# Improving Cost-Effectiveness and Relevance of Agricultural Censuses in Africa:

# *Linking Population and Agricultural Censuses*

**Naman Keita, Senior Statistician**

**FAO Regional Office for Africa, Ghana**

**Abstract**

Imperfect sampling frames and their negative impact on data quality have
been a major technical issue in many African countries conducting
Agricultural Censuses most of which are on a sample basis, due to the
specific context of traditional subsistence farming systems in place.
The paper is based on experiences of several African countries during
recent years, in adopting some kind of coordination and linkage between
Population and Agricultural Censuses in order to obtain, in a more cost
effective manner, up-to-date and improved sampling frames for use in
Agriculture Censuses and other subsequent surveys.

In addition to providing information for building improved sampling
frames and better sample design, linking the two Censuses offers many
advantages. The agriculture module of the Census of Population provides
complete enumeration of agricultural households (and sometimes
information on rural communities) which allows presentation of data for
small geographical/administrative units, increasing considerably the
value and relevance of the whole census operation. Also as the same
identification of households is used for both censuses there is scope
for in-depth analysis using cross-tabulations of agricultural data with
the socio-economic and demographic data from the Census of Population.

The paper describes two country experiences and summarizes some of the
lessons learned from these and other country experiences during the past
10 years.

## 1. Some features of agricultural censuses in Africa

The Food and Agriculture Organization (FAO) of the United Nations,
defines the Census of Agriculture as ***"**a large-scale, periodic,
statistical operation for the collection of quantitative information on
the structure of Agriculture. The word \"census\" implies a complete
enumeration of all agricultural holdings. However, it can be conducted
by a sample enumeration, provided the sample is large enough to generate
sub-national data**" ***\[FAO, (1995)\].

In most African countries, the agricultural sector is characterized by
the existence of a large number of small subsistence farmers producing
food crops mainly for their own consumption. As area cultivated depends
largely on available manpower, production is done on a number of small
plots sometimes far away from the dwelling of the farmer's family and
not always located at the same place. Most farmers are still illiterate
and do not keep records of area of plots cultivated, yield or
production, and in some places, shifting cultivation is also used.

In this context, some key data related to the structure of agriculture,
like crop area and other important current data like yield and
production cannot be obtained by direct interview of farmers[^1].
Objective and physical measurements are required in order to generate
accurate data. FAO has developed methods of measuring area, using
compasses, tapes and programmable calculators. Crop cutting is used for
estimation of yield and production. However, these methods are very time
consuming and costly[^2] and given the number of small farmers and plots
involved, it is almost an impossible task to conduct a complete
enumeration of all farms during an agricultural census. The situation
may be even more difficult in countries with a large nomadic and
semi-nomadic livestock sector.

This is why, for most African countries, the censuses of agriculture are
being conducted on a sample basis in order to keep cost under an
affordable limit. The effectiveness of the sample used to accurately
represent the statistical universe of farms depends to a large extent on
the quality of sampling frame used and have a considerable implication
on the quality of census results.

Therefore, the availability of an appropriate sampling frame is a key
issue in planning and conducting agricultural censuses in Africa. In
fact some census results were never published because of the use of out
dated and inappropriate sampling frame leading to obvious
mis-representation of the reality.

2\. Sample design and importance of proper sampling frame for
agricultural censuses

As stated above, because of resource limitations and constraints of
traditional farming systems, sample enumeration is the most common
feature of agricultural censuses in Africa. The sample design usually
adopted is stratified two-stage sampling with Primary Sampling Units
(PSU) being the Enumeration Areas (EA) or villages and the Secondary
Sampling Units (SSU) the Agricultural Households which are often used to
identify holdings[^3].

