33)

HO

USE

HO

LD S

URV

EY: R

EFER

ENC

E PH

OT

O A

LBU

M

ቲማቲም፣መደብ

(Tom

atoe

s: M

edeb

)ትንሽ

(131

), መካከለኛ

(132

), ትልቅ

(133

)

Page

2

ጎመን፣ቁጥር

(Gre

ens -

Cabb

age:

Pie

ces)

ትንሽ

(141

), መካከለኛ

(142

), ትልቅ

(143

)

ጎመን/ቆስጣ

/ሰላጣ፣አስር

(Gre

ens -

Kale

: Esir

)ትንሽ

(61)

, መካከለኛ

(62)

, ትልቅ

(63)

ሙዝ፣ቁጥር

(Ban

ana:

Pie

ces)

ትንሽ

(141

), መካከለኛ

(142

), ትልቅ

(143

)

ሙዝ፣ዘለላ

(Ban

ana:

Bun

ch)

ትንሽ

(41)

, መካከለኛ

(42)

, ትልቅ

(43)

Page

3

ብርቱካን፣ቁጥር

(Ora

nge:

Pie

ce)

ትንሽ

(141

), መካከለኛ

(142

), ትልቅ

(143

)ብርቱካን፣መደብ

(Ora

nge:

Med

eb)

ትንሽ

(131

), መካከለኛ

(132

), ትልቅ

(133

)

ድንች፣መደብ

(Pot

ato:

Med

eb)

ትንሽ

(131

), መካከለኛ

(132

), ትልቅ

(133

)

ስራስር፣ቁጥር

(Tub

ers:

Pie

ces)

ትንሽ

(141

), መካከለኛ

(142

), ትልቅ

(143

)

ስራስር፣መደብ

(Tub

ers:

Med

eb)

ትንሽ

(131

), መካከለኛ

(132

), ትልቅ

(133

)

ድንች፣ቁጥር

(Pot

ato:

Pie

ce)

ትንሽ

(141

), መካከለኛ

(142

), ትልቅ

(143

)

Page

4

ቆጮ፣መደብ

(Koc

ho: M

edeb

)ትንሽ

(131

), መካከለኛ

(132

), ትልቅ

(133

)

ቡላ፣

አስር

(Che

ese:

Esir

)ት

ንሽ(6

1), መ

ካከለኛ

(62)

, ትል

ቅ(6

3)

ጆግ

(Jog

)

አንድ

መጠ

ን(8

)

መለኪ

ያ(M

elek

iya)

አንድ

መጠ

ን(9

)

ጫት

፣ዞር

ባ /አ

ቃራ

(C

hat:

Zorb

a/Ak

ara)

ትንሽ

(191

), መ

ካከለኛ

(192

), ት

ልቅ

(193

)

ብርጭ

ቆ(B

irchi

ko)

ትንሽ

(31)

, መካከ

ለኛ(3

2), ት

ልቅ

(33)

ፌስታ

ል(F

esta

l)ት

ንሽ(7

1), መ

ካከለኛ

(72)

, ትል

ቅ(7

3)

ቅርጫ

ት/ቀ

ምባ

(Ker

chat

/Kem

ba)

ትንሽ

(91,

ምስሉ

(ፎ

ቶው

) እዚ

ህ የለ

ም),

መካከ

ለኛ(9

2), ት

ልቅ

(93)

ኩባያ

(Kub

aya/

Cup)

ትንሽ

(101

), መ

ካከለኛ

(102

), ት

ልቅ

(103

)

ስኒ (Sin

i)ት

ንሽ(1

71),

ትል

ቅ(1

72)

ሳህን

(Sah

in)

ትንሽ

(151

), መ

ካከለኛ

(152

), ት

ልቅ

(153

)

ጣሳ/

ታኒካ/ሸ

ምበር/ሰ

ለሞን

(Tas

a/Ta

nika

/She

mbe

r/Se

lem

on)

ትንሽ

(181

), መ

ካከለኛ

(182

), ት

ልቅ

(183

)

Page

7

ቁና/

ምሼ

/ቀፈ

ር/አን

ቅብ

(Kun

na/M

ishe

/Kef

er/E

nkib

)ት

ንሽ(1

11),

መካከ

ለኛ(1

12),

ትል

ቅ(1

13)

አቁማ

ዳ /ዳ

ዉላ /ለ

ኮታ

(Aku

mad

a/Da

wla

/Lek

ota)

