Download Importance and Uses of Agricultural Statistics

The agricultural statistics series will be based on the Global Strategy to Improve
Agricultural and Rural Statistics that is located in the resource section and available
from the Wikipedia web page (wiki.asfoc.ibge.gov.br). The Global Strategy is based
on input from national, regional, and international institutions that have an interest in
improving agricultural statistics to meet growing user needs for reliable, timely,
relevant, comparable, consistent, and accessible agricultural data.
There is an increasing focus on the role of agricultural in rural development, where
many of the world’s poor live and work. These data are also needed for monitoring
of the Millennium Development Goals on a country, regional and international basis.
The Global Strategy cites a decline in the quality and suitability of agricultural data for
these purposes. This module will provide an overview of the importance and uses of
agricultural data to understand the current and emerging needs of data users and
broaden the vision for agricultural statistical systems.
1
Statistically speaking, agricultural statistics are seen as part of the economic profile of
a country but are increasingly becoming more broadly defined as data on agriculture
in relation to the environment, climate change, biodiversity, food security, and
natural resource management are being examined. In many countries the
relationships between the ministries of agriculture and national statistical
organizations could be improved in terms of integrating agricultural data with other
available data to provide a more comprehensive picture of the issues within a
country.
We can look at agricultural data in two general groups:
1. The structure of agriculture in a country, which includes agricultural holding by
distribution, size, tenure, land use, means of production and labor force.
2. Annual agricultural activities which includes crop and livestock production, trade
and prices of agricultural products and labor force information.
2
Increasingly Agricultural data is seen in the broader context of social, environmental
and economic needs of the population. As populations increase so does their
demand for agricultural products and need for economic stability. Therefore
agriculture is moving from simply focusing on production to sustainably meeting
social needs without damaging the environment while remaining economically viable
to the mostly lower income population.
Globalization means that raw materials can be obtained from one country, processed
in a different country, and marketed in virtually all countries. Advances in technology,
transportation and communication have made it more effective to conduct business
where it is geographically advantageous rather than being limited by the rules,
regulations and resources where the business is located.
3
International organizations and increasingly national governments need regional and
global data for planning and estimation of future needs and impacts. Agricultural
activities and policies in one country affects other countries through global trade and
environmental impact.
Agricultural statistics are needed to provide information used to monitor trends and
estimate future prospects for agricultural commodity markets which can assist in
setting policies such as price supports, where the price of a commodity is artificially
maintained by government action to stabilize the economy, or tariffs, a fee charged
by governments on particular goods that are either imported or exported.
Agricultural statistics are also needed to assess the role of agriculture commodity
production in trade and economic development, not only at the national level but
also at the regional level.
The world population is increasing as the amount of land suitable for cultivation is
diminishing, leading to food security problems. Data is needed for international
organizations to analyze the food security situation and plan efforts to meet
agricultural production requirements.
There is an increasing interest in examining the environmental impact of agricultural
activities including issues such as chemical use, genetic engineering, biodiversity,
water conservation and land use.
4
National governments need information for development planning, especially in rural
areas where a large percentage of the population may be economically dependent on
agriculture. Agricultural statistics provide this information by holding, type and area,
which is not available from other data sources in the detail required. These data on
agricultural commodity production form part of the System of National Accounts
(SNA).
Most countries are monitoring their progress towards the 2015 Millennium
Development Goals (MDGs) or are monitoring their national progress in fulfilling their
Poverty Reduction Strategy Papers (PRSPs), which are likely aligned with the MDGs.
Agricultural statistics provide critical data on several goals including food security,
gender equality, and environmental sustainability.
To determine federal policies in the support of agricultural production, resource
management, and research, the government needs reliable data on a regular basis to
identify problems, measure the impact of policies and programs, and predict
upcoming problems and opportunities by comparing data regionally and
internationally. For example, data on areas that are affected by weather-related
losses or from outbreaks of disease and pests can help define areas affected and in
need of government assistance.
5
In the Millennium Development Goals there are some indicators that come directly from agricultural statistics,
while there are others that could benefit from the addition of agricultural data to provide a more robust picture
of the situation, though they are not strictly required. An example would be information on women in agriculture
to add to the gender equality information.
The following list of direct indicators is to provide an overview of the types of data needed from agricultural
statistics to monitor MDGs. More detailed information is available from the United Nations Statistics Division
handbook, “Indicators for Monitoring the Millennium Development Goals”
(unstats.un.org/unsd/mdg/Resources/Attach/Indicators/HandbookEnglish.pdf).
