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Istat’s  new strategy and tools for enhancing statistical utilization of the available Istat’s  new strategy and tools for enhancing statistical utilization of the available

Istat’s new strategy and tools for enhancing statistical utilization of the available - PowerPoint Presentation

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Istat’s new strategy and tools for enhancing statistical utilization of the available - PPT Presentation

Istats new strategy and tools for enhancing statistical utilization of the available administrative databases Giovanna DAngiolini Pierina De Salvo Andrea Passacantilli Speaker Andrea Passacantilli ID: 768520

administrative data statistics quality data administrative quality statistics 2014 june vienna indicators statistical national institute features istat archive forms

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Istat’s new strategy and tools for enhancing statistical utilization of the available administrative databasesGiovanna D’AngioliniPierina De SalvoAndrea PassacantilliSpeaker: Andrea PassacantilliQ2014 - Vienna, 2-5 June 2014 Italian National Institute of Statistics - Vienna, 2-5 June 2014

The administrative data sources owned by public institutions set up an important information asset for official statistics By means of properly exploiting these data repositories it is possible to:reduce the costs of producing statistical data reduce the need for surveys and therefore the burden on respondents (people, firms, other organizations)improve the data quality, in particular the data timeliness and the coverage of the populations of interest Administrative data sources - a resource for official statistics Italian National Institute of Statistics - Vienna, 2-5 June 2014

DPR 7 september 2010, n.166: new Istat regulation ISTAT provides “for defining methods and formats to be used by the public administration for exchanging and using statistical and financial information in the web, as well as for harmonizing changes, enhancements and new design initiatives which concern the sets of forms and the information systems which are used by the public administration for collecting information which is used or may be used for statistical purposes”The aim of the project is to exploit administrative data sources for statistical purposes, working and studying on the administrative forms, but not only.It is referred to ALL the administrative data sources: “…which are used or MAY BE USED for statistical purposes”CHANGING OR RE-DESIGNING AN ADMINISTRATIVE FORM: AN OCCASION FOR NEGOTIATING CHANGES IN ORDER TO MAKE THE RELATED ARCHIVES MORE USEFUL FOR STATISTICAL PURPOSES The purpose of Istat’s strategy Italian National Institute of Statistics - Vienna, 2-5 June 2014

COMMITTEE FOR HARMONIZING ADMINISTRATIVE FORMS Members are nominated by Istat and by administrative data archive owner institutions launches INVESTIGATIONS ON ADMINISTRATIVE DATA ARCHIVES and their related ADMINISTRATIVE FORMS An INVESTIGATION is an analysis and documentation activity concerning the CONTENT and the QUALITY of the archive jointly undertaken by ISTAT and the OWNER INSTITUTION by means of standard methodological and information managing tools releases RECOMMENDATIONS on INNOVATION PROJECTS concerning ADMINISTRATIVE DATA ARCHIVES and their related ADMINISTRATIVE FORMS the OWNER INSTITUTION informs ISTAT about the innovation project ISTAT evaluates the project and releases recommendations Committee for harmonizing administrative forms: NEW ACTIVITIES Italian National Institute of Statistics - Vienna, 2-5 June 2014

Committee for harmonizing administrative forms:THE INFORMATIC TOOLSDARCAP (Documenting ARChives of P ublic Administration) is a web-based information management system which:supports Istat experts in producing STRUCTURED DOCUMENTATION of the CONTENT of the existing administrative data archives and of their main features (such as the owner institutions) which is collected by INVESTIGATIONS on the archive supports the owner institutions in sending Istat via web their COMMUNICATIONS which concern INNOVATION INITIATIVES on administrative forms and archives supports Istat experts in producing STRUCTURED DOCUMENTATION of the NEW CONTENT of the administrative data archives which are involved in innovation projects, and in defining ISTAT RECOMMENDATIONS Italian National Institute of Statistics- Vienna, 2-5 June 2014

SET (collection of observable items) POPULATION (subset of reference populations such as families, persons, businesses, organizations) SET OF EVENTS which occur in time INSTANT EVENT DURABLE EVENT two types: QUANTITATIVE OR QUALITATIVE FEATURES, VARIABLES FEATURE CLASSIFICATIONS (sets of admittable items for a qualitaitve feature), DOMAINS OF VALUES has EXAMPLES: Student, Degree course, Employer, Employee, Patient, Hospital, Business, Local unit EXAMPLES: University enrollment, Examination, Hiring on, Hospitalization, Hospital discharge EXAMPLES: Employment contract, Hospital stay, Current degree course EXAMPLES: Sex, Age, Turnover, Type of emplyment contract, Date of university enrollment, Duration of hospitalization EXAMPLES : Sex classification, Age classes, Amount of turnover which get a qualitative classification item or a value taken from has STRUCTURED DOCUMENTATION OF THE CONTENT OF THE ADMINISTRATIVE DATA SOURCES : THE ONTOLOGY two types: has

