Item 2.2 Use of waivers in business statistics

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Presentation transcript:

Item 2.2 Use of waivers in business statistics 5 April 2017 Working Group on methodology Aleksandra Bujnowska

Waivers Skewed distributions in business statistics: small counts and dominant companies Large number of suppressions in detailed tables Waiver: disclosure permission Legal basis in EU Statistical Law Recent experiences in ProdCom (product statistics) Discussion with Expert Group ongoing

Where can waivers be applied? No legal restrictions, but rather practical Usually no need in social statistics A communication challenge in case data is not directly collected by the Statistical Institute (e.g. administrative data or Big Data) Practical problems in statistics production (need for standardisation and tools)

Do waivers pay off? Recent experiences from ProdCom : SK: from 751 selected companies 41% gave permission for five year; confidential cells down from 87% to 45% for Total quantity HU: asked for permission from all companies in the online questionnaire: 60% agreed; confidential cells down from 77% to 45%

Do waivers pay off? PL: separate survey for giving permission; from 1403 selected companies 1014 responded and 665 gave their consent valid until withdrawal; confidential cells is expected to go down from 43% to 31% NL: asked a five year waiver from 1428, 62% responded and 25% gave permission. Confidential cells down from 65% to below 60%.

Do waivers pay off? The experiment in one domain only (ProdCom) The experiment was not standardised (different selections and approaches) Use of waivers has a robust positive effect on data availability

How can waivers be applied? Systematic (broad) or targeted Before, during or after data collection One instance, one survey or even an overall deal Period of validity These dimensions are not independent. Communication is important: companies should understand what is their risk, but also what could be their advantage

Open issue: tick boxes Is a tick-box on the questionnaire sufficient permission to publish? What are your experiences and/or opinions?

(2,k) dominance rule The rule is on the two largest companies in the cell. The discussion is on what to do in case only the largest has given a waiver. Two interpretations seem to exist: Keep the original rule Calibrate the risk from the perspective of the second largest Should we aim at common understanding or leave both interpretations?

(2,k) dominance rule

(2,k) dominance rule

Passive confidentiality In case of passive confidentiality data is considered non-confidential by default. Companies would have to apply for confidentiality (the reverse of giving a waiver). Easy to implement in statistics production and high impact on data availability. Used efficiently in trade statistics

Thank you for your attention. Wim. Kloek@ec. europa. eu Aleksandra Thank you for your attention! Wim.Kloek@ec.europa.eu Aleksandra.Bujnowska@ec.europa.eu Jussi.Ala-Kihnia@ec.europa.eu