Quality Guidelines for statistical processes using administrative data European Conference on Quality in Official Statistics Q2014 Giovanna Brancato, Francesco.

Slides:



Advertisements
Similar presentations
ESRC UK Longitudinal Studies Centre A Framework for Quality Profiles Nick Buck and Peter Lynn Institute for Social and Economic Research University of.
Advertisements

Eurostat Georgiana Ivan Jean-Louis Mercy Eurostat, European Commission European Conference on Quality in Official Statistics Vienna, 3-5 June 2014 Measuring.
Fulvia Cerroni - Serena Migliardo - Enrica Morganti Italian National Institute of Statistics Session 27: Use of administrative sources I Helsinki 5 May.
Enhancing Data Quality of Distributive Trade Statistics Workshop for African countries on the Implementation of International Recommendations for Distributive.
QM Implementation Based on CoP, PDCA, and GSBPM
CZECH STATISTICAL OFFICE | Na padesatem 81, Prague 10 | Jitka Prokop, Czech Statistical Office SMS-QUALITY The project and application.
TURKISH STATISTICAL INSTITUTE Metadata and Standards Department 1 Nezihat KERET Gülhan Eminkahyagil Metadata and Standards Department Turkish Statistical.
The use and convergence of quality assurance frameworks for international and supranational organisations compiling statistics The European Conference.
Giovanna Brancato, Marina Signore Istat Work Session on Statistical Metadata (METIS) Metadata and Quality Indicators Reuse for Quality reporting Geneva,
European Conference on Quality in Official Statistics (Q2010) 4-6 May 2010, Helsinki, Finland Brancato G., Carbini R., Murgia M., Simeoni G. Istat, Italian.
Use of survey (LFS) to evaluate the quality of census final data Expert Group Meeting on Censuses Using Registers Geneva, May 2012 Jari Nieminen.
Quality assurance activities at EUROSTAT CCSA Conference Helsinki, 6-7 May 2010 Martina Hahn, Eurostat.
REFERENCE METADATA FOR DATA TEMPLATE Ales Capek EUROSTAT.
Marina Signore Head of Service “Audit for Quality Istat Assessing Quality through Auditing and Self-Assessment Signore M., Carbini R., D’Orazio M., Brancato.
Quality issues on the way from survey to administrative data: the case of SBS statistics of microenterprises in Slovakia Andrej Vallo, Andrea Bielakova.
CountrySTAT REGIONAL BASIC ADMINISTRATOR TRAINING for ECO MEMBER STATES Ankara, Turkey, October 2013 CountrySTAT STATISTICS COMPONENT (Concepts,
Implementation of quality indicators in the Finnish statistics production process Kari Djerf Statistics Finland Q2008, Rome Italy.
CZECH STATISTICAL OFFICE Na padesátém 81, CZ Praha 10, Czech Republic 1 Subsystem QUALITY in Statistical Information System Czech.
European Conference on Quality in Official Statistics Session 26: Quality Issues in Census « Rome, 10 July 2008 « Quality Assurance and Control Programme.
Towards a more efficient system of administrative data management and quality evaluation to support statistics production in Istat Grazia Di Bella, Simone.
Giovanna Brancato, Giorgia Simeoni Istat, Italy European Conference on Quality in Official Statistics – Q2008, Rome, 8-11 July 2008 Modelling Survey Quality.
Use of Administrative Data Seminar on Developing a Programme on Integrated Statistics in support of the Implementation of the SNA for CARICOM countries.
Statistik.atSeite 1 Norbert Rainer Quality Reporting and Quality Indicators for Statistical Business Registers European Conference on Quality in Official.
Supporting Researchers and Institutions in Exploiting Administrative Databases for Statistical Purposes: Istat’s Strategy G. D’Angiolini, P. De Salvo,
1 C. ARRIBAS, D. LORCA, A. SALINERO & A. COLMENERO Measuring statistical quality at the Spanish National Statistical Institute.
Copyright 2010, The World Bank Group. All Rights Reserved. Principles, criteria and methods Part 2 Quality management Produced in Collaboration between.
Implementation of the European Statistics Code of Practice Yalta September 2009 Pieter Everaers, Eurostat.
