Bias in the Relative Assessment of Happiness,Political Stance, Height and Weight
AbstractCognitive biases have been a recognised feature of research into human behaviour since at least Kahneman and Tversky’s ground-breaking work of the 1970s. We find that such biases extend into the realm of perceptions about relative happiness and we compare and contrast this phenomenon across three other characteristics : height, weight and political stance. Our findings indicate a powerful and consistent bias in the way individuals perceive their place in the population distribution. In particular, those at extremes perceive a population distribution that is incorrectly and heavily biased towards themselves,irrespective of whether the characteristic is objective and easily observed or not.
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Bibliographic InfoPaper provided by University of Warwick, Department of Economics in its series The Warwick Economics Research Paper Series (TWERPS) with number 943.
Date of creation: 2010
Date of revision:
This paper has been announced in the following NEP Reports:
- NEP-ALL-2010-09-18 (All new papers)
- NEP-HAP-2010-09-18 (Economics of Happiness)
- NEP-NEU-2010-09-18 (Neuroeconomics)
- NEP-POL-2010-09-18 (Positive Political Economics)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Easterlin, Richard A, 2001. "Income and Happiness: Towards an Unified Theory," Economic Journal, Royal Economic Society, vol. 111(473), pages 465-84, July.
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American Economic Review,
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- DiTella, Rafael & MacCulloch, Robert & Oswald, Andrew J., 2001. "Preferences over inflation and unemployment: Evidence from surveys of happiness," ZEI Working Papers B 03-2001, ZEI - Center for European Integration Studies, University of Bonn.
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- Vincenzo Carrieri & Maria De Paola, 2011. "The Effects Of Peoples’ Height And Relative Height On Well-Being," Working Papers 201110, Università della Calabria, Dipartimento di Economia, Statistica e Finanza (Ex Dipartimento di Economia e Statistica).
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