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Measuring Happiness and Making Policy

Measuring Happiness and Making Policy. Professor Paul Dolan Tanaka Business School Imperial College London. Income versus happiness. A. B. Commute > 1hr/day Over 70 Has children Has degree. C. D. How do we decide?. Is the measure conceptually appropriate?

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Measuring Happiness and Making Policy

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  1. Measuring Happiness and Making Policy Professor Paul Dolan Tanaka Business School Imperial College London

  2. Income versus happiness A B Commute > 1hr/day Over 70 Has children Has degree C D

  3. How do we decide? • Is the measure conceptually appropriate? • Is the measure normatively relevant? • Is the measure empirically useful?

  4. Is the measure conceptually appropriate? • Distinguish between good life and good for the individual • Prudential value is suitable for most policy applications • Both measures mostly contain prudential concerns • The measure should be a complete account of well-being • There is more to life than income (and happiness?) • The measure should measure what it purports to • Allows us to make intra and inter-personal comparisons • There is no gold standard but there is ‘validity’ • Both measures converge with and predicts health etc.

  5. Is the measure normatively relevant? • The measure must be acceptable to policy makers and to the general public, at least in time • Income is attractive because the individual judges what will be in his best interests • But may be questioned if it does not lead to LS • And if preferences are misguided, myopic etc. • Support for LS may depend on language used • LS may be better than happiness, and misery better still?

  6. Is the measure empirically useful? • Is it intra- and interpersonally comparable? • Both shaped by expectations, shaped by circumstances • Brain imaging and physiological measures may help LS • Is it cardinal? • LS performs better than income here • Is measurement error low? • Both measures reasonably stable for most sub-groups • Is it sensitive? • Income changes may not be meaningful but global LS may not pick up small effects of policy • Is it practical? • Both relatively easy to collect

  7. Conclusion • Using different measures may result in different policies • No single measure is ever likely to satisfy all criteria • But well-being measures are used in policy as if they do • Choice really depends on which criteria matter most • Some criteria may be more important in some contexts • And there may be various trade-offs between the criteria • We need more conceptual clarity and empirical evidence • But subjective evaluations may well be the way forward

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