The sampling frame used for the selection of PSUs is usually derived
from the last Population Census data and the selection is done at the
first stage with probability proportional to some indication of size
(pps). In many cases, the population census questionnaire includes
questions to all qualified members of the household about *main
activity* as well as *branch of activity*. When primary census files are
available and accessible, this information is sometimes used to identify
agricultural households when the household head or a household member
has *agriculture* as the main activity. This criteria is used to
determine the number of agricultural households (or the total population
of agricultural households) in the EA which may be used as size
indicator.

However, the limits of this information and the risk of under-estimation
are obvious. In many cases, the last population census is so remote that
the access to basic files is almost impossible and in the absence of
other information the total population of the EA or the total number of
households is used for the size of the EA. In some other cases, PSUs
(EAs or villages) are randomly selected with equal probability. Complete
listing of agricultural households for selected PSUs is then done to
build a frame for second stage selection and SSUs are selected, often a
fix number with equal probability or fixed proportion, depending on the
selection procedure used at first stage.

Depending on the time separating the last population census from the
agricultural census, the frame used for selecting PSUs (EAs or villages)
may be far from corresponding to actual situation regarding boundaries,
composition and size and may be completely out-dated. Villages may have
changed names, disappeared or new villages may have been created. This
imperfection of sampling frames is a major source of over-all
non-sampling error and has a serious impact on the quality of data
generated by agricultural censuses in African countries. This is why
several countries engaged in agricultural censuses in recent years have
attempted to improve the situation in a cost-effective manner through
better coordination of population census and agricultural census
operations.

**3. Coordination between population and agricultural censuses**

Population and agricultural censuses are large scale and very costly
statistical exercises particularly for African countries, most of which
have to rely on donor funding for these operations. Better coordinating
these two major data collection exercises makes it possible to realize
economies of scale as the infrastructure of population census may be
used to collect relevant agricultural data needed for building up-dated
sampling frame for the agricultural census.

The alternative of conducting an ad-hoc exercise for building a sampling
frame for agricultural census will substantially increase the cost of
the agricultural census operation. Experience shows that cost of
agricultural censuses in the African context may vary from 3 millions
dollars to 10 millions dollars (in particular if nomadic livestock is to
be covered). An ad-hoc sample frame building exercise may add more than
20% to the cost of the census.

In the past, attempts of coordination between the two operations met
strong resistance, as population census managers, thought that this
linkage will get their operation out of focus and add a too heavy burden
to the data collection exercise. In recent years however, with
increasing scarcity of resources, several African countries, with advice
of FAO, have adopted some type of coordination between the population
census programme, in the broad sense, and the agricultural census.

Different countries have adopted different modalities of coordinating
the two operations, depending on the phase of advancement of the
preparatory work of the population census. The type of linkage between
the two censuses vary across countries from conducting a comprehensive
*pre-census* operation in conjunction with the field work for up-dating
Enumeration Area maps (cartography) to including an *agriculture module
with a minimum number of questions* into the population census
questionnaire. The benefits of this linkage are many.

First of all, even with a minimum agriculture module, up-dated sampling
frame with additional information on statistical units can be
constructed and valuable material for more effective sample design
(stratification, optimization of sample size and selection procedures)
will be available. As population census is conducted on a complete
enumeration basis, some of the domains for which frames are difficult to
obtain are covered. This is the case for example of urban and peri-urban
agriculture, horticulture crops and some other crops which are location
specific or rare.

Secondly, in the case of comprehensive pre-census, data on many
variables related to the structure of agriculture may be obtained on a
complete enumeration basis and some very valuable agriculture related
community level data may be collected. As data become available for
small geographical units, the relevance and value of the whole census
increase considerably given the current context of policy focus on
poverty and hunger alleviation which all are known to be location
specific. The growing importance of decentralization policies also
increases demand for data at lower administrative units not always
provided by normal sample censuses. Pre-census may be considered in fact
as complete enumeration phase (first phase) of a two-phase agriculture
census; the second phase being conducted on a sample basis for
collection of detailed structural data. Furthermore, since the same
identification is used for both agriculture module and main population
census questionnaire, there is scope for cross tabulation of
agricultural related variables with socio-demographic variables which
may add more value to data analysis.

