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Quality criteria for official statistics

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Presentation on theme: "Quality criteria for official statistics"— Presentation transcript:

1 Quality criteria for official statistics
Relevance: the degree to which statistics meet current and potential needs of the users Accuracy: the closeness of estimates to the unknown true values Timeliness: the period between the availability of the information and the event or phenomenon it describes Punctuality: the delay between the date of the release of the data and the target date (the date by which the data should have been delivered Accessibility and clarity: the conditions and modalities by which users can obtain, use and interpret data Comparability: the measurement of the impact of differences in applied statistical concepts, measurement tools and procedures where statistics are compared between geographical areas, sectoral domains or over time Coherence: the adequacy of the data to be reliably combined in different ways and for various uses

2 Headline indicators : SDI theme Headline indicator
EU-27 evaluation of change Socioeconomic development Real GDP per capita Sustainable consumption and production Resource productivity Social inclusion Risk of poverty or social exclusion (*) Demographic changes Employment rate of older workers Public health Life expectancy and healthy life years (**) Climate change and energy Greenhouse gas emissions Consumption of renewables (***) Sustainable transport Energy consumption of transport relative to GDP Natural resources Abundance of common birds (****) Conservation of fish stocks Global partnership Official Development Assistance Good governance [No headline indicator] :

3 Evaluation of the changes for indicators without quantitative target (case of desired direction: growth) Average annual growth rate > 1% (in absolute terms)  clearly favourable/unfavourable 0% < average annual growth rate (in absolute terms) < 1%  moderately favourable/unfavourable ¾ of the SDIs evaluated with this method

4 Evaluation of the changes for indicators with quantitative target
Theoretical target 'path'  the average annual growth rate (in %) between 2000 and the latest year for which data are available is calculated, as a proportion of the theoretical average annual growth rate that would be required to meet the target (in the target year) Average annual growth rate > =100%  on the target path  clearly favourable/unfavourable 80% < average annual growth rate < 100%  close to target path  moderately favourable Average annual growth rate < 80%  far from the target path  moderately unfavourable Clearly unfavourable  when changes are moving in the wrong direction, away from the target path 20% of the SDIs evaluated with this method

5 Evaluation of decoupling Example of Resource productivity - Changes since 2000
Indicator/year 2000 2001 2002 2003 2004 2005 2006 2007 Resource productivity 100 102.5 105.0 107.4 105.8 106.6 GDP 102.0 103.3 104.6 107.3 109.4 112.9 116.3 Domestic material consumption (DMC) 99.0 97.8 97.5 102.2 107.9 No decoupling would have occurred if DMC would have increased as much or more than the GDP Relative decoupling took place because DMC increased less than GDP Indicators intended to measure decoupling  evaluated according to the extent to which decoupling occurred  how far the connection between a particular variable and economic growth has been broken Decoupling occurs when the growth rate of the driving force (GDP) exceeds the growth rate of the environmental pressure over a certain timeframe Absolute decoupling: The pressure on environment is stable or decreasing while the economic driving force is growing Clearly favourable Relative decoupling: The pressure on environment increases but at a lower rate than the growth of the economic variable Moderately unfavourable No decoupling: The pressure on environment increases at the same or a higher rate than the growth of the economic variable Clearly unfavourable Indicators evaluated with this method: Energy intensity (Socioeconomic development) Resource productivity (Sustainable consumption and production) Greenhouse gas emissions intensity of energy consumption (Climate change and energy) Energy consumption of the transport relative to GDP (Sustainable transport) Volumes of freight and passenger transport relative to GDP (Sustainable transport) Absolute decoupling would have occurred if DMC would have been stable or would have decreased 5


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