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Employer-Employee Feasibility Report Released

Published: Wed 15 Oct 2003 11:14 AM
Linked Employer-Employee Feasibility Report Released
A new report confirming the feasibility of successfully integrating existing employer and employee information was released today by Statistics New Zealand. Feasibility Report: Linked Employer-Employee Data (LEED) is the result of a collaborative effort between Statistics New Zealand, the Department of Labour and the Inland Revenue Department.
"The report marks the completion of the first stage of a proposed development that has the potential to make one of the most significant advances in statistical information in recent years," says Brian Pink, Government Statistician.
The feasibility report is the culmination of 12 months' investigation into the viability of creating a linked employer-employee dataset (LEED). This development will provide new insights into the operation of the labour market and business performance. Prototype series have been created on job and worker flows, employment tenure, multiple job holding and business demography. These measures have the potential to provide new and improved official statistics that are useful for strategic labour force and business planning (for regional councils, strategic planners, central government, business planning). In addition, the infrastructure also has the potential to provide useful statistical information on policy questions such as skill shortages, firm dynamics, business performance, benefit to work transitions, productivity, human capital development, multiple job holding, precarious work, and gender pay issues.
The LEED initiative follows the successful development of similar datasets by a number of European and North American countries including the USA, Canada, France, Sweden and Germany.
While still under development, these initial findings have been released to invite comment from potential users on the concepts, sources and methods employed in the creation of this dataset, and on the value of the proposed official statistical series.
The large-scale use and integration of administrative data for statistical measurement presents new challenges for Statistics New Zealand. The feasibility report summarises these major challenges and also outlines possible new statistical outputs.
The report brings together the findings of a suite of technical papers that discuss issues relating to proposed new official employment and business statistics, policy research uses, data quality and methodology, confidentiality, data security and privacy.
The conclusion that this initiative is feasible has been reached following an examination of the quality and characteristics of the input data, its ability to support the proposed use and an examination of the legal context and issues surrounding the imperative to protect individual privacy and data confidentiality.
LEED is another step towards deriving new information through improved access to administrative data sources. By using existing information, this development will make no additional demands on business or the public. The universal nature of the administrative data used in LEED makes possible the production of many new statistics that could not otherwise be compiled without imposing an excessive burden on respondents.
The resulting statistics have the potential to inform policy development, monitoring, debate, and decision-making both within government and by the wider community.
In addition, LEED has potential to reduce or refocus existing surveys of employment, leading to a reduction in respondent load.
Initial funding for this work was obtained from the Cross-Departmental Research Pool for two years from June 2002 to July 2004. The Department of Labour has provided additional funding and support from the Skills Action Plan to facilitate input from local and international subject area experts. These collaborative efforts have enhanced the speed and quality of the development.
The report is available free from the Statistics New Zealand website (www.stats.govt.nz).
Brian Pink
Government Statistician

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