Guidelines on the use of estimation methods for the integration of administrative sources DIME/ITDG meeting 2018/02/22

Contents Purpose of the presentation Objectives of the guidelines Pre-requisites for integration Usage scenarios Typology of methods Conditions for the use of methods Structure of the guidelines Purpose of the presentation To provide information to the DIME/ITDG about the status of the project and to receive feedback and comments

Objective of the guidelines – 1 Nowadays statistical products regularly rely on different data sources Such products are often called multi-source statistics This project focused on estimation methods for the integration of different sources Distinction between two kinds of data sources Statistical data Administrative data

Objective of the guidelines – 2 The guidelines consider the integration of these two kinds of sources For the integration of statistical data and administrative data it is necessary: To create an infrastructure which supports the integration To distinguish different usage scenarios for the integration To understand the conditions necessary for the application of the different methods

Objective of the guidelines – 3 For a number of usage scenarios the guidelines present: A short description of methods which are applicable in the usage scenario Decision rules for usage of the methods under more detailed specifications of the usage scenario A recommendation of preferred methods if the usage scenario allows the application of different methods

Prerequisites for integration of administrative data – 1 For the integration of administrative data in the statistical production process an appropriate infrastructure must be available: Appropriate IT infrastructure Database architecture Software for data access, data manipulation, and technical data integration (statistical) software which supports the use of methods

Prerequisites for integration of administrative data – 2 A model for assessing quality of multi-source statistics Administrative and organisational infrastructure Arrangements with administrative units for data exchange including legal aspects (privacy, security) Competent staff for the production of multi-source statistics

Prerequisites for integration of administrative data – 3 Useful sources for details about prerequisites: ESSnet on quality of multisource statistics – KOMUSO https://ec.europa.eu/eurostat/cros/content/essnet-quality-multisource-statistics-komuso_en ESSnet on the use of administrative data and accounts data in business statistics https://ec.europa.eu/eurostat/cros/content/use-administrative-and-accounts-data-business-statistics_en

Usage scenarios for administrative data – 1 A bird’s eye view on usage scenarios: Administrative data used either exclusively or in combination with survey data as source for statistical products (Direct usage) Administrative data used as source for building and maintaining statistical registers (Indirect usage) Administrative data used as support in the different sub-processes of the GSBPM (Indirect usage) Integrate data, Edit & impute, Weighting and estimation, Calculate aggregates, Validation, ….

Usage scenarios for administrative data – 2 All usage scenarios use methods for data linkage (GSBPM sub-process 5.1: Data integration in a narrow sense) and require: The identification of units The identification of duplicates Challenges are: The harmonisation of units and measurements in different sources (alignment) The presentation of the same figures for the same phenomenon in different sources (univalency)

A typology of methods – 1 Type A: Methods for different sub-processes of GSBPM: Integrate data (5.1) Edit & Impute (5.4) Weighting and estimation (5.6 et. al. ) Alignment of statistical units and measurements (hidden in different sub-processes)

A typology of methods – 2 Type B: Methods which define a workflow for statistical production Workflow for producing statistical products from administrative data (register based census) Workflow for producing statistical products from administrative data in combination with survey data Workflow for creation a statistical register Workflow for updating statistical registers

A typology of methods – 3 Useful sources for methods (mainly type A methods): ESS.VIP Admin WP 2: Statistical methods https://ec.europa.eu/eurostat/cros/content/wp2-statistical-methods_en ESSnet MEMOBUST https://ec.europa.eu/eurostat/cros/content/memobust_en ESSnet Data integration https://ec.europa.eu/eurostat/cros/content/data-integration_en A.&B. Wallgren: Register-based Statistics

Conditions for the use of methods – 1 Besides the usage scenario the application of methods depend on some conditions for the data Structural conditions for the data Possible structures: micro-data, macro-data Temporal structure: time series (longitudinal data) Due to the fact that physical integration is done step by step it is sufficient to consider the structure only for the use of two datasets

Conditions for the use of methods – 2 Possible combination of the structural conditions: Both datasets are microdata Both datasets are macro-data A combination between micro-data and macro-data Systematic treatment of different temporal structures is at the moment not considered

Conditions for the use of methods – 3 Representation of the envisaged population: Complete vs. incomplete Disjoint vs. overlap Representation of the variables of interest: Unique representation (variable only in dataset) vs. multiple representation Completeness with respect to statistical units vs. incompleteness (missing values)

Conditions for the use of methods – 4 Conditions specific to Type A methods (GSBPM sub-processes): Characterisation of the variables (numeric, categorical,….) Information about possible errors in the data Conditions specific to Type B methods: The basic methods are a detailed specification of the workflow and conceptual data modelling (for statistical units Conditions for detailed specification of some of the sub-processes (e.g. mass imputation, or alignment of measurements)

Structure of the guidelines – 1 The guidelines are organised as follows Introduction The use of administrative data in statistical production (Basically this presentation) Estimation methods for specific GSBPM and sub-processes in the case of micro-data and time series (editing, imputation, weighting and estimation Alignment of units and measurements The Integration of statistical and administrative micro-data Macro-integration Using administrative data for creation and maintenance of registers Direct usage of administrative data for statistical products

Structure of the guidelines 2 The chapters 3 – 8 are self-contained and can be read independently The structure of chapters 3 – 8 is as follows: Description of the problem (usage scenario) Conditions on the data for the possible methods Short description of the possible methods Evaluation of the methods: A decision tree branching according to the conditions If there are more than on methods in a terminal node the methods will be ordered from recommended up to not recommended