Segregation and Life Satisfaction

Abstract

Our aim is to cast light on socioeconomic residential segregation effects on life satisfaction (LS). In order to test our hypothesis, we use survey data from Chile (Casen) for the years 2011 and 2013. We use the Duncan Index to measure segregation based on income at the municipality level for 324 municipalities. LS is obtained from the CASEN survey, which considers a question about self-reported well-being. Segregation’s impact upon LS is not clear at first glance. On one hand, there is evidence telling that segregation’s consequences are negative due to the spatial concentration of poverty and all the woes related to it. On the other hand, segregation would have positive effects because people may feel stress, unhappiness, and alienation when comparing themselves to better-off households. Additionally, there is previous evidence regarding the fact that people prefer to neighbor people of a similar socioeconomic background. Hence, an empirical test is needed. In order to implement it, we should deal with two problems, first, the survey limited statistical significance at the municipal level, hence we use the small area estimation (SAE) methodology to improve the estimations’ statistic properties, and second, the double causality between segregation and LS; to deal with the latter, we include lagged LS as a regressor. Our findings indicate that socioeconomic segregation has a positive effect on LS. This result is robust to different econometric specifications.

Determinants of Residential Satisfaction During the Initial Stage of the COVID-19 Pandemic: The Case of Xiangyang City, China

“…Unlike the findings of Montero and others [56], who argued that older adults are more likely to have a lower level of life satisfaction based on the data collected from Chile for the years 2011 and 2013, this study posits that older residents have higher residential satisfaction than young people during quarantine in China. This contradictory result may be explained by different cultural and pandemic contexts.…”

Segregation and well‐being in Sweden: Geographies of well and ill‐being

“…A geography of discontent can be observed: there are areas where most of the population is likely to feel unsatisfied with their lives: particularly in neighbourhoods built in the miljonprogrammet era at the edge of cities that are also ethnically and socioeconomically strongly homogenised. Even though this similarity to neighbours in these neighbourhoods could have some positive effects as Montero et al (2021) suggested, it does not take away the fact that there are neighbourhoods that are structurally deprived of most factors that make one feel well. Thus, considerably lower internal well‐being can be expected there as well.…”

“…Well‐being is a relevant approach to studying residential segregation. Well‐being is an overall measure of the quality of life (Montero et al, 2021), and, therefore, able to cover aspects of neighbourhood homogenisation such as health, income, labour market access, and housing more holistically beyond economic terms as done in socioeconomic segregation studies. There are indications that well‐being and socioeconomic segregation could be interrelated—unequal societies are unhealthier, less affluent, and function less well (Pickettt & Wilkinson, 2010).…”

“…Conversely, it might feel better not being confronted with wealthier people, as within a more mixed neighbourhood. (Montero et al, 2021) or reflect a preference for ethnic similarity. Hence, well-being could be a dimension that furthers understanding of neighbourhood homogenisation, either as a form of segregation itself or as a consequence of ethnic or socioeconomic segregation.…”

Family and Individual Contexts of Middle-School Years and Educational Achievement of Youths in Middle-Aged Adulthood

“…Family SES was measured by the Duncan’s Socioeconomic Index (SEI) score when the youths were in grade 7, which was provided by the principal investigators of LSAY by calculating the parental responses of their educational level, income, and occupational prestige [ 43 ]. SEI is constructed by weighting an occupation’s median education and income on the metric of occupational prestige [ 43 ], which has been widely used to indicate family SES in empirical research with higher scores representing better family SES [ 44 , 45 ].…”