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Further data linking with WERS 2004

Further data linking with WERS 2004. John Forth WERS 2004 Information & Advice Service. Rationale for data linking. Rationale 1: Extend the information set for each workplace or employee Examples: Augment workplace records with data on financial performance

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Further data linking with WERS 2004

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  1. Further data linking with WERS 2004 John Forth WERS 2004 Information & Advice Service

  2. Rationale for data linking • Rationale 1: • Extend the information set for each workplace or employee • Examples: • Augment workplace records with data on financial performance • Augment workplace records with data about wider enterprise • Augment workplace or employee records with contextual data about the industry sector or occupation

  3. Rationale for data linking • Rationale 2: • Reduce measurement error in a particular item • Examples: • Compare WERS data with external source of information on legal status or foreign ownership • Compare WERS financial performance data with other sources

  4. Rationale for data linking • Rationale 3: • Extend the information set for another dataset • Example: • Add workplace data from WERS to a separate workplace or employee-level dataset

  5. Issues in data linking • Confidentiality • Extent and reliability of links • Measurement error • Loss of information See also: Chesher and Nesheim (2006) DTI Occasional Paper No. 3.

  6. Existing instance of linked data ONS Annual Respondent Database (ARD2) matched onto WERS 2004 • Data on financial performance of business units (from ABI) • 847 (48%) of XS workplaces in trading sector (ASTATUS1<=8) have an ABI 2004 return in ARD2 • Offers data on value-added, profitability, labour costs, capex • Low survey and item non-response • Prospect of data for multiple years • Issue: many returns (~80%) concern whole enterprise • One solution: combine with FPQ data

  7. Existing instance of linked data ONS Annual Respondent Database (ARD2) matched onto WERS 2004 • 1998-2004 Panel Survey: 166 (~25%) of trading sector w/ps have financial data for both years • Issue: fewer than 30 have site-level data for both years; no WERS Financial Performance Questionnaire • General issue: available only in ONS Virtual Micro-data Lab Further info: Forth and McNabb (2007) WIAS Technical Paper No.1

  8. Work in progress ONS Business Structure Database matched onto WERS 2004 • Version of the IDBR prepared for research use • Provides info on legal status and country of ownership • Provides information on enterprises’ internal structure • Provides info on demographic events: birth, death, merger, takeover • BSD record available for 2,143 (93%) of XS workplaces • One potential use: identify siblings for 714 (45%) of the XS workplaces that belong to multi-plant enterprises

  9. Work in progress WERS 2004 matched onto the ONS Annual Survey of Earnings and Hours (ASHE) • Annual survey of 165,000 employees • Detailed information about hours and earnings (basic, overtime, incentive payments, pension arrangements) • WERS can provide more information about the employer • Around 5,000 ASHE records (3%) link to XS workplaces • In most cases (95%), there are 2+ ASHE records per workplace • One potential use: examine union impact on composition of earnings

  10. Further opportunities at ONS • Surveys deriving from IDBR (to be investigated): • Community Innovation Survey (CIS4): data on product/process innovation and R&D from 16,000 enterprises over period 2002-2004 • E-commerce Inquiry: annual survey of 10,000 enterprises covering access to ICT and e-commerce activity • Annual Inquiry into Foreign Direct Investment: annual survey of 16,000 enterprises covering foreign ownership and financial flows

  11. Matching on summary data items Possible options (dependent on demand): • Industry: • Levels: down to SIC 2003 Class / Sub-class level • Examples: aggregate productivity, profitability, labour costs • Occupation: • Levels: down to SOC 2000 Minor Group • Examples: composition by gender, ethnicity, age; average qualifications; average wages

  12. Matching on summary data items Possible options (dependent on demand): • Geography: • Levels: any postcode-based classification that does not compromise the anonymity of respondents. See National Statistics Postcode Directory for options. • Examples: unemployment and vacancy rates by TTWA; profile of labour force in TTWA; urban/rural indicator.

  13. Comments and suggestions WERS Information and Advice Service URL: http://www.wers2004.info Email: wers2004@niesr.ac.uk Telephone: +44(0) 20 7654 1933

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