Goal 1: Eradicate extreme poverty and hunger
Target 1.B: Achieve full and productive employment and decent work for all, including women and young
people
1.4 Growth rate of GDP per person employed
1.5 Employment-to-population ratio
1.6 Proportion of employed people living below $1 (PPP) per day
1.7 Proportion of own-account and contributing family workers in total employment
Goal 7: Ensure environmental sustainability
Target 7.A: Integrate the principles of sustainable development into country policies and programmes and
reverse the loss of environmental resources
7.1 Proportion of land area covered by forest
7.2 CO2 emissions, total, per capita and per $1 GDP (PPP)
7.3 Consumption of ozone-depleting substances
7.4 Proportion of fish stocks within safe biological limits
7.5 Proportion of total water resources used
Goal 8: Develop a global partnership for development
Market access
8.6 Proportion of total developed country imports (by value and excluding arms) from developing countries
and least developed countries, admitted free of duty
8.7 Average tariffs imposed by developed countries on agricultural products and textiles and clothing from
developing countries
8.8 Agricultural support estimate for OECD countries as a percentage of their gross domestic product
8.9 Proportion of ODA provided to help build trade capacity
6
Agricultural producers and associated private sector businesses that support
agricultural production need data in order to decide on the proper actions to take to
make the most of their resources and make good business decisions. Information on
crop conditions, production, inventories and prices can help determine what should
be planted, breeding and feeding decisions and marketing focus.
Agricultural support businesses including dealers, processors, warehouses, and
transportation companies need information to make operational decisions regarding
the purchasing and handling of agricultural commodities. For example, what
products to stock in what quantity such as seeds, fertilizer, and equipment as well as
tracking agricultural products ready for processing, transport and export.
7
In general, most of the poor live in rural areas with less infrastructure, lack of access
to markets and job opportunities, and more vulnerable to price fluctuations and
disasters. The rural population’s economic welfare is dependent upon agricultural
production and agribusinesses.
Many of the poorest are subsistence farmers striving to provide sufficient food for
their families. Data can be used to highlight ways to maximize productivity for
subsistence farmers and target government programs such as agricultural extension
services.
Community level data can provide a picture of market access for small holdings as
well as opportunities for supplemental incomes. Combining agricultural survey and
census data with proxy measures on socioeconomic status of holdings and rural
households can provide a more complete picture of the role of agriculture in rural
development.
8
Agricultural statistics can provide data on food availability by area which can be used
to determine the current status of food security by area. Data on community markets
and prices provides information on access.
Data on household expenditures and consumption patterns can identify at risk
households and communities, providing more quantitative information regarding
food insecurity. This can be important information for short-term assistance action
and long-term development planning.
Combining the data on availability and access with weather and crop predictions, as
well as tracking historical natural disaster patterns, can help estimate areas of future
food insecurity for planning purposes.
9
In developing countries, rural poor women often work on family farms as unpaid
family workers. They often grow small gardens and gather items to supplement
family food. This type of work is often hard to measure as it is often not considered
work. There is an opportunity to use agricultural statistics to more robustly gather
information on this under-reported area.
Agricultural statistics can provide data on farm work by gender and comparison of the
characteristics of agricultural holdings by sex can indicate any gender related issues
for further study.
10
When looking at the statistics for women in employment from the International
Labor Organization's 2009 report, you can see that the majority of women work in
the services sector worldwide. As you would expect, the percentage of women
engaged in agriculture rises when you remove developed country information from
the data.
19.3 percent of women work in the industry sector (26.6 per cent for men)
46.3 per cent in the services sector (41.2 per cent for men) and
35.4 per cent in the agricultural sector, compared with 32.2 per cent for men
The proportion of women working in agriculture rises when you exclude developing
country data.
Source: Global Employment Trends for Women
International Labour Office - Geneva: ILO, 2009
(www.ilo.org/public/libdoc/ilo/P/09275/09275(2009).pdf)
11
Data can be used to analyze a particular crop or livestock of interest, such as the main
export for the country for example, to track changes and look for ways to maximize
production.
Studies could be carried out by geographical area to look at land use and agricultural
production and see if there are better ways to maximize production within the
particular ecological zone while preserving natural resources.
For policy purposes it would be useful to analyze data by various types of agricultural
holdings such as subsistence versus market-oriented and we’ve already discussed by
gender.
12
Usually programs for agricultural development or research are conducted on a small
scale. These programs benefit from agricultural census data that can provide a robust
baseline measure for the target group of interest, whether it be by type of holding,
geographic area or type of production.
Every country has an ongoing survey program to provide up to date statistics on a
variety of topics. Including a few specific questions for the holdings participating in
the program can produce outcome measures to guide project decisions.
Impact assessment would require more robust program measures that would ideally
involve comparing baseline data to subsequent agricultural census data.
13
This may seem rather circular but the fact that new agricultural data and methods can
improve current agricultural statistics should not be ignored.
