Abstract
Subjective well-being (SWB) has presented long-lasting interest for researchers and the recent focus on the economic approach to SWB led to increased awareness of the topic. Despite the significant number of studies, conceptualizing and assessing SWB, along with finding predictors of SWB, need further empirical exploration. Following this rationale, using statistical and econometric methods (correlation analysis, Principal Component Analysis (PCA), Multinomial Logistic Regression (MLR)) applied on data collected via a survey on students from Bucharest University of Economic Studies (363 respondents), this study explores and provides insights that support a better understanding of defining and measuring SWB. Additionally, the study offers valuable information on the main determinants of SWB for a particular group, in this case, Romanian business students. According to findings, we argue that: (1) when assessing perception of life satisfaction and happiness, Romanian students tend to make slight distinctions between these two concepts; (2) question order effect is not significant, whereas negative sentiments (such as pessimism) impact self-assessment of happiness, but not of life satisfaction; (3) the main predictors for SWB are satisfaction with current activities, level of optimism/pessimism, health, and safety of the neighborhood. This paper proposes a new approach to modeling SWB by MLR, which features expressing the dependent variable with respect to the principal factors obtained by PCA.
Highlights
Subjective well-being (SWB) has presented long-lasting interest as an area of research in psychology [1], since many scholars associate SWB with psychological issues that consist of “happiness, life satisfaction, the presence of positive affect, and the relative absence of negative affect” [2] (p. 11)
Despite the significant number of studies, conceptualizing and assessing SWB, along with finding predictors of SWB, need further empirical exploration. Following this rationale, using statistical and econometric methods (correlation analysis, Principal Component Analysis (PCA), Multinomial Logistic Regression (MLR)) applied on data collected via a survey on students from Bucharest University of Economic Studies (363 respondents), this study explores and provides insights that support a better understanding of defining and measuring SWB
In line with the evidence and controversies charted in the literature review, the present paper focuses on providing relevant insights into the following knowledge gaps: (1) While single metric scales (World Values Survey, General Social Survey, or Gallup World Poll) gather data on either self-reported life satisfaction or self-reported happiness, there is an open debate on whether these two concepts can be used interchangeably; (2) SWB scales are not entirely reliable, since people’s answers are influenced by response sets and response styles; the extent to which question order influences SWB assessment has not been thoroughly examined; (3) The majority of studies that assess Romanian students’ SWB focus on psychological factors, while the economic approach of SWB seems to be neglected
Summary
Subjective well-being (SWB) has presented long-lasting interest as an area of research in psychology [1], since many scholars associate SWB with psychological issues that consist of “happiness, life satisfaction, the presence of positive affect, and the relative absence of negative affect” [2] (p. 11). Using a particular strategy in designing the survey, the present study collects and analyzes specific data that offer valuable insights into the impact of context effects on SWB estimation In this context, the study concentrates on the main topics in SWB with a special focus on the incongruous findings and questions that still need answers. The paper includes a literature review that emphasizes the peculiarities of estimating SWB and the main results so far of empirical analyses of SWB determinants in the case of students and young adults In this context, the study continues to set out the main research assumptions and presents the research methods and materials, including the design of the questionnaire, sample selection, data collection, and description of main research methods. The last section comments on the limitations of the study and directs further research efforts
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