Production and trade methodology

Acknowledging the sheer scale of technological advances in the means of communicating data, FAO is seeking innovative solutions to enhance its data collection capacities, beyond the questionnaire. At the forefront of this innovation, FAO is exploring seamless data exchange and harvesting possibilities such as SDMX with statistical agencies of membership countries and other international institutions, to maximize coverage, while minimizing respondent burden.

Assembling and disseminating information
Once data are collected, the next challenge is to assemble and disseminate information in an internationally comparable form, taking stock of the diversity in country datasets regarding concepts, definitions, coverage and classifications. In this connection, FAO is in the process of harmonizing its data norms and methodologies with internationally adopted classification schemes such as the Central Product Classification (CPC) of the United Nations Statistics Division (UNSD) for production data and the Harmonized Commodity Description and Coding System (HS) of the World Customs Organization (WCO) for trade data.

Quality standards
Continuous endeavours are made to ensure that our data conform to the highest quality standards. Quality assurances hinge on developing and implementing new methodologies. For example, in 2011 the division set about in overhauling its framework for imputing missing or non-reported crop data. Every effort is made to collect data, but there will always be cases when data are simply unavailable. A new methodology was developed to use contemporaneous information on harvest outcomes in nearby countries or similar crops within the country to estimate missing values in a particular country. The degree of precision achieved using this method considerably enhances confidence in using our datasets, not just for research and analysis but for decision-making and policy formation.