We Do Not Have the Same Tastes! Evaluating Individual Heterogeneity in the Preferences for Amenities

Abstract

It is widely recognized by scholars that amenities affect the individual well-being. Ample empirical evidence has been provided for developed countries, although this analysis for developing economies is scant. The aim of this paper is to study the association between locational specific characteristics and self-reported measures of subjective well-being. We focus our analysis in Chile, a developing country located in South America endowed with a rather heterogeneous set of amenities across cities. Using data from several sources to account for both natural and urban city amenities along with individual traits, our first results suggest that natural and urban amenities do affect the level of subjective well-being across Chilean cities. Afterwards, we allow for the estimated parameters associated to amenities vary to characterize the whole distribution rather than a single average parameter. This analysis uncovers the existence of unobserved individual heterogeneity, that is, individuals display different tastes for amenities not captured by observed traits, and consequently compensating variations associated to amenities differ across the sample. These results provide valuable elements to policy makers and city planners to the design of policies that enhance the population well-being and to the understanding of the development of cities in developing economies.

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Fig. 1
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Notes

  1. 1.

    The concept of SWB, defined as “a person’s cognitive and affective evaluations of his or her life” (Diener et al. 2005), has been used in different fields such as economics, sociology and psychology to evaluate the key factors affecting individuals’ well-being. In general, SWB is measured by survey questions about individuals’ self-perception about different domains such as life satisfaction, happiness and quality of life. Although, some debate of the correct interpretation of each of these domains persists (see for example, Veenhoven 2000, 2017), in economics—the field from which the theoretical framework used in this article is derived—the measurement of individual welfare using data on reported subjective well-being has become popular and has served as an empirically adequate and valid approximation for individually experienced welfare (Frey et al. 2009). Furthermore, the empirical evidence seems to support the theoretical link between SWB and the unobserved utility. For example, Benjamin et al. (2014) and Perez-Truglia (2016) using behavioral experiments and observational data, respectively, find that SWB is a reliable proxy for individuals’ utility and preferences. Thus, in the economics literature, these concepts are often used interchangeably (see Di Tella and MacCulloch 2006; Ferreira and Moro 2010) and we adopt the same approach in this study.

  2. 2.

    In general, studies using a random coefficient approaches use stated preferences surveys.

  3. 3.

    Although the CASEN has been conducted every 2 or 3 years since 1987, we only use the 2013 version because it is the only wave containing questions about individuals’ life satisfaction.

  4. 4.

    For some applications, see Falco et al. (2015) and Greene et al. (2014).

  5. 5.

    Note that for each random parameter we need an integral.

  6. 6.

    For dummy variables, the marginal effects correspond to a discrete change from 0 to 1. The marginal effects for the rest of the categories are presented in Table 5 in “Appendix”.

  7. 7.

    Standard errors for the marginal effects are computing using Delta Method.

  8. 8.

    This ratio was multiplied by 10,000 to get a meaningful measure.

  9. 9.

    This is computed as \(100 \times \varPhi \left( {\frac{{\hat{\alpha }_{k} }}{{\hat{\sigma }_{k} }}} \right),\) where \(\varPhi\) is the cumulative standard normal distribution, \(\hat{\alpha }_{k}\) and \(\hat{\sigma }_{k}\) are the mean and the standard deviation of the coefficients estimated in column 3 of Table 3, respectively.

  10. 10.

    The unconditional distributions were computed using 10,000 draws from the estimated distribution.

  11. 11.

    For more details about the CV distribution, please see Daly et al. (2012).

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Acknowledgements

The authors acknowledge and appreciate the wise comments of two anonymous referees and the financial support of CONICYT/Chilean Fondecyt 11170018 “City differences in the return to schooling”.

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Appendix

Appendix

See Table 5.

Table 5 Marginal effects on the probability of reporting a specific level of life satisfaction

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Ahumada, G., Iturra, V. & Sarrias, M. We Do Not Have the Same Tastes! Evaluating Individual Heterogeneity in the Preferences for Amenities. J Happiness Stud 21, 53–74 (2020). https://doi.org/10.1007/s10902-019-00081-2

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Keywords

  • Subjective well-being
  • Amenities
  • Heterogeneous preferences
  • Random parameters models
  • Compensating variation

JEL Classification

  • C35
  • I31
  • Q51