STRUCTURED DOCUMENTATION OF THE CONTENT OF THE ADMINISTRATIVE DATA ARCHIVES: WHICH INFORMATION AN ADMINISTRATIVE DATA ARCHIVE COLLECTS – QUALITY EVALUATION The content of the observed SETS evolves in time Elements of reference statistical populations such as families, persons, businesses, organizations, with their features, enter into or exit from those particular POPULATIONS which are observed by the administrative archive (population’s coverage)Example: a persons enrolls in a university and becomes a student, a student gets a degreee and is not a student anymore New instant events with their features occur and enter into SETS OF INSTANT EVENTS New durable events with their features begin and enter into SETS OF DURABLE EVENTS, or finish The administrative data source observe such an evolution,through a CONTINUOUS DATA COLLECTION activity (coverage problems) Italian National Institute of Statistics- Vienna, 2-5 June 2014

Committee for harmonizing administrative forms:THE METODOLOGICAL TOOLS To set up a framework of quality indicators, classified by quality hyperdimension and dimension, for assessing and documenting the overall quality of any administrative data archive We intend quality as quality for statistical usage, but irrespective of any particular statistical usageWe take into account the existing work, particularly the BLUE-ETS experienceWe work in accordance with the Statistical Network on Administrative Data - UN-ECE, OECD, EurostatGive methodological directions for using the structured documentation of the content of the archive as a guide in specifying proper indicators for any archive, as well as in interpreting the meaning of the obtained indicators Which are the proper indicators for each observed SET with its related FEATURES/VARIABLESFor each obtained indicator , which kinds of error it measures Italian National Institute of Statistics - Vienna, 2-5 June 2014

Hyperdimensions Dimensions Quality Indicators Hyperdimensions : Source, Metadata, DataMetadata1. Clearness and standardization of the data documentations 2. Comparability of the data documentations 3. Identification code and linking variables 4. Documentation of the collection procedures and use of personal data. Source 1 . Keeper 2. Relevance and utilizations 3. Privacy and security 4. AvailabilityData (in progress) Coverage and identifications , Integrability , Accuracy , Time- related dimension Regulatory reference of the archive Potential Utilization Data release ….Documentation availability of the archive’s contentExisting identification code, for every collective…. Quantitative indicators CALCULATED ON DATA FRAMEWORK FOR QUALITY IDICATORS: THE STRUCTURE Quality indicators Italian National Institute of Statistics - Vienna, 2-5 June 2014

Quantitative indicators and possible errorsIn order to define such quantitative indicators, first we have discriminated between possible errors, on one side, and ways of checking them, on the other side. The possible errors are defined in terms of those objects that may be present in an administrative data source’s ontology…an example!Italian National Institute of Statistics- Vienna, 2-5 June 2014

Student (Rossi 1/1/2012_t ) Enrollment (Enrollmenti 1/1/2012) Career ( Career m1/1/2012_t) Examinations ( Examination j 1/1/2013 ) Degree ( Deegree k 1/1/2012 ) Examinations and their features t Careers and their features ENROLLMENTS and their features Degrees and their features STUDENTS REGISTRY Student ( Verdi 1/1/2010_t ) Student ( Rossi 1/1/2012_t ) STUDENTS Student ( Bianchi 1/1/2012_t ) wrong inclusion wrong exclusion

Quality check methods Q uality indicators’ frame concerning the collectives’ coverage and the elements’ identificationSearching evident errors (duplicate identification codes)Linking with other data sourcesUsing logical constraints Calculating time lags Two other quality indicators’ frames: the possible errors on characteristics and relationshipsItalian National Institute of Statistics- Vienna, 2-5 June 2014

ConclusionsWe are now ready to start the investigation activity and the supervision activity on innovation projects concerning administrative data sources at operating speedWe are now carrying on our work of specifying indicators in the Data hyperdimension We plan to integrate the existing indicators, such as the BLUE-ETS indicators, in our indicators’ framework We are aiming to provide foundations for future research aimed at building a generalized probabilistic frame for the quality assessment activityItalian National Institute of Statistics- Vienna, 2-5 June 2014