ት

ንሽ(2

1), ት

ልቅ

(22)

Page

8

ማዳበ

ሪያ/ኑ

ሴ/ሸ

ራ/ጭ

ረት

(Mad

aber

ia/N

use/

Sher

a/Ch

eret

)ት

ንሽ(1

21),

መካከ

ለኛ(1

22),

ትል

ቅ(1

23)

ሳጥን /ካ

ሳ (B

ox/C

asa)

አንድ

መጠ

ን(6

)በዚ

ህ ገፅ

የተ

ጠቀመ

ጡት

መለኪ

ያዎች

ለ ም

ርት አ

ሰባብ

ሰና አ

ጠቃ

ቀም (

post

ha

rves

t) መ

ጠይ

ቅ ነው

።

SECT

ION

5A

: FO

OD

LA

ST 7

DAY

S

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ID

1.2.

3.4.

5.6.

Ove

r th

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st o

ne w

eek

(7 d

ays)

, did

you

or

othe

rs in

you

r ho

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cons

ume

any

[ITEM

]?

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(SPE

CIFY

) ___

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NU

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nuts

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(SPE

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) ___

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SUM

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(W

ITH

NSU

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SECT

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5A

: FO

OD

LA

ST 7

DAY

S (c

ont.

)

FOO

D

ID

1.2.

3.4.

5.6.

Ove

r th

e pa

st o

ne w

eek

(7 d

ays)

, did

you

or

othe

rs in

you

r ho

useh

old

cons

ume

any

[ITEM

]?

INCL

UD

E FO

OD

BO

TH E

ATEN

CO

MM

UN

ALL

Y IN

TH

E H

OU

SE-

HO

LD A

ND

TH

AT E

ATEN

SEP

ARA

TELY

BY

IND

IVID

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USE

-H

OLD

MEM

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.

YES

..1N

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2

NEX

T IT

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How

muc

h in

tot

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id y

our

hous

ehol

d co

nsum

e in

the

pa

st w

eek?

SEE

UN

IT C

OD

ESA

BOVE

How

muc

h ca

me

from

pu

rcha

ses?

IF

NO

NE

RECO

RD 0

.

SEE

UN

IT C

OD

ESA

BOVE

How

muc

h di

d yo

u sp

end?

How

muc

h ca

me

from

ow

n pr

oduc

tion

?

IF N

ON

E R

ECO

RD 0

.

SEE

UN

IT C

OD

ESA

BOVE

How

muc

h ca

me

from

gift

s an

d ot

her

sour

ces?

IF

NO

NE

REC

ORD

0.

SEE

UN

IT C

OD

ESA

BOVE

QUA

NTI

TYU

NIT

CO

DE

QUA

NTI

TYU

NIT

CO

DE

BIRR

QUA

NTI

TYU

NIT

CO

DE

QUA

NTI

TYU

NIT

CO

DE

VEG

ETA

BLES

14O

nion

141

Gre

en c

hili

pepp

er (k

ariy

a)

142

Red

pepp

er (b

erbe

re)

143

Gre

ens

(kal

e, c

abba

ge, e

tc.)

144

Tom

ato

145

Oth

er v

eget

able

(SPE

CIFY

) ___

__

FRU

ITS

15Ba

nana

151

Ora

nge

152

Oth

er fr

uit (

SPEC

IFY)

___

__

TUBE

RS &

STE

MS

16Po

tato

17Ko

cho

26Bu

la

170

Swee

t pot

ato

171

Boye

/Yam

172

Cass

ava

173

God

ere

174

Oth

er tu

ber o

r ste

m (S

PECI

FY)_

____

MEA

T, P

OU

LTRY

, & F

ISH

180

Goa

t & m

utto

n m

eat

181

Beef

182

Poul

try

SECT

ION

5A

: FO

OD

LA

ST 7

DAY

S (c

ont.

)

FOO

D

ID

1.2.

3.4.

5.6.

Ove

r th

e pa

st o

ne w

eek

(7 d

ays)

, did

you

or

othe

rs in

you

r ho

useh

old

cons

ume

any

[ITEM

]?

INCL

UD

E FO

OD

BO

TH E

ATEN

CO

MM

UN

ALL

Y IN

TH

E H

OU

SE-

HO

LD A

ND

TH

AT E

ATEN

SEP

ARA

TELY

BY

IND

IVID

UAL

HO

USE

-H

OLD

MEM

BERS

.

YES

..1N

O...

