This document provides an overview and objectives of a CountrySTAT regional basic administrator training for GCC member states being held in Abu Dhabi, UAE from January 26-30, 2014. It discusses how CountrySTAT is aligned with the FAO's Global Strategy to Improve Rural and Agricultural Statistics by establishing a minimum core set of data, integrating agriculture into national statistical systems, and building statistical capacity. The training will cover statistical concepts, quality processes, core and sub-national modules to standardize data, and statistical reference documents to support countries in improving their food and agriculture data.

1. CountrySTAT REGIONAL BASIC
ADMINISTRATOR TRAINING
for GCC MEMBER STATES
Abu Dhabi, United Arab Emirates (UAE), 26 – 30 January 2014
CountrySTAT STATISTICS COMPONENT
(Concepts, Definitions, Classification, Data
Harmonization)
CountrySTAT Team
FAO, Statistics Division
Rome-Italy

2.  CountrySTAT and Global Strategy to Improve
Rural and Agricultural Statistics
 Objectives of the Statistical Component
 Data Quality Process
 Core and Sub-National Modules
 Statistical Specific Characteristics in the Data
Quality Assessment
 Panorama Reports
 CountrySTAT Statistical Reference Documents
OVERVIEW

3. • The Global Strategy supports developing countries to
produce timely and accurate agriculture and rural
statistics by improving statistical systems, methods, tools
and staff skills
• CountrySTAT is aligned with the principles of the Global
Strategy to Improve Agriculture and Rural Statistics. The
Global Strategy is based on 3 pillars:
 Establishment of a minimum set of core data that countries will collect to
meet current and emerging demands (Economic, Social, Environmental and
Geographic Location data)
 The integration of agriculture into national statistical systems in order to
satisfy the demands of policy makers and other users who rely on
comparable data across locations and over time
 Governance and statistical capacity development which will provide the
foundation for sustainability of the agricultural statistics systems
CountrySTAT AND GLOBAL STRATEGY TO IMPROVE
RURAL AND AGRICULTURAL STATISTICS

4. • Centralization and integration of data coming from various
sources
• Promote the use of the international standards (Concepts,
Definitions, Classifications) and Metadata
• Data harmonization according to FAO standards
• Support countries to create tables, improve the structure of
data tables, data quality, and to make data available for key
indicators
• Assist countries in the uploading of data from different agricultural
surveys/censuses, statistical yearbooks, food balance
sheets, estimation of missing data
• improve statistical skills of staff in countries
OBJECTIVES OF THE STATISTICAL COMPONENT

5. • DIFFERENT PHASES OF THE DATA QUALITY PROCESS:
DATA QUALITY PROCESS

6. • Core Module using the standard data structure allows to compare
data at regional and international level for the 14 Domains (Production,
Trade, Population, Food Availability, Labor, Land Use and Irrigation,
Machinery, Pesticides, Fertilizers, Prices, Forestry, Fisheries, Water and
Value Added) and the Core Standard Indicators.
• Sub-National Module includes the same categories (domains and
indicators) described in the Core Module (with disaggregated data at
sub national level according to the national classification).
• Correspondence table allows to ensure linkage and coherence
between the national classification at sub-national level and the
international classification at national core level.
• Data from Core Module allows to support the elaboration of the Food
Balance Sheets (FBS) and analytical indicators to get Food Security
Statistics.
CORE AND SUB-NATIONAL MODULES

7. DATA OF CORE MODULE

8. DATA OF CORE MODULE

9. • The statistical specific characteristics in the data
quality assessment that refer the CountrySTAT
Team are as follows:
 Relevance and completeness
 Accuracy
 Comparability
 Coherence
 Timeliness and punctuality
 Accessibility and clarity
STATISTICAL SPECIFIC CHARACTERISTICS
IN THE DATA QUALITY ASSESSMENT

10. • Relevance : Refers to the ability of data to meet
current and potential user needs at national,
regional and international levels.
• Accuracy: The analysis of data and metadata accuracy
are carried out during the Technical Working Groups
Meetings.
• Comparability : The adaptation of the national
classification to the classification of commodities,
concepts and definitions of the FAO ensures regional
and international comparability of statistical data.
STATISTICAL SPECIFIC CHARACTERISTICS
IN THE DATA QUALITY ASSESSMENT

11. • Coherence: Refers to the ability of data to meet current and
potential user needs at national, regional and international levels.
STATISTICAL SPECIFIC CHARACTERISTICS
IN THE DATA QUALITY ASSESSMENT

12. • Timeliness and punctuality: refer to the
time-lag between data collection and
dissemination.
• Accessibility and clarity : require an
organization of data structure to have easy
access to the data and metadata.
STATISTICAL SPECIFIC CHARACTERISTICS
IN THE DATA QUALITY ASSESSMENT

13. • Periodical Panorama Reports” are written by each country to
understand the current situation of national statistics systems.
• The Panorama Reports provide an overview of the
institutional, legal, technical and operative aspects of national
food and agriculture statistics.
PANORAMA REPORTS I & II

14. • Statistical Reference Manual
• CountrySTAT Concepts, Definitions and Classification
• International Classifications
• CountrySTAT e-learning course
• CountrySTAT Brochures
• CountrySTAT Communications Strategy
CountrySTAT STATISTICAL REFERENCE DOCUMENTS

15. 27/01/2014
Statistics Division, FAO Rome-Italy
THANK YOU