Despite these potential benefits, the experiences conducted so far have
been on an ad-hoc basis with a lot of advocacy and persuasion as
collaboration between the two major Government institutions often
responsible for the two censuses are not always as effective as it
should be. Also, whatever technical solution is adopted (pre-census or
agriculture module), there is an additional cost added to the population
census exercise (questionnaires and manuals, training, enumerator's time
in the field, supervision, data processing) and the coordination will
work only if this is recognized and corresponding resources are made
available.

**4. Country examples**

During the 2000 round of the World Census of Agriculture, several
African countries have established some kind of linkage between
population and agricultural census operations, ranging from a
comprehensive pre-census in conjunction with cartographic operation in
the field to including a small agricultural module into the main
population census questionnaire. The following countries have conducted
pre-censuses: Togo, Senegal, and Benin. Agriculture modules were
introduced in population census questionnaires by Cote d'Ivoire, Rwanda
and Uganda. The two approaches are briefly described below with two
country examples: Togo for the pre-census and Rwanda for the agriculture
module.

*Togo*

Given the socio-political situation in the country in early 1990s, which
led to displacement of large segments of the population, it was
considered that data available from the last population census could not
be used as a basis for taking the agricultural census to be taken in
1996/97. Therefore, as the country was also planning to take a new
population census it was decided to coordinate the preparation of the
two major operations and to conduct a joint field exercise for up-dating
the Enumeration Area maps. In conjunction with this exercise, a
pre-census of agriculture was conducted on a complete enumeration basis,
taking advantage of the infrastructure being mobilized in the field.

The main purpose of the pre-census of agriculture was to collect data on
rural localities and agricultural households in order to build a proper
sampling frame for the up-coming agricultural census. The pre-census had
three specific objectives:

-   Identification of agricultural households in newly delineated
    Enumeration Areas as a basis for building the sample frame for the
    agricultural census.

-   Complete enumeration of agricultural households and population in
    all geographical units and agro-ecological zones.

-   Collection of data on relevant socio-economic characteristics of
    agricultural households and localities.

Data from the pre-census was to provide a sampling frame not only for
the agricultural census of 1996/97 but also for all subsequent sample
surveys to be conducted in the agriculture and rural sector. Data from
pre-census, combined with data from pilot census was to be used to
improve the efficiency of the sample design for the census through a
series of studies:

-   Cost of data collection at PSU level and SSU level to contribute to
    determination of appropriate sample size given resources available
    and quality requirement.

-   Optimum allocation of sample between first stage and second stage
    depending on variability within and between PSUs.

-   Determination of the most appropriate variable to be used as measure
    of size of PSUs: number of agricultural households, agricultural
    population etc.

Two main types of questionnaires were used during the pre-census of
agriculture.

**Village questionnaire:**

This questionnaire included socio-economic variables for all villages:

-   Identification and general information (identification, village
    name, head...)

-   Localization of the village

-   Types of roads accessing to the village

-   Infrastructure used for water and electricity

-   Schools and training centers

-   Economic infrastructures (market, agro-industries etc..)

-   Languages spoken

-   Main economic activities

-   Fruit production

#### Household questionnaire

The following variables were included:

-   **Identification of Household**

-   **Socio-economic characteristics** of the head of the household and
    household members

-   Detailed information on the **activities of the household**

The data was used to build a sampling frame for the 1996/97 agricultural
census (a sample of 9000 agricultural households were selected) and
subsequent annual agricultural production surveys.

In addition, a specific report analyzing data from the pre-census was
published which provided valuable information on the structure of
agriculture of Togo well in advance of the release of the main census
report. More importantly, village level data proved to fulfill an
important demand for planning institutions within the Government as well
as NGOs and other intuitions operating at the field level.

