SMART2 A web2.0 platform for citizens
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1 SMART2 A web2.0 platform for citizens S. Falorsi, A. Fasulo Paris, OECD Conference Centre, 27/10/2014
2 Contents: Why SMART Current version of SMall ARea Tool (SMART) Extension of SMART: SMART2 Give some documentation about Case Studies Examples of new outputs New user interface of SMART2
3 Why SMART It is important to outline that the SMART platform was set up because strongly requested by the Local Authorities to have an instrument to study the local phenomena of interest in order to drive policies and funds based on a methodology validated by Istat. SMART is a Web2.0 platform set up by Istat to give citizens a tool to study the phenomena of labour market and health labour market and health are domains of interest belonging to the set of indicators of well-being at local level. The tool gives to the users a methodology to compare the official data available on line with the crowd sourced data uploaded by the user.
4 Current version of SMART Why SMART? Construction of an information web system to produce small area estimates in the labour market In recent years there has been an increasing need for local governments, Istat Regional Offices and Regions (Society among Italian Regions CISIS) for labour market data at unplanned subregional levels in order to optimize local economic planning activities Activation of a project co-funded by CISIS: first version of SMART released in 2009
5 Current version of SMART Access to SMART Access to the web system only after registration Presence of disclaimer on using results A user guide and a methodological report are available online
6 Current version of SMART SMART Home page -
7 Current version of SMART Handling requests Parameters of interest: yearly employment and unemployment rate estimates Domains: standard areas (provinces or LLMAs) or user-defined areas (aggregation of municipalities) Auxiliary information for small area estimators: standard demographic classes (cross-classification of gender crossed 14 age classes) and user-defined area level variables
8 1. Current version of SMART SMART Handling requests
9 Current version of SMART Implemented small area estimation methods All the methods implemented in SMART are model based estimators based on linear mixed models Area level synthetic predictor Area level EBLUP Unit level synthetic predictor Unit level EBLUP Unit level EBLUP using spatial correlation among area random effects
10 Current version of SMART Output Notification of the small area estimation method chosen by the web system on the basis of Absolute Relative Error (ARE) and Average Squared Error (ASE) Parameter estimates and MSEs for the selected small area estimator The system does not produce official estimates Diagnostic to check the validity of the assumptions underlying the model Ability to save tables and charts in Excel and jpeg files
11 Future version of SMART (SMART2) Data base extension: 1. EUSILC Survey: income 2. Multipurpose Health Survey: use of health services and disease prevalences and.. Other social surveys useful for well-being statistics e.g. Consumer Expenditure Survey Survey on Living Conditions
12 Future version of SMART (SMART2) Codes to obtain estimates an diagnostics written in R instead of SAS English version of the web site Extension of the estimation methods (logistic model added) Greater flexibility in the choice of the set of auxiliary variables and model features when default options are not adopted Subclasses Broad-area Extension of diagnostics
13 Next slides documentation about Case studies and examples of new outputs of the system SMART2 new user interface
14 Documentation
15 Case Studies and examples of new outputs of the system Phases of the estimate process The production process underlying the web system SMART2 follows the guidelines released by SAE ESSnet project (SAE ESSnet, 2012) 1. Choice of target variables and domains of interest 2. Evaluation of the quality of direct estimates 3. Identification of the best set of auxiliary variables and best class of model through appropriate criteria for model fitting 4. Analysis of the quality of several indirect estimators in terms of: MSE Bias (studied by means of appropriate diagnostic tools) Graphical analysis using pie charts, contour lines, box-plots
16 Case Studies and examples of new outputs of the system Labour Force Survey Target variables: Quarterly provincial estimates of the number of employed and people looking for work by sex and age group Results: Distribution of the direct estimates CV Med 75 perc 80 perc 85 perc 90 perc 95 perc 99 perc max quarter quarter quarter quarter
17 Case Studies and examples of new outputs of the system Labour Force Survey Example: Cartograms Quarterly provincial estimates of the number of people looking for job years: estimates (left) and CV (right) with a unit level model
18 Case Studies and examples of new outputs of the system EUSILC Survey Target variables: Provincial estimates of labour income, employment income and equivalent household income Results: Distribution of the direct estimates CV Income Med 75 perc 90 perc 95 perc 97 perc 99 perc max EH income CV distribution of the area level predictor Income Med 75 perc 90 perc 95 perc 97 perc 99 perc max EH income EH income
19 Case Studies and examples of new outputs of the system EUSILC Survey Boxplot and density function Provincial estimates of the equivalent household income Boxplot (left) and density function (right)
20 Case Studies and examples of new outputs of the system Multipurpose Health Survey Target variables: Annual health district estimates of the number of people: obese, who made at least one mammogram screening, who made at least one specialist visit in payment Results: CV of the variable number of obese people Estimator CV% < CV% 33.3 CV% > 33.3 direct EBLUP unit EBLUP area Spatial EBLUP
21 Case Studies and examples of new outputs of the system Multipurpose Health Survey Contour lines with a unit level synthetic estimator LLMA estimates of the number of obese people
22 Case Studies and examples of new outputs of the system Multipurpose Health Survey Choice of age groups (spline functions)
23 SMART2 new interface - Login page Service by Single Sign-On Istat
24 List of different queries Output by means of a unique zip file
25 New query page n.1 Input data divided into 6 pages
26 New query page n. 2
27 New query page n. 3
28 New query page n. 4
29 New query page n. 5
30 New query page n. 6
31 Invio richiesta E possibile rivedere e modificare i dati della richiesta prima dell invio
32 Case Studies and examples of new outputs of the system Multipurpose Health Survey Choice of the default model (AIC and BIC) Model Broad-area AIC BIC LLH Italy Model 1 3 macroareas macroareas Italy Model 2 3 macroareas macroareas Italy Model 3 3 macroareas macroareas Italy Model 4 3 macroareas macroareas
33 Thank you for your attention
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