2

NEX

T IT

EM

How

muc

h in

tot

al d

id y

our

hous

ehol

d co

nsum

e in

the

pa

st w

eek?

SEE

UN

IT C

OD

ESA

BOVE

How

muc

h ca

me

from

pu

rcha

ses?

IF

NO

NE

RECO

RD 0

.

SEE

UN

IT C

OD

ESA

BOVE

How

muc

h di

d yo

u sp

end?

How

muc

h ca

me

from

ow

n pr

oduc

tion

?

IF N

ON

E R

ECO

RD 0

.

SEE

UN

IT C

OD

ESA

BOVE

How

muc

h ca

me

from

gift

s an

d ot

her

sour

ces?

IF

NO

NE

REC

ORD

0.

SEE

UN

IT C

OD

ESA

BOVE

QUA

NTI

TYU

NIT

CO

DE

QUA

NTI

TYU

NIT

CO

DE

BIRR

QUA

NTI

TYU

NIT

CO

DE

QUA

NTI

TYU

NIT

CO

DE

183

Fish

OTH

ER

19M

ilk

20Ch

eese

201

Butt

er/g

hee

202

Oils

(pro

cess

ed)

21Eg

gs

22Su

gar

23Sa

lt

BEVE

RAG

ES &

STI

MU

LAN

TS

24Co

ffee

203

Tea

204

Soft

drin

ks/S

oda

205

Beer

206

Tella

25Ch

at /

Kat

OTH

ER P

REPA

RED

FO

OD

195

purc

hase

d In

jera

196

purc

hase

d br

ead/

bisc

uit

197

Past

a/M

acca

roni

198

Oth

er p

urch

ased

pre

pare

d fo

od

CO

NSU

MPT

ION

UN

ITS

UN

ITSI

ZEU

NIT

CO

DE

UN

ITSI

ZEU

NIT

CO

DE

Kilo

gram

1Ku

nna/

Mis

he/K

efer

/Enk

ibSm

all

111

Gra

m2

Kunn

a/M

ishe

/Kef

er/E

nkib

Med

ium

112

Litr

es4

Kunn

a/M

ishe

/Kef

er/E

nkib

Larg

e11

3

Cent

ilitr

es5

Med

ebSm

all

131

Jog

8M

edeb

Med

ium

132

Mel

ekiy

a9

Med

ebLa

rge

133

Birc

hiko

Smal

l31

Piec

e/nu

mbe

rSm

all

141

Birc

hiko

Med

ium

32Pi

ece/

num

ber

Med

ium

142

Birc

hiko

Larg

e33

Piec

e/nu

mbe

rLa

rge

143

Esir

Smal

l61

Sahi

nSm

all

151

Esir

Med

ium

62Sa

hin

Med

ium

152

Esir

Larg

e63

Sahi

nLa

rge

153

Fest

alSm

all

71Si

niSm

all

171

Fest

alM

ediu

m72

Sini

Larg

e17

2

Fest

alLa

rge

73

Tasa

/Tan

ika/

Shem

ber/S

elem

onSm

all

181

Kerc

hat/K

emba

Smal

l91

Tasa

/Tan

ika/

Shem

ber/S

elem

onM

ediu

m18

2

Kerc

hat/K

emba

Med

ium

92Ta

sa/T

anik

a/Sh

embe

r/Sel

emon

Larg

e18

3

Kerc

hat/K

emba

Larg

e93

Zorb

a/Ak

ara

Smal

l19

1

Kuba

ya/C

upSm

all

101

Zorb

a/Ak

ara

Med

ium

192

Kuba

ya/C

upM

ediu

m10

2Zo

rba/

Akar

aLa

rge

193

Kuba

ya/C

upLa

rge

103

Oth

er (S

peci

fy)

900

HOUSEHOLD SURVEY: TRAINING MANUAL (EXCERPT)

SECTION 5A: FOOD OVER THE LAST 7 DAYS

Respondent: Individual primarily responsible for the preparation of food.

Section 5A should be asked of the individual in the household who is primarily responsible for food preparation for the household, with the assistance of other food preparers and the head of household, if applicable.

Section 5A asks questions about the total consumption (quantity) of food items in the past week, which can come from purchases, own-production, and/or gifts.

Section 5A also asks about the monetary value of food items that were consumed over the past one week and that came from purchases. This is important to understand since Section 5A DOES NOT necessarily ask about expenditures on food items that were bought over the past one week.