*Rwanda*

During the last Population Census (2002), the Government of Rwanda,
decided to collect a limited number of information on the Agriculture
and Rural Sector by adding to the main Census Questionnaire, an
Agricultural Module. Given the socio-political turmoil that the country
experienced in the mid-1990s an up-dated frame for agriculture was much
needed. The objectives of adding this module were to:

-   Provide a complete enumeration of all households of Rwanda engaged
    in agricultural activities (including livestock, agro-forestry and
    aquaculture), to serve as a basis for development of an efficient
    and up-to-date sampling frame.

-   Provide a limited number of updated information on all agricultural
    households of the country, which allows for effective sample design
    (stratification, sample size calculation etc.) for all coming
    surveys in the sector.

-   Analyze the agricultural data collected, which can be
    cross-tabulated with other census data for more in-depth analysis
    and presentation of a reference situation in the agricultural
    sector. The use of the same household identification number in the
    Population Census Questionnaires and in the Agricultural Module,
    make it possible to do automatic linkage between the files and to
    extract tables crossing agricultural data with other socio-economic
    data at all levels.

###### Agricultural Module

-   **Identification of Household**: province, district, sector,
    "cellule" (village), enumeration area, household number and name of
    head.

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-   **Identification of Agricultural Households** (Households operating
    an agricultural holding).

-   **Type of agricultural holding operated by the Household**
    (agriculture, livestock, fishery and all combinations)

-   **Crop grown by the agricultural household** (8 main crops
    identified with all combinations)

-   **Livestock raised and numbers** (5 main livestock identified)

-   **Ownership of land**

    The Population Census used a Main Questionnaire for Ordinary
    Households and a Form for collecting information on existing
    infrastructure in all villages. The census questionnaire included
    detailed questions related to:

    -   **Identification of Household**

    -   **Housing (and other living conditions of the Household)**

    -   **Individual Characteristics of Household Members**

    -   **Deaths during the last 12 months**

        Forms for collecting detailed and geo-referenced information
        (using GPS), on existing infrastructure in all villages of
        Rwanda were also used to collect the following information:

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-   **Localization of the village**

-   **Socio-economic and cultural infrastructure in the village** (up to
    10 infrastructure may be listed with GPS coordinates)

The data collected is being used mainly to build an up-dated and
effective sampling frame for the agricultural census envisaged and all
sample surveys to be conducted on agriculture and rural sector. The
sampling frame is made of the list of all Enumeration Areas (and
villages) with the following information:

-   Total number of households

-   Number of agricultural households (crop, livestock, aquaculture,
    agro-forestry)

-   Number of households engaged in crop production, in livestock,
    aquaculture, agro-forestry and other agricultural activities

-   Number of households engaged in the production of each major crop
    and type of livestock.

    The data collected is being also used to provide detailed tables for
    analysis of the agriculture sector at all major geographical levels.
    The following types of tables are available:

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-   Number of agricultural households for all Provinces and districts

-   Number of agricultural households for all agro-ecological zones

-   Distribution of agricultural households by province and districts
    and by type of activities (crop production, livestock, aquaculture,
    agro-forestry)

-   Distribution of agricultural households by province and districts
    (and by agro-ecological zones) by type of crops and by type of type
    of livestock

-   Livestock numbers by Province, district and agro-ecological zones.

    It is envisaged to cross-tabulate data from the agricultural module
    with socio-demographic data from the main Population Census
    Questionnaire for in-depth analysis.

**5. Lessons learned**

*Coordination of the two census programmes at UN level*

Despite general recommendations on coordination between Population and
Agricultural Censuses in the Programmes for the World Census of
Agriculture prepared by FAO for each decennial programme, the
experiences conducted so far come mainly from initiatives taken at
country level. Since the UNFPA and FAO are the main organizations
technically sponsoring the Population and Agricultural Censuses, much
stronger and coordinated recommendations as well as adequate guidelines
by these organizations will provide reference to countries and
facilitate the linkage of the censuses. FAO is taking necessary steps in
this direction within the framework of the up-coming programme for the
World Census of Agriculture 2010.

