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Recommended Practices for Editing and Imputation in the European Statistical System: the EDIMBUS Project* Orietta Luzi (Istat, Italy) Ton De Waal (Statistics.

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Presentation on theme: "Recommended Practices for Editing and Imputation in the European Statistical System: the EDIMBUS Project* Orietta Luzi (Istat, Italy) Ton De Waal (Statistics."— Presentation transcript:

1 Recommended Practices for Editing and Imputation in the European Statistical System: the EDIMBUS Project* Orietta Luzi (Istat, Italy) Ton De Waal (Statistics Netherlands) Beat Hulliger (Federal Statistical Office, Switzerland) *Partially fund by Eurostat UNECE Work Session on Statistical Data Editing Bonn, 24-27 September 2006

2 Outline Project aim Steps of the project The state-of-the-art Survey Concluding remarks

3 Aim of the Project (January 2006-June 2007) Developing a Recommended Practices Manual (RPM) focusing on the specific area of E&I in cross-sectional business surveys (EDIMBUS) Project partners –ISTAT Italy (coordinator) O. Luzi, M. Di Zio, U. Guarnera, A. Manzari – CBS Netherlands T. De Waal, J. Pannekoek, C. Templeman, J. Hoogland –SFSO Switzerland B. Hulliger, D. Kilchmann

4 The RP Manual Aim of the Manual To offer a support for the design, the implementation and testing of E&I procedures in cross-sectional business surveuys To contribute to the standardization of E&I processes at Statistical Agencies Recommendations How to do things: –Which method should be selected, depending on the conditions –Checklist of what should be done when dealing with a given data problem or when adopting a given methodological solution

5 The RP Manual Covered topics methods and practices for E&I in cross-sectional business surveys methods and practices for designing an E&I strategy methods and practices for evaluating the effects of E&I in cross-sectional business surveys methods and practices for documenting E&I activities

6 Steps of the Project 1)State-of-the-art in the EDIMBUS field (literature review and questionnaire) 2)Development of a draft version of the RPM (definition of a template, work assignment) 3)Feasibility testing: Evaluation of the draft RPM in different national settings 4)Revision of the draft RPM and production of the final version of the RPM

7 Step 1) State-of-the-art survey Main objectives E&I strategies Methods and practices currently adopted in business surveys Cost of E&I Supporting tools adopted in business surveys Evaluation and documentation in business surveys Existing tools for supporting the design of E&I procedures: guidelines, manuals,… Access to the within-NSI literature

8 Step 1) State-of-the-art survey Questionnaire and glossay mailed to Partner´s Institutions The National Statistical Institutes of the European countries Three overseas statistical authorities: ABS, Statistics Canada, US Census Bureau (29 Countries involved) Response rate ~80%

9 Survey results: responses by type of survey SBS: Structural Business Surveys STS: Short-Term Business Surveys EC: Economic Censuses

10 Survey results: current methods and practices

11 Survey results: cost of editing Question: Could you range the used resources for the E&I process in respect to the workload of the whole survey?

12 Survey results: adopted tools Use of Computer Aided Interviews –60% of surveys use electronic questionnaires as either unique solution for data capturing, or in combination with traditional paper questionnaires Use of Generalized software –19 surveys (39%) declare to use some type of such tools –In most cases software consists of ad-hoc SAS programs –Actual generalized software are Banff (Canada, Italy), Blaise (Slovenia), SLICE (Netherlands), two different tools developed by Eurostat (Poland,Italy)

13 Survey results Preliminary tests of E&I –Answered negative 50% of times. Among them: 50% not enough resources 45% not suitable data available Documenting E&I –82% of the analysed surveys produces some (standard?) documentation of E&I 75% Technical reports 50% Methodological reports 62% computes indicators

14 Survey results Supporting tools for the design of E&I strategies –Only 4 Countries (Canada, Finland, Norway, UK) declare to have developed some kind of such tools. –Other affirmative responses generally refer to Eurostat manuals, UN/ECE documents, “non-standard” methodological documentation developed at the Statistical Agencies Control of E&I at Statistical Agencies –Only 5 Countries declare to have an established procedure for obtaining approval for the E&I strategy of a survey

15 Concluding remarks 1. Costs of E&I Answers are heterogeneous since each survey manager uses its own definition for measuring the “amount of resources spent for E&I” However, it results that E&I is perceived as the most time and resources consuming survey phase An open problem is how to measure costs of editing

16 2. E&I definitions and concepts High heterogeneity in definitions and concepts adopted in the different survey contexts, not only at International, but also at National level As a matter of fact, while methods and practices for particular problems are more or less known, the communication about E&I seems still under-developed There is no common understanding among survey managers and methodologists and across institutions (or even within) of what is E&I Concluding remarks

17 3. Standardization of E&I strategies It is relatively rare to find documents about the approach one should follow in designing an E&I strategy There is a real need for developing and disseminating standard tools like RP in the specific area of E&I …but at which level E&I processes for cross-sectional business surveys can be standardized? Concluding remarks

18 4. Generalized software and other tools for E&I In the area of business surveys Statistical Agencies are intensively adopting tools for anticipating editing activities at the data capturing stage The use of other sources of information at the E&I stage is intensive too Few Countries use generalized software. Reasons? –lack of knowledge of (functionalities of) already existing software –high costs needed to develop/integrate generalized software in the existing survey processes, often characterised by very specific data problems Concluding remarks

19 Thank you for your attention


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