Example: If in the past week the household purchased a large amount of teff from a wholesaler, DO NOT record the entire value of that purchase. Instead, record the monetary value of the portion of teff that was consumed by the house-hold in the past week.

It is possible that individual household members will have consumed some food over the past one week independently of the other household members. As you are administering Section 5A, you must prompt the respondents from time to time to remind them to consider such individual consumption as they are answering your questions. Often enumera-tors forget the fact that this is not for an individual member or for only the respondent but for the entire household.

Units: You must closely study the units of food consumption included in the questionnaire. The list of available units has been expanded to include the most common non-standard units (ex: medeb, kubaya, zorba, etc) used in Ethiopia when purchasing and consuming food items. Often times, household respondents will be able to recall the amount consumed more accurately if they are allowed to report in the units with which they are most familiar. This will also reduce the amount of calculations required to record the information because the enumerator and respondent are not responsible for converting reported quantities into standard units (kilograms, litres, etc).

Photo Reference Book

Consider that a kilogram is a kilogram regardless of where you are in the world. However, what one person con-siders to be a small orange or a small medeb of tomatoes might be considered by another person to be medium or large. Likewise, a cup or a kerchat used in one market may be a different size than the one used in another market.

Although the addition of non-standard units (NSUs) allows the respondent to more easily and accurately report what they have consumed, we must also make the NSUs as comparable and consistent as possible. To that end, you have been given a Photo Reference Book, which should accompany you on all interviews. When a respondent reports an item consumed and uses NSUs, show them the relevant photo and ask them to identify which pictured item most closely matches the size they are reporting, then use the correct unit code to record this on the questionnaire.

58

The Photo Reference Book contains photos of the NSU combination that are most likely to be reported. Each photo also includes a reference item to help you and the respondent understand the relevant size of the food items. For example, if a photo shows a cabbage but has no reference item, we cannot be sure if the cabbage is the size of a fist or a soccer ball. The reference item – a widely recognized object that comes in a commonly known size – helps you and the respondent understand the true size of the items in the picture. To be most effective, you may need to point out and explain the reference item to the respondent. Some pictures (pages 1 – half of page 5) show NSUs of specific food items and can only be used for those food items indicated in the picture. Note that the photos for tubers, however, should be used for all tubers, and not only the specific one in the photo. The rest of the pictures show various containers that can be used to measure a wide range of goods. These photos should be used for all such items, regardless of what food is pictured in the container. The last page shows containers that are most commonly used for measuring harvested foods, but may also be used for household consumption reporting, especially for large households.

Examples

The respondent reports that the household consumed a lot of potatoes, but she doesn’t know the quantity in kilograms. Show him the photo on page 4 (top, center) and say, “Please take a look at this photo, which shows heaps/piles (medeb) of potatoes. Notice the size of the piles compared to a common water bottle.Which one is closest in size to the amount your household consumed?” The respondent indicates the medium size pile, and tells you they purchased and consumed a pile this size, and also they picked from their yard and ate more, equivalent to about half the size of this pile, nothing was gifted to them. You will use unit code 132 for all questions, and report quantities as follows: Q2=1.5; Q3=1; Q5=0.5; Q6=0

Another household tells you they purchased a small sahin of teff, but only ate half of it in the past 7 days. DO NOT simply record the amount as a small sahin of teff. First, show her the photo on page 7 (top, right). You can point to the small one in the photo and say, “Please take a look at this photo. Notice the size of the containers compared to a common coke bottle. Was the one you purchased similar in size to this small one here?” If she agrees, then you record that unit; if she corrects you to say that her purchase, in fact, was similar to the one in the middle, then record the medium size unit. Remember also that the total amount consumed and reported in Q2 is 0.5 (one half, since that is all they consumed).

Questionnaire

Q1. This question asks whether any member of the household CONSUMED specific foods listed over the past 7 days.

Complete Q1 for all foods before moving to Q2-Q6. Fist, ask Q1 for ALL ITEMS in the list. Then for every food item where Q1=1, ask the rest of the questions one row at a time.

For example: First ask if any member of the household consumed teff in the past 7 days. After recording 1 for yes, or 2 for no, ask if anyone in the household consumed wheat in the past 7 days, and so on….Once you have completed Q1 for every food item, return to the top and ask Q2-Q6, in order, for each item for which the respondent reported consumption in the past 7 days. If the respondent reported con-suming teff and wheat, ask Q2-Q6 for teff before moving on to Q2-Q6 for wheat.

