"The measurement and statistical issues“

Professor Denise Lievesley

Head of School of Social Science and Public Policy,

King’s College London and

Chair, European Statistical Advisory Committee

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What you measure matters

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Welcome the initiatives ‘GDP and beyond’

We already have a rich array of data describing the social circumstances of our populations

Over-attention on economic variables to the exclusion of others

Over-attention on nation as unit of analysis

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Evidence that inequalities within our societies are growing, exacerbated by the recessions

Leading to disruption and insecurity Countries with the greatest homogeneity

achieve the most

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Concern about an unrelenting pursuit of growth

At the expense of the poorest And of the environment

(the two are interconnected)

Behoves us to give visibility to the disenfranchised in our societies

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Quality of data

Currency and

punctuality

Currency and

punctuality

Relevance to policy

Relevance to policy

Potential for disaggregation

Potential for disaggregation

Coherence across sources

Coherence across sources

Clarity and transparencyClarity and

transparency

Consistency over time and space

Consistency over time and space

Validityand

reliability

Validityand

reliability

Comparability through

standards

Comparability through

standards

Accessibility and affordability

Accessibility and affordability

Efficient use of resourcesEfficient use of resources

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Purposes of cross-national data

To learn from one another (contrast and similarity) For purposes of national accountability (the indicator

movement) To build a greater global understanding through

comparison and through multiple instances of the same phenomena

To aggregate across national boundaries for a regional or global picture

To accelerate progress through sharing resources To make research more credible/ defensible recognising

that research which displeases is attacked rather than accepted

To distance the research from the political process (tension – policy relevance v. autonomy)

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Challenges to comparability

Language Culture Social systems and structure Administrative systems Ideology and politics Economics and resources Context – events Different methodologies and types of

methodological expertise (often deeply ingrained)

Shared national initiatives or a European initiative? Comparative by design Compiling national data in a European

framework (post-hoc comparability)

Both?

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Importance of partnership between the official statisticians and a broader ‘user’ community Building trust – a prerequisite for the collection

and use of data Advocating for the resources Sharing data – not all collected by official

agencies Creating expertise, adding value Communicating the data (even if they are

uncomfortable for our governments Building statistically literate communities

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Ideal scenario

Long term partnerships of both users and producers of research who Select topics pertinent to their situations and

policy needs Work together to develop common definitions

and instruments Combine the deep understanding of the ‘local’

and the perspicacity of the stranger

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Under-exploitation of existing data

There is growing awareness that failure to exploit the full potential of data has costs for society and many institutions and agencies now espouse the aim of ensuring that data are used as extensively as possible.

The International Statistical Institute’s declaration on professional ethics states that “A principle of all scientific work is that it should be open to scrutiny, assessment and possible validation by fellow scientists.”

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“Publicly funded research data are a public good, produced in the public interest. As such they should remain in the public realm. Availability should be restricted only by legitimate considerations of national security restrictions; protection of confidentiality and privacy; intellectual property rights; and time-limited exclusive use by principal investigators.”

Data grow in value the more they are used, unlike most commodities which are diminished with use.

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Better utilisation of what we have

Fresh data collection takes time and resources

Current financial constraints are impacting upon our ability to collect new data

Secondary data analysis can take place in resource–constrained (including a time-constrained) environment

Compliance costs important especially in small countries and in surveys of elites, businesses, institutions

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Conclusion Welcome this EESC hearing Believe in the importance of the further

development and greater exploitation of these ‘complementary’ data

So essential to build policies in our countries which address the quality of life of our citizens as well as environmental degradation

Developments must be underpinned by sound statistical methodology

Partnership with user community is vital to build the trust necessary to enhance our understanding of the progress of our societies

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