Improving Agricultural Statistics in the COMCEC Region
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need for re-aligning agricultural statistics to new problems and user requirements.11 The
following routes for expansion are suggested:
 Agriculture to Rural : This is a route suggested with the development of the Geographical
Information System (GIS) technology, which makes measurements based on area frames
easier and more reliable. However, it is not easy to properly define the term ‘rural’, and to
link agricultural households or enterprises, which are at the heart of agricultural statistics,
to spatial measurements.
 Resources to Production: Statistics making it possible to link resource use to output, in
addition to providing isolated information on the components EAA, Input-Output (I-O) and
Social Accounting Matrices (SAM) are essential to conduct economic analysis on
productivity and efficiency in agriculture.
 Producer to Consumer: Agricultural policies of the past (and at present in many
countries) generated agricultural statistics which are predominantly producer-oriented,
neglecting the consumers. Consumers are in both urban and rural areas, and constitute the
reason for the existence of agriculture. This is why many institutions are now referring to
“food and agriculture” statistics instead of “agriculture statistics”.
 Agriculture to Agro-Industry: This is where most of the value is added to agricultural
products. This is also the main source of diminishing agricultural GDP in the total GDP. As
more and more agricultural products are processed and transported further away from
the field, before reaching the consumers, the agricultural value added shifts from the
agricultural sector to the industrial sector and services. Agricultural statistics should
capture the journey of agricultural value added, in order to maintain the interest in
agriculture and related statistics.
 Agriculture to Related Non-Agriculture: Agriculture does not operate in isolation from
other sectors of the economy. It is therefore important to be able to link the agricultural
sector and its statistics to the rest of the economy, to be able to analyze the forward and
backward linkages of the sector.
So here are the new issues and challenges:
 Wider Scope of Agricultural Statistics : Agriculture is covered when the supply, demand
and market issues are addressed simultaneously, and integrated into the rest of the
economy and further to the rest of the world.
 Micro-Data and Confidentiality : Everybody wants micro-data but nobody wants to share
their micro-data with others. Providers of agricultural statistics need to find a way to
disseminate micro-data, while ensuring that the privacy of the data is not violated.
 Quality of Statistics: Quality of statistics depends on the quality at the source, processing
and user levels. Trade-offs between time, cost and statistical error are unavoidable.
11 Kasnakoglu, 2005.