59

If any of the items were given to animals OR were purchased but not consumed OR were given for free but not consumed, they SHOULD NOT be reported as part of household consumption. For instance, if the household just bought a 50 kg bag of rice but has not eaten any of that or any other rice, the response to Q1 should be NO for rice.

Q2. This question asks the quantity of food items that a household has reported to have consumed over the past week. The question has two parts where you need to record: the unit measurement of the food consumed and the quantity of each food item should be recorded.

Quantity consumed: This is a number. If only part of the purchased food was consumed, please ask your re-

spondent to estimate the portion consumed.

The unit codes for the quantity are provided on the back side of the page. If the respondent is more com-fortable reporting a given quantity in a unit not listed here, record this as ‘other, specify’ write the name of the unit and try to make a note of the size/shape of the unit being reported.

For instance, where a household has consumed two (2) kilograms of maize, you need to record 2 in the column for quantity and one (1) in the column for unit.

Q3. This question asks what amount of the total food items consumed and reported in Q2, came from purchases.

For example, of the two kilograms of rice that the household consumed over past one week (recorded in Q2), only one (1) kg may have originated from purchases. In this case, for Q3 you MUST record, one (1) in the quan-tity column and twenty (20 for kg) in the unit column.

Consumption out of business inventory, such as a grocery inventory, MUST be considered as con-sumption originating from purchases and be included in Q3 too.

Q4. This question asks the amount of money that was paid to purchase the food reported in Q3. Note thatQ4 refers ONLY to the monetary value of the consumed food that came from purchases.

Q5. This question seeks to capture the amount of food that was reported to have been consumed (in Q2) that came from own-production (that is, own farm/garden, etc.). Similar to the other questions, both quantity and unit MUST be entered here.

Q6. This question seeks to capture the amount of food that was reported to have been consumed (in Q2) that came from either gifts OR sources other than purchases or own production/assistance.

Q3, Q5, Q6. If Q1=1 but the respondent reports no consumption of an item from a given source (i.e., purchases, own-production, gifts), record ‘0’ in the column for quantity and leave the column for unit blank.

60

ONLINE ANNEX II:LIBRARY OF NONSTANDARD UNIT CONVERSION FACTORS AND REFERENCE PHOTOS

ETHIOPIA: DOCUMENTATION AND REFERENCE PHOTOGRAPHS

MALAWI: DOCUMENTATION AND REFERENCE PHOTOGRAPHS

NIGERIA: DOCUMENTATION AND REFERENCE PHOTOGRAPHS

UGANDA: DOCUMENTATION

* All documents available online at www.worldbank.org/lsms

61

Living Standards Measurement Studywww.worldbank.org/lsms

data.worldbank.org

SELECT LSMS GUIDEBOOKS

Measuring the Role of Livestock in the Household EconomyAlberto Zezza, Ugo Pica-Ciamarra, Harriet K. Mugera, Titus Mwisomba, and Patrick Okell

November 2016

Land Area Measurement in Household SurveysGero Carletto, Sydney Gourlay, Siobhan Murray, and Alberto Zezza

August 2016

Measuring Asset Ownership from a Gender PerspectiveTalip Kilic and Heather Moylan

April 2016

Measuring Conflict Exposure in Micro-Level SurveysTilman Brück, Patricia Justino, Philip Verwimp, and Andrew Tedesco

August 2013

Improving the Measurement and Policy Relevance of Migration Information in Multi-topic Household SurveysAlan de Brauw and Calogero Carletto

May 2012

Design and Implementation of Fishery Modules in Integrated Household Surveys in Developing CountriesChristophe Béné, Asafu D.G. Chijere, Edward H. Allison, Katherine Snyder, and Charles Crissman

May 2012

Agricultural Household Adaptation to Climate Change: Land Management & InvestmentNancy McCarthyDecember 2011

Agricultural Household Adaptation to Climate Change: Water Stress & VariabilitySushenjit Bandyopadhyay, Limin Wang, and Marcus Wijnen

August 2011

Comparative Assessment of Computer-Assisted Personal Interview (CAPI) Software PackagesArthur Shaw, Lena Nguyen, Ulrike Nischan, and Herschel Sy

July 2011

Tracking in Longitudinal Household SurveysFirman Witoelar

July 2011

Surveying Justice: A Practical Guide to Household SurveysKristen Himelein, Nicholas Menzies, and Michael Woolcock

January 2010

the use of non-standard units for the collection of...

Documents