Research for Statistics

Tim Holt

Three Presentations

• Hand: Drivers for research – natural development and ‘blue skies’

• Scheuren: Research agenda - foresight, insight and hindsight. Environment: slow take-up, lack of innovation

• Hulliger: Research environment: need more research, stronger research community – suggestions for progress

General Themes

• The drivers for the research agenda?

• Unhelpful drivers

• The specific to the general to the specific

• What is research output?

• Should NSIs be risk averse?

• Who is the research community?

The drivers of research:Hand “the development of statistics is driven by

exogenous factors”

• Supply side: automated data acquisition, large administrative data sets, file merging, computing power

• Demand side: policy needs (e.g. credit crunch), devolution, regionalisation, EU enlargement, economic convergence, civic cohesion, migration …

Drivers: questions

• Do sources determine outputs?

• How to anticipate policy areas before they are identified?

• How should research funding be divided between applications and methods?

• How can ‘blue skies’ work be identified?

Unhelpful Drivers?

• The ‘policy fashion’ of successive Framework Programs

• Lack of continuity

• Focus on current policies to the detriment of future needs?

• Question: Is it possible to improve the funding regime?

From the specific to the general to the specific

• Specific problems – general methodology – new specific applications

• Abstraction, general methodological development and customizing new applications all take skills

• Some problems: abstraction to general methodological framework is well identified (e.g. small area estimation, disclosure control)

• Some problems not so clear

Questions

• What should be funded as research?

• Is it necessary to formulate a general methodological approach to justify funding?

• What is research and what is development and does it matter?

• Who should fund what?

What is research output?

• Publications?• Other documents (standards, manuals etc)• New generalised methods?• Take-up and implementation of research

findings?• By initiators or others?• Improved statistics?• Sustained research capacity?• An innovation culture based on research and

evaluation within each NSI?

Impediments to innovation

• Budget• Organisational inertia• Users dislike change – time series• Risk aversion

– New methods may contain unidentified risks– Innovation carries risk– Dangers to the reputation of the NSI -public

confidence

• BUT Lack of innovation leads to erosion of usefulness, hence loss of public confidence

Are there areas to encourage more innovation

• Exploratory products

• Rapid response analyses

• Developmental outputs

• All vehicles for research findings

Who is the Official Statistics research community?

• Within NSIs (within the EU)

• Other organisations (Market research – Hulliger)

• Academics: sub-contractors under ESSnet

• Official statisticians outside the EU