Pilot Census in Poland Some Quality Aspects Geneva, 7-9 July 2010 Janusz Dygaszewicz Central Statistical Office POLAND.
United Nations Oslo City Group on Energy Statistics OG7, Helsinki, Finland October 2012 ESCM Chapter 8: Data Quality and Meta Data 1.
QUALITY ASSESSMENT OF THE REGISTER-BASED SLOVENIAN CENSUS 2011 Rudi Seljak, Apolonija Flander Oblak Statistical Office of the Republic of Slovenia.
Overview and challenges in the use of administrative data in official statistics IAOS Conference Shanghai, October 2008 Heli Jeskanen-Sundström Statistics.
Report on the breakout session on Rapid Estimates Roberto Barcellan European Commission - Eurostat.
Census quality evaluation: Considerations from an international perspective Bernard Baffour and Paolo Valente UNECE Statistical Division Joint UNECE/Eurostat.
14-Sept-11 The EGR version 2: an improved way of sharing information on multinational enterprise groups.
The business process models and quality issues at the Hungarian Central Statistical Office (HCSO) Mr. Csaba Ábry, HCSO, Methodological Department Geneva,
Copyright 2010, The World Bank Group. All Rights Reserved. Principles, criteria and methods Part 1 Quality management Produced in Collaboration between.
First meeting of the Technical Cooperation Group for the Population and Housing Censuses in South East Europe Vienna, March 2010 POST-ENUMERATION.
Fulvia Cerroni - Viviana De Giorgi (Istat) Session 11: Use of administrative data in the statistical system 15 October 2008 The Tax Authority Source as.
Overview of Programme of the Working Group on Flash Estimates of GDP Roberto Barcellan European Commission - Eurostat.
13 November, 2014 Seminar on Quality Reports QUALITY REPORTS EXPERIENCE OF STATISTICS LITHUANIA Nadiežda Alejeva Head, Price Statistics.
1 European Statistics Code of Practice. I.Institutional Environment Principle II.Statistical processes Principle III.Statistical Output Principle.
Quality Reports Ukraine November Regulation 223/2009 on European Statistics European Statistics shall be produced  on the basis of uniform standards.
A Training Course for the Analysis and Reporting of Data from Education Management Information Systems (EMIS)
1 Recent developments in quality related matters in the ESS High level seminar for Eastern Europe, Caucasus and Central Asia countries Claudia Junker,
Quality declarations Study visit from Ukraine 19. March 2015
National Population Commission (NPopC)
Implementation of Quality indicators for administrative data
Supporting the use of administrative data in official statistics.
Quality assurance in official statistics
Dual Mode of Data Collection – A New Approach in the Population, Housing and Dwelling Census in Slovakia in 2011 European Conference on Quality in Official.
4.1. Data Quality 1.
Documentation of statistics
Generic Statistical Business Process Model (GSBPM)
Overview of the ESS quality framework and context
Organization of efficient Economic Surveys
Sub-regional workshop on integration of administrative data, big data
Quality assessment ESTP Training Course “Quality Management and survey Quality Measurement” Rome, 24 – 27 September 2013 Giorgia Simeoni Researcher Unit.
The European Statistics Code of Practice - a Basis for Eurostat’s Quality Assurance Framework Marie Bohatá Deputy Director General, Eurostat ... Strategic.
Quality Reporting in CBS
Assessment of quality of standards
The new quality strategy in the modernised Italian National Statistical Institute Giovanna Brancato Giorgia Simeoni, Antonia Boggia,
Karin Blix, Statistics Denmark,
GSBPM AND ISO AS QUALITY MANAGEMENT SYSTEM TOOLS: AZERBAIJAN EXPERIENCE Yusif Yusifov, Deputy Chairman of the State Statistical Committee of the Republic.
Metadata on quality of statistical information
Prodcom Working Group Item Quality reporting and indicators
2.7 Annex 3 – Quality reports
European Statistics Code of Practice
Guy Van Gyes CAWIE-meeting 23-24/01/2012
Joint UNECE/Eurostat/OECD
ESS conceptual standards for quality reporting
Presentation transcript:

