… and the Pursuit of Happiness - Institute of Economic Affairs

… and the pursuit of happiness
the folly of wellbeing in public policy
US economy with the title ‘The use of econometric models as a
guide to economic policy’ (see Klein, 1947).
So the process of measuring the economy metamorphosed
almost overnight into the desire to use these measurements to
predict and control it, exactly as is the case with happiness today.
Enormous optimism was expressed about these possibilities,
despite the salutary experience of the spectacular failures of forecasts
carried out in the summer of 1945 for the rest of that year
and for 1946. Klein himself documented the errors in an article
(see Klein, 1946). Unemployment, for example, had been forecast
to be 8 million but was only 3 million. But he argued that output
could be predicted much more accurately, and that the correct
application of econometrics to this data meant that ‘we can look
forward to much better results in the post-transition period’.
Over 60 years on, we have a massive literature on all the
nuances of economic forecasting, spanning a wide range of statistical
techniques and economic theories, far more sophisticated
than the highly innovative but rather crude methods of Klein in
the 1940s. But it is no exaggeration to say that no progress has
been made in the accuracy of forecasts. At key times, the onsets
of booms or recessions, forecasts prove just as inaccurate as they
were in 1945. The Bank of England Quarterly Bulletin in October
2008, for example, shows that the consensus forecast for UK and
US GDP growth in 2009 in January 2008 was for positive growth
of 2.0 and 2.7 per cent respectively. As late as August, the forecasts
were still for positive growth, despite the fact that by then
both economies were in recession and output was already falling!
The actual out-turn for 2009 was negative growth of 3 per cent in
America and 5 per cent in Britain. There are many such examples.
It is not just that we cannot predict the economy with
any reasonable level of systematic accuracy. We still have no
consensus as to what the drivers of GDP are, and therefore what
the effects of any particular policy might be, even in a qualitative
sense. At the time of writing, for example, one school of
thought, of which Joe Stiglitz is a prominent member, believes
that more fiscal expansion is required to revive growth in the US
and European economies. Another school, in which Robert Barro
is prominent, maintains that fiscal expansion will actually lead to
lower economic activity.
Of course, the fact that economics has made little or no
progress in its ability to predict and control the macroeconomy
does not necessarily mean that the same fate awaits the happiness
index and its devotees. Changes in both real GDP and happiness
over time share a deep common feature, however. Namely, that
they are, across the Western world as a whole, scarcely indistinguishable
from purely random series. There is a small amount
of pattern, of potential information, in the US GDP data, but it
is small. And, more generally, these data series are dominated by
random noise rather than by any consistent ‘signal’. 8
Conclusion
This experience with GDP has a critical implication. It is simply
not possible to obtain systematically reliable predictions of aggregate
happiness indices, any more than it is for GDP. We cannot
predict with accuracy the next shake of a true die, and neither can
we do so for happiness. Further, any statistical relationship which
purports to identify the drivers of happiness (or GDP) over time
8 Interested readers are referred to Ormerod and Mounfield (2000).
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