Agricultural censuses are necessary to improve intercensal survey estimates and
provide detailed small area data that is not available from survey data. In order to do
this, data must be comparable, which means standardized definitions, unit of
enumeration, and data collection methodologies. Complete documentation can also
assist in determining the potential causes of errors in estimates and help in
determining ways to improve the estimates.
14
Agricultural production takes place within ecosystems and as such has a positive or
negative impact on the environment. This is of growing concern due to the need for
sustainable agriculture and international environmental agreements that reflect
public concerns that may influence trade.
The Organisation for Economic Co-operation and Development (OECD) has
documented efforts by OECD member countries to develop a common framework to
measure the environmental impact of agriculture including definitions. This common
framework with well-defined indicators allows the tracking of trends over time
related to particular types of agriculture, utilization of scarce resources in certain
geographical areas, and the impact of certain production practices.
15
To gain an idea of the impact that agricultural activities have on the environment,
let’s look at some numbers from the June 2006, Food and Agricultural Statistics
Global Outlook (faostat.fao.org/Portals/_Faostat/documents/pdf/world.pdf), that is
produced by the statistics division of the Food and Agriculture Organization of the
United Nations (FAO).
From these data, it’s clear that agricultural activity uses a large proportion of natural
resources in terms of land and water so it is reasonable to expect that production
practices can have a large impact on resource sustainability and pollution.
Note that arable land according to the FAO use and definition in this context refers to
land that is under cultivation or left fallow less than five years. The term arable in this
context does not include land that is suitable for agriculture but not under cultivation.
Source: Food and Agriculture Statistics Global Outlook, June 2006
(faostat.fao.org/Portals/_Faostat/documents/pdf/world.pdf)
16
Agriculture is necessarily weather and climate dependent. The impact of changing
climatic conditions on agriculture needs to be taken into consideration when
forecasting needs and improving production methods to meet increasing food
demands. At the same time there is an increasing trend toward measuring,
examining and balancing between social, environmental and agricultural needs.
The inter-relationships and between agriculture and climate change is complex and
the challenge will be to maintain food production and allow economic development
to proceed in fragile areas. As research continues to examine the best ways to
quantify these relationships, statistical agencies should be aware of this area of
research in the international context.
17
Historically water resource management was concerned with supplies for agricultural
use. Increasingly this demand for water is being balanced by economic and
environmental needs in a broader sense with a focus on technologies to promote
more efficient use of water in agriculture. Better information on water availability
and use including data on water source levels and users is needed to understand
water usage.
In water scarce areas there is increasing demand for water which in some cases has
resulted in more efficient use of water. Tracking agricultural water use, especially in
irrigation, including monitoring water quality after farm use can help measure the
potential health and environmental impacts.
Agriculture is at risk from greater incidence and severity of floods and drought. This
problem is exacerbated by land use policies and urbanization in at risk zones. The
ability to analyze agricultural holdings, population distributions and flood and drought
affected areas can help decision makers in setting policies and educating the public.
18
In 1992, under the international Convention on Biological Diversity many countries
committed to conserve biodiversity including genetic resources, habitats and species.
As part of the initiative to develop agri-environmental indicators, OECD member
countries have held Expert Meetings to address specific issues, including biodiversity.
The ultimate goal is to establish a framework that covers the diversity of flora and
fauna within the complexity of social, economic and environmental interactions, and
their interaction with other ecosystems, including the variety of agricultural holdings.
While detailed studies on biodiversity may be beyond the responsibility of statistical
agencies, the system of environmental indicators could be introduced in data
collection to provide baseline and monitoring information of specific indicators that
can be integrated into the existing methodology.
19
To reduce the dependency on traditional, limited energy sources, biofuels have
become an increasing market for what were traditionally feed stocks. Agricultural
statistics are a good source to track biofuel trends and market impact. Biofuel sales
translates into better returns for producers but makes previously inexpensive food
and feed sources less viable for the poorer population.
20
Read the questions on the slide without referring to the other slides. Note your
answers and then scroll down for the answers. Do not worry about precise
terminology, the point is to understand the concepts presented. If you answer a
question incorrectly, review the applicable slides.
QUIZ ANSWERS:
1.
Agricultural statistics can be classified into what two groups? Structural and
Activity statistics.
2.
Why do producers and private sector need agricultural statistics? To manage
their respective businesses, farmers or producers to know what seeds to buy,
what market prices are when choosing livestock feed, etc. Agricultural
service or support business to prepare for processing, transportation, farm
supplies, etc.
3.
What percentage of the world’s land is use for agricultural activities? 38%
4.
What does agriculture have to do with poverty? Many poor people live in
rural areas where a large part of the economy is based on agriculture.
21