Are Poor People Less Happy? Findings from Melanesia

Feeny, Simon; McDonald, Lachlan; Posso, Alberto

doi:10.1016/j.worlddev.2014.06.022

Cited by 22 publications

(14 citation statements)

References 41 publications

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“…Subsequent reviewers have generally arrived at a similar conclusion (Diener et al, 1999;Headey and Wearing, 1992;King and Napa, 1998). However, despite this apparent consensus, there are numerous empirical reports indicating that people who are rich have a level of subjective well-being that is substantially higher than people who are poor (Feeny et al, 2014). We note that the mean change in annual income (compared to 2011) was 1.9%, but this did not result in a greater level of happiness.…”

Section: Economic Variablesmentioning

confidence: 68%

“…In all models, the number of people in the household has also been found to have a significantly positive effect on happiness. Although Feeny et al (2014) found that household size has a negative association with happiness, they considered only economically poor households. In modern society, although enjoying material comfort, many people report feeling isolated and lonely (Yoshinaka and Hatanaka, 2013); therefore, we assume that those who live with a big family are less likely to feel lonely.…”

Section: Basic Variablesmentioning

confidence: 99%

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Subjective Well-being and Its Determinants in China: An Empirical Study Based on Survey Data

Liang¹,

Shen

2016

RAE

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Using household survey data collected in 2013, this paper empirically investigates the determinants of individual subjective well-being in China, where there has been rapid economic development over the past three decades. The main results are as follows. First, factors such as good health, marital status, life satisfaction, body mass index, physical exercise, and expectations of inflation are all significantly correlated with the reported level of happiness. Second, income has no significant effect on the level of happiness, and happiness has an inverted U-shaped relationship to wealth. Third, increased education decreases the level of happiness. To some extent, these findings can explain why subjective well-being has declined in China, despite its spectacular economic growth.

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Section: Economic Variablesmentioning

confidence: 68%

Section: Basic Variablesmentioning

confidence: 99%

Subjective Well-being and Its Determinants in China: An Empirical Study Based on Survey Data

Liang¹,

Shen

2016

RAE

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“…For instance, in economics and the social sciences, ordinal variables are used to predict phenomena like income distribution, poverty, consumption patterns, nutrition, fertility, healthcare decisions, and subjective well-being, among others [e.g. 3,44,39,27,36,20]. In marketing research, customer preferences are used to create automatic recommendation systems, as in the case of Netflix [e.g.…”

Section: Introductionmentioning

confidence: 99%

Supervised dimension reduction for ordinal predictors

Forzani

Arancibia

Llop

et al. 2018

Computational Statistics & Data Analysis

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In applications involving ordinal predictors, common approaches to reduce dimensionality are either extensions of unsupervised techniques such as principal component analysis, or variable selection procedures that rely on modeling the regression function. In this paper, a supervised dimension reduction method tailored to ordered categorical predictors is introduced. It uses a model-based dimension reduction approach, inspired by extending sufficient dimension reductions to the context of latent Gaussian variables. The reduction is chosen without modeling the response as a function of the predictors and does not impose any distributional assumption on the response or on the response given the predictors. A likelihood-based estimator of the reduction is derived and an iterative expectation-maximization type algorithm is proposed to alleviate the computational load and thus make the method more practical. A regularized estimator, which simultaneously achieves variable selection and dimension reduction, is also presented. Performance of the proposed method is evaluated through simulations and a real data example for socioeconomic index construction, comparing favorably to widespread use techniques.

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“…The difficulties in generalizing these results are raising calls to choose widely-used wellbeing measurements in policy analysis. Secondly, existing studies usually focused on depicting the associations of wellbeing with just one or one kind of determinant rather than taking an overview [ 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 ]. Thirdly, studies incorporating wellbeing within the impact assessment of climate change related policies are still scarce [ 3 , 4 , 8 , 20 , 21 , 22 , 23 , 24 ].…”

Section: Introductionmentioning

confidence: 99%

Do Climate Change Policies Promote or Conflict with Subjective Wellbeing: A Case Study of Suzhou, China

Liu

Huang

Hiscock

et al. 2016

IJERPH

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As public expectations for health rise, health measurements broaden from a focus on death, disease, and disability to wellbeing. However, wellbeing hasn’t been incorporated into the framework of climate change policy decision-making in Chinese cities. Based on survey data (n = 763) from Suzhou, this study used Generalized Estimation Equation approach to model external conditions associated with wellbeing. Then, semi-quantitative analyses were conducted to provide a first indication to whether local climate change policies promote or conflict with wellbeing through altering these conditions. Our findings suggested: (i) Socio-demographic (age, job satisfaction, health), psychosocial (satisfaction with social life, ontological security/resilience) and environmental conditions (distance to busy road, noise annoyance and range hoods in the kitchen) were significantly associated with wellbeing; (ii) None of existing climate change strategies in Suzhou conflict with wellbeing. Three mitigation policies (promotion of tertiary and high–tech industry, increased renewable energy in buildings, and restrictions on car use) and one adaption policy (increasing resilience) brought positive co–benefits for wellbeing, through the availability of high-satisfied jobs, reduced dependence on range hoods, noise reduction, and valuing citizens, respectively. This study also provided implications for other similar Chinese cities that potential consequences of climate change interventions for wellbeing should be considered.

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Are Poor People Less Happy? Findings from Melanesia

Cited by 22 publications

References 41 publications

Subjective Well-being and Its Determinants in China: An Empirical Study Based on Survey Data

Subjective Well-being and Its Determinants in China: An Empirical Study Based on Survey Data

Supervised dimension reduction for ordinal predictors

Do Climate Change Policies Promote or Conflict with Subjective Wellbeing: A Case Study of Suzhou, China

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