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Transparency and statistics

Transparency and statistics. The contribution of statistics to the improvement of transparency in the policy making process. Policy making and transparency. Policy making covers the whole process from decision making up and until evaluation of the implementation

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Transparency and statistics

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  1. Transparency and statistics The contribution of statistics to the improvement of transparency in the policy making process

  2. Policy making and transparency • Policy making covers the whole process from decision making up and until evaluation of the implementation • Transparency inheres verifiable, reliable and measurable observations of changes in reality due to policy making • Transparency in policy making improves the quality of the policy making process dr. ir. Hans Stol, Transparency and Statistics, www.stolconsult.nl

  3. Framework for Evidence Based Policy Making ENVIRONMENT EBPM CONTROL SYSTEM EVIDENCE BASED DECISION MAKING INDICATOR VALUES MODELLING AND ANALYZING INTENDED INDICATOR VALUES OBJECTIVES/ INDICATORS MEASURED VALUES MEASURES TO CHANGE REALITY ACCORDING THE OBJECTIVES OBJECT SYSTEM OF INTEREST dr. ir. Hans Stol, Transparency and Statistics, www.stolconsult.nl

  4. classification policy area publisher indicator object type objective derivation rule metadata measurement indicator Politicians and Statisticians cooperate/communicate by standardised reference frame Metadata model measurement Metadata model objectives admin. source questionnaire classification policy area classification data item (+metadata) target (value,time) object type question object type objective Metadata model presentation reality dr. ir. Hans Stol, Transparency and Statistics, www.stolconsult.nl

  5. Example of indicatorsWB experience in Morocco: policy area “innovation: improvement of the use of ICT” objectives results dr. ir. Hans Stol, Transparency and Statistics, www.stolconsult.nl

  6. Transparent politicians value statistics statisticians Do we know what the population is (students, companies in innovative sectors of industry, innovative functions, people participating in innovative functions)? Can we determine the meta data (definition of the data to be measured)? Can we measure in an effective way? Do we have (need) reference data? Can we use administrative sources? Can we disseminate the indicators timely? politicians • Can we influence innovation? • If yes: can we define objectives related to real world: which entities carry attributes connected to innovation? • If no: do not intend to be transparent. • Do we really whish to define the intended situation in a measurable way? • If yes: can we define the pursued situation in a measurable way? • If no: do not intend to be transparent. • Define the objectives in terms of real world entities: p.e.: # graduated students in IT, # jobs in defined innovative functions, turnover in defined innovative sectors of industry (always related to the realisation of measurable objectives). dr. ir. Hans Stol, Transparency and Statistics, www.stolconsult.nl

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