Quality Guidelines for statistical processes using administrative data European Conference on Quality in Official Statistics Q2014 Giovanna Brancato, Francesco Barbalace, Antonia Boggia, Claudia Busetti ISTAT, Italian National Statistical Institute Unit Auditing, Quality and Harmonisation

Presentation of the work Rationale Quality evaluation requires reference standards Main purpose To provide Istat with a manual of principles and guidelines on quality for processes using administrative data Methods Identification of a reference quality model; development of quality guidelines; contributions by Istat experts State of the art First release: almost complete Results Precondition for the launch of auditing and self- assessment procedures

Rationale Audit Self- assessment Length: about 60 pages Organization: General principles & guidelines -Process quality -Output quality -Annexes Releases: August: in Italian February: update and English version

Quality model in statistical processes using administrative data Quality Guidelines for statistics produced using administrative sources Usability Before any specific statistical purpose is identified Input quality Quality of the administrative sources used for statistical purposes Throughput quality Referred to the process of using administrative sources for specific statistical purposes Output quality Quality of statistics produced using administrative data

Quality model in statistical processes using administrative data Usability next presentation Input quality Presentation: “Towards a more efficient system of administrative data management and quality evaluation to support statistics production in Istat – ISTAT” Scheduled in: Session “Integrated Production and Data Modelling” Wednesday (14:30-16:00)

The Quality Guidelines: Input quality Quality of the sources, centrally acquired, managed and monitored Principles main issues/ stepsDecision/documentation elements Scouting of new administrative sources Preliminary investigation; Knowledge of administrative concepts and rules Evaluation on the acquisitionActual and potential relevance; Costs/Benefits; Actual and potential uses; Stability; Quality Acquisition of an administrative register Formal agreements: time, frequency, format, documentation, costs,… Pre-treatmentTechnical transformations; Check on metadata documentation; Integration with standard classifications; Common harmonization activity; Basic quality control and validation; Production of standard quality indicators Monitoring and feedback to data providers Number and kind of internal uses; Satisfaction on the use from internal users; Feedback to producers

The quality Guidelines: Throughput quality Conceptual & Process Target popul. & concept Choice of the source Used source Integration Units harmonization Variables and classifications derivations Time dimension alignment Editing & imputation Estimation Objects (units & events) coverage error: missing, units duplicates, delays linkage errors: missed links, mislinks Variables specification /validity error comparability errors missing items measurement errors, mapping errors, compatibility errors, comparability errors Potential errors

The quality Guidelines: Throughput quality Example on a Principle and Guidelines: Editing and Imputation Principle: The strategy adopted in the E&I phase should take into account the specific nature of the administrative data. The impact of the E&I procedure should be assessed using proper quality indicators. Guidelines: 1.Strategy a.Single source vs. integrated sources b.Steps when a single source is used c.Alternatives in integrated sources: pros & cons 2.Type of errors and treatment methods a.Sources of errors b.Tailoring of editing & imputation methods in data from administrative sources 3.Evaluation on the impact of the E&I phase

Output Quality The quality of statistics produced using administrative data (output quality) is defined according to the dimensions of EU quality vector Relevance Accuracy QualityTimeliness & Punctuality Accessibility & Clarity Comparability Coherence The administrative nature of used data may affect most of quality components and may limit our possibility to measure some components of the accuracy dimension

Output Quality Relevance. Statistics meet the needs of users Accuracy and reliability. Statistics accurately and reliably portray reality Timeliness and punctuality. Statistics are released in a timely and punctual manner Coherence and comparability. Statistics are consistent internally, over time and comparable between regions and countries; it is possible to combine and make joint use of related data from different sources Accessibility and clarity. Statistics are presented in a clear and understandable form, released in a suitable and convenient manner, available and accessible on an impartial basis with supporting metadata and guidance

Index of the Guidelines Section I. Process Quality A. Acquisition and management of an administrative register A.1. Scouting and study of new sources A.2. Preliminary evaluation on the acquisition of an administrative register A.3. Acquisition of an administrative register A.4. Pre-treatment, quality controls and release for internal uses A.5. Monitoring and evaluation on the internal use and feedbacks to producers

Index of the Guidelines B. Dealing with an administrative register in a statistical production process B.1. Identification of the objectives of the use B.2. Analysis and choice of the register B.3. Data integration B.4. Identification and harmonization of units and coverage evaluation B.5. Derivation of variables and classification B.6. Alignment of time and geographical dimension C. Data treatment C.1. Editing and imputation C.2. Estimation C.3. Validation

Index of the Guidelines D. Data storage, dissemination and documentation D1. Data storage, dissemination and documentation Section II: Output Quality Definition of “output” Quality dimensions and meaning when applied to outputs using administrative data Impact of the use of administrative data on quality dimensions

Thank to the other contributors of the Guidelines F. Cerroni, M. Di Zio, D. Filipponi, O. Luzi, M. Scanu Thank you for your attention