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The Distance Between Perception and Reality in the Social Domains of Life

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Handbook of Happiness Research in Latin America

Part of the book series: International Handbooks of Quality-of-Life ((IHQL))

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Abstract

This chapter provides an overview of the psychological biases behind the striking gaps between perception and reality in four social domains—health, employment, the perception of security, and social ranking. Biases associated with cultural values are very relevant with respect to health and job satisfaction. Affect and availability heuristics are the dominant sources of bias in perceptions of security. The formation of subjective social rankings appears to be less culturally dependent and more dependent on the level of socioeconomic development of each country. Understanding the gaps between objective and subjective indicators may help clarify public debate on social policy.

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Notes

  1. 1.

    Furthermore, some “objective measures” may also be subjective inasmuch as they are constructs based on the subjective criteria of experts.

  2. 2.

    All of the perception data mentioned in this paragraph come from the Gallup World Poll of 2006 for Latin America. Further details are presented in the relevant sections below.

  3. 3.

    See the exact wording of this question below.

  4. 4.

    Since culture—as well as personality—refers to those factors that construct what individuals are and how they see themselves and the world around them, perception is necessarily shaped by those factors.

  5. 5.

    And, as such, may be said to be “subjective” or “culturally biased”.

  6. 6.

    For a broader psychological perspective of survey response issues see Tourangeau et al. (2000). A brief overview of the literature on the psychology of survey response is provided by Farrall et al. (2009, pp. 53–59).

  7. 7.

    In my own econometric studies, I have assessed the influence of optimism on job satisfaction (Chaparro and Lora 2013), on health satisfaction (Lora, 2011), and on subjective social rankings (Lora and Fajardo 2013).

  8. 8.

    Sommerfeld et al. (2002) and Salomon et al. (2004). Jürges (2007) has found that an important part of cross-country differences in self-reported health in ten European countries can be attributed to differences in response styles, possibly reflecting differences in beliefs, values, and expectations. Lindeboom and van Doorslaer (2004) and van Doorslaer and Gerdtham (2003) have found evidence of reporting differences across age-sex groups but not across socioeconomic groups in Sweden and Canada, while Milcent and Etile (2006) provide evidence of reporting differences by income but only in the middle categories of self-rated health. Groot (2000) analyzes the impact of age biases in the United States and finds that the scale of reference of a subjective health measure changes with age.

  9. 9.

    Health perceptions of the general populations of Latin American countries have been the subject of very few studies. Suárez-Berenguela (2000) calculated socioeconomic gradients of health-assessed health status in Brazil, Jamaica, and Mexico and of self-reported symptoms of illness or accident in those same countries, plus Ecuador and Peru. He found normal gradients, although they were substantially less steep than the objective indicators of morbidity or mortality. Dachs et al. (2002) studied inequalities in self-reported health problems in 11 Latin American countries. They found that inequalities (by quintiles) were small, which they attributed to cultural and social differences across socioeconomic groups in the perception of health.

  10. 10.

    The two measures are, respectively, total factor productivity computed as a residual from a Cobb-Douglas production function with capital and education-augmented labor, and a measure of labor productivity where labor is augmented by education. These productivity calculations come from Daude and Fernández-Arias (2010).

  11. 11.

    The correlation is −0.004 for the 18 Latin American countries with data on self-employment and employment in firms of less than ten workers in 2007 (or closest year) computed by SEDLAC from official household survey data.

  12. 12.

    Warr (2003) provides an excellent summary of this literature.

  13. 13.

    While in the standard ordered probit model, Denmark and Finland are ranked at the top of the seven countries, when vignettes are used as anchors to re-scale the model, Scandinavian countries are ranked lower and the Netherlands is found to have the highest level of job satisfaction.

  14. 14.

    Essentially, the perception of insecurity is stronger among women and older people, presumably because they are more vulnerable, in spite of the fact that these groups are less prone to be crime victims. Individuals with more education and higher incomes are found in some studies for developed countries (but not for Latin America) to be less fearful of crime.

  15. 15.

    To test the importance of proximal cues, Lee et al. (2010), at the peak of the flu pandemic fear of 2009, arranged for participants in a field experiment to encounter a sneezing person before answering a set of questions about different types of risk. Those exposed to the cue considered that the risk of an “average American” to die before the age of 50 from a crime or accident was 41.2 %, while those not exposed to the cue estimated that risk at 27.9 %.

  16. 16.

    See a brief survey in Vilalta (2012) and a discussion of the literature in Farral et al. (2009, pp. 91–101). Additional evidence is reported in Wyant (2008) for Philadelphia, United States; and in Russo et al. (2011) for Italian counties.

  17. 17.

    O’Connell and Whelan (1996) found that the perception of crime prevalence in Ireland is independent of personal experience of victimization. However, the small sample of this study (623) casts some doubt on the conclusion, given the relatively low frequency of crime events in the sample.

  18. 18.

    However, in one of three samples used in the study (covering the metropolitan area of Mexico City, January 2011), only indirect victimization was found to be associated with high significance with feelings of insecurity.

  19. 19.

    For an exhaustive discussion of the theoretical and empirical literature see Farral et al. (2009).

  20. 20.

    This is also the case outside Latin America. For instance, only 6 % of all individuals ranked in the richest third of South Africans in terms of actual per capita household income perceive that they are among the richest third.

  21. 21.

    Measured with a summary index of the five health conditions assessed through the EQ-5D instrument described in the health section above.

  22. 22.

    Admittedly, however, some people may derive pecuniary benefits from their relation with others or their participation in social or religious organizations.

  23. 23.

    These computations make use of the fact that, since income affects subjective social ranking, the effect of any other variable on social ranking can be expressed in terms of income. The actual calculations presented in this paragraph are based on the coefficient estimates in Lora and Fajardo (2013, Table 5) for a hypothetical 30 year-old woman who lives in Brazil, has one child, a high education level, is employed, has friends and religious beliefs, and lives in a house with access to all public services.

  24. 24.

    As pointed out by a commentator, it may also be due to a social desirability bias, as interviewees may feel ashamed to declare themselves relatively well-off or rich. The same commentator suggested an alternative explanation: by placing themselves subjectively in the middle rungs, individuals mitigate the disutility associated with inequality, which results from feeling envious of those who are richer and from feeling regret for having more than those who are poorer, as argued by Fehr and Schmidt (1999). These hypotheses have not been tested in this context.

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Lora, E. (2016). The Distance Between Perception and Reality in the Social Domains of Life. In: Rojas, M. (eds) Handbook of Happiness Research in Latin America. International Handbooks of Quality-of-Life. Springer, Dordrecht. https://doi.org/10.1007/978-94-017-7203-7_30

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