Page 74 - Special Topic Session (STS) - Volume 3

STS515 Steve MacFeely
crisis those efforts have intensified with a raft of new indices attempting
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to measure and blend human, natural and production capital or the social,
economic and environmental pillars of development. Linked, is the
emergence of climate crisis and environmental degradation. For example,
how can we put a value on the environment, on biodiversity, on
ecosystems, or spirituality or aesthetic? Challenges regarding potential
double counting, designing a single valuation methodology that works
equally well across all domains, and problems with data availability all pose
difficulties. For example, most economic valuations are based on marginal
changes to ecosystems on the assumption that they are stable, but in
reality, little is known about the stability of ecosystems and their response
to change - a critical threshold could trigger structural changes, at which
point the marginality assumption and the valuation may no longer hold.
Another serious policy concern is ‘end of work’ or a ‘jobless future’ – the
disruptive blend of technology, automation and task based labour that has
been dubbed the 4 industrial revolution. The shift towards non-standard
th
work patterns is blurring the distinction between formal and informal
employment. The variety of new non-standard or on-demand employment
contracts mixed with robotics and other technological advances are posing
challenges for those trying to classify and measure this new gig economy.
4.4 Political Economy: Statisticians should also be aware of the wider context on
how data are being used and the important debates underway in which data
or statistics are in one way or another at the heart. At the core of official
statistics is the ambition to provide impartial information , yet no statistic is
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truly impartial – every statistic is the product of many decisions and
assumptions, conscious or subconscious. It is important that students
understand this and that the choices they make have an impact. The selection
of variables in a composite index; whether to weight or not; or the treatment
of outliers all affect, not only the basic result but perhaps also the alignment
to political or economic ideologies. This realization becomes especially
important when thinking about ‘evidence based decision making’ versus
‘evidence informed decision making’ or ‘Governance by numbers’ [8]. This is
a growing concern for many as algorithms are playing an increasingly greater
role in our lives, from deciding whether we get a loan to whether we are short
listed for an interview.
Many other interesting debates are underway, not least, the ‘End of
Theory’ argument posited by Anderson [9] that causation no longer
matters, and that with big data, only correlation matters . Should ‘open
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11 European Commission Beyond GDP; OECD Better Life Index; and UNEP Inclusive Wealth
Index.
12 UN Fundamental Principle of Official Statistics No. 1
13 For the record, I think this argument is nonsense, but it is an interesting debate.
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