*Modalities of linkage*

The modalities of linking the two censuses will continue to vary from
one country to another as many factors are to be considered. It should
however be recognized that cost implications are very different from a
comprehensive pre-census to a limited module on agriculture as part of
the census questionnaire. Whatever the case, additional funds will be
required to cover for the extra costs for printed material
(questionnaires and manuals), training, enumerators and supervisors
time, and data processing. In view of the significant benefits to be
gained with this linkage as compared to cost, for the agricultural
census and subsequent surveys, it is worth mobilizing the extra
resources needed.

*Type of questions and variables for an agriculture module*

The experiences conducted show that, the type of questions and variables
most appropriate are [simple]{.underline} often
[qualitative]{.underline} questions (type of activity, type of crop
grown, etc\...) not requiring precise measurement. Given the short
timeframe in which population census questionnaires are to be filled,
and the type of enumerators used, attempts to get precise numbers (like
livestock numbers) have failed to provide accurate results. Even data on
population numbers was not precise enough in the case of the pre-census
of Togo as questions were asked to household heads and detailed
questions on household members were not asked.

*Timing of the population census field operations and implication for
agricultural module*

The most appropriate period for collecting adequate data on agriculture
is the cropping season. Therefore for pre-censuses and agricultural
modules to better capture relevant data, it is advisable that field
operations be conducted during agricultural season. Fortunately, in many
African countries, population censuses are conducted during the summer
vacation periods in order to take advantage of the availability of large
numbers of students and teachers who can be used as field personnel and
this period coincides with cropping seasons in many places.

*Data processing and analysis*

## 

The timely processing of the agriculture module depends to a large
extent on advance planning and provision of adequate resources before
the data is collected. If the module is to be processed by the Bureau of
the Population Census, the module will most probably be the last
questionnaire to be processed as higher priority will be given to
population census main questionnaire. On the over hand, the cost of
processing will be much reduced as the data processing infrastructure of
the population census (computers and data entry clerks) will be used for
the agriculture module. This was the case in Rwanda where a delay of
several months occurred as the Bureau has to complete data entry and
editing of the main population census questionnaire before starting work
on the agricultural module. On the contrary, the pre-census of Togo was
rapidly processed as resources were made available within the Ministry
of Agriculture to quickly process the data to be used for the
agricultural census and there was no competing data entry activity.

Data analysis has to be also planned in advance and resources provided
for, if a report is to be prepared in time on the basis of the data from
agricultural module. During the experiences conducted so far
cross-tabulation of agriculture data with population data from
population censuses has not been done but in Rwanda this option is still
being envisaged.

## 

ReferenceS

AGRICULTURAL CENSUS REPORTS OF: Togo, Senegal, Cote d'Ivoire.

PRE-CENSUS REPORT OF: Togo

CILSS/C.E./Projet DIAPER, (1996). Rapport d\'évaluation de l\'enquête
agricole permanente.

D.J. Casley and D.A. Lury, (1976). Data Collection in Developing
Countries.

FAO (1995). Programme for the World Census of Agriculture 2000

FAO Statistical Development Series \# 9, (1997). Report on the World
Census of Agriculture.

FAO (1982) Estimation of crop areas and yields in agricultural
statistics

FAO, Zarkovich, (1966). Quality of statistical data

Judith T. Lessler & William D. Kalsbeek, (1992). Non sampling errors in
surveys

[^1]: *In few countries like Cape Verde however, local measurement units
    are being used by farmers and provide the basis for good
    approximation of crop area.*

[^2]: *With the increased precision of Global Positioning Systems (GPS),
    there are very promising prospects of substantially reducing the
    workload of field staff for crop area measurement in the near
    future. Several tests are being conducted to evaluate comparative
    advantage of this new device as compared to the traditional method
    using tapes and compasses.*

[^3]: *Usually, it is assumed that there is a one-to-one correspondence
    between agricultural household and holding.*