Life Satisfaction and Public Finance: An Empirical Analysis in the European Union

Disorders of gut-brain interaction (DGBI) are characterized by debilitating symptoms not explained by structural or biochemical abnormalities. While functional conditions present with complex, likely heterogeneous pathophysiology, we aimed to investigate if proxy measures of sociocultural and environmental factors are associated with the prevalence of various DGBI in populations across the world. We performed an ecological study utilizing peer-reviewed published datasets reporting for 26 countries prevalence rates of DGBI (Rome Foundation Global Epidemiology Study, RFGES), with six independent variables: Helicobacter pylori prevalence and household size as proxy measures for orofecal infections, gross domestic product per capita (GDP), and median age as a proxy measures for socioeconomic development, density of fast food outlets (FFO) per 100,000 population as proxy measure for processed food exposure, and suicide mortality rate per 100,000 people, and world happiness scores were used as a proxy for psychological stress. The data were retrieved from publicly accessible datasets (United Nations, CIA World Factbook, World Bank, World Happiness Report, commercial/financial reports of a global FFO chain). We used linear regression to assess variables in univariate and multivariate analysis and report standardized β coefficients with 95% confidence intervals (CI). The regression model revealed that the overall prevalence of DGBI was inversely associated with both GDP per capita (β = -0.57, 95% CI: -0.92, -0.22, p = 0.002) and happiness scores (β = -0.433 95% CI: 0.821, -0.065, p = 0.023), while being positively associated with H. pylori prevalence (β = 0.40, 95% CI: 0.008, 0.81, p = 0.046). The prevalence of functional constipation (FC) was also inversely associated with GDP per capita (β = -0.50, 95% CI: -0.86, -0.13, p = 0.01) and happiness scores (β = -0.497, 95% CI: -0.863, -0.132, p = 0.01), while being positively associated with H. pylori prevalence (β = 0.53, 95% CI: 0.16, 0.91, p = 0.007). The Multivariate model analysis revealed that combining the factors of H. pylori prevalence, suicide rate, household size and happiness scores showed statistically significant association with FC (p = 0.039). Household size (β = -0.43, 95% CI: -0.82, 0.038, p = 0.033) and suicide rates (β = 0.55, 95% CI: 0.19, 0.90, p = 0.004) were statistically significantly associated with functional diarrhea. Irritable bowel syndrome (IBS) was associated with GDP per capita (β = -0.40, 95% CI: -0.79, -0.014, p = 0.043) and happiness scores (β = -0.390, 95% CI: -0.778, -0.003, p = 0.049). Utilizing publicly available data, the prevalence of DGBI across diverse countries is linked to various socio-cultural and environmental factors. Collectively, the data suggests that the prevalence of DGBI is increased in less prosperous regions of the world.

Happiness plays an important role in human emotion and one’s growth. In this paper, we use the data from the World Happiness Report, Countries of the World, and Countries Dataset 2020 to discern the relationship the happiness score has with the economy, family, health, freedom, trust, perception of corruption, generosity, and residual. In our research, we used the regression approach to find the most important factors that affect the happiness score in the past five years. Since we observed a positive and moderate relationship between the residual and happiness score, we then looked for other factors that contribute to the residual, the unexplained factor. Finally, we verified the main factors to the happiness score.

Through the impact of the COVID-19, people around the world have been affected to various degrees. Thus, it is more interesting to compare the happiness reported between 2022/2021 and before 2019. This article concludes 5 years of happiness scores data including family, Gross Domestic Product (GDP), health, freedom, generosity trust, and dystopia residual. Happiness scores are considered appropriate indicators to measure the progress of social development. This study presents two linear regression models to predict happiness scores across countries in 2022. Data is sourced from the world happiness report dataset from 2015-2021, available in open source. Preliminary exploratory data analysis was carried out to select the most appropriate variables to include in the models. The models’ accuracy was tested by comparing the output values to the true 2022 world happiness report data. The experiment results show that the linear regression achieved a Root Mean Square Error (RMSE) = 0.236 and Mean Squared Error (MSE) = 0.056 for 2022.

Happiness is a state of contentment, joy, and fulfillment, arising from relationships, accomplishments, and inner peace, leading to well-being and positivity. The greatest happiness principle posits that morality is determined by pleasure, aiming for a society where individuals are content and free from suffering. While happiness factors vary, some are universally recognized. The World Happiness Report (WHR), published annually, includes data on ‘GDP per capita’, ‘social support’, ‘life expectancy’, ‘freedom to make life choices’, ‘generosity’, and ‘perceptions of corruption’. This paper predicts happiness scores using Machine Learning (ML), Deep Learning (DL), and ensemble ML and DL algorithms and examines the impact of individual variables on the happiness index. We also show the impact of COVID-19 pandemic on the happiness features. We design two ensemble ML and DL models using blending and stacking ensemble techniques, namely, Blending RGMLL, which combines Ridge Regression (RR), Gradient Boosting (GB), Multilayer Perceptron (MLP), Long Short-Term Memory (LSTM), and Linear Regression (LR), and Stacking LRGR, which combines LR, Random Forest (RF), GB, and RR. Among the trained models, Blending RGMLL demonstrates the highest predictive accuracy with R2 of 85%, MSE of 0.15, and RMSE of 0.38. We employ Explainable Artificial Intelligence (XAI) techniques to uncover changes in happiness indices, variable importance, and the impact of the COVID-19 pandemic on happiness. The study utilizes an open dataset from the WHR, covering 156 countries from 2018 to 2023. Our findings indicate that ‘GDP per capita’ is the most critical indicator of happiness score (HS), while ‘social support’ and ‘healthy life expectancy’ are also important features before and after the pandemic. However, during the pandemic, ‘social support’ emerged as the most important indicator, followed by ‘healthy life expectancy’ and ‘GDP per capita’, because social support is the prime necessity in the pandemic situation. The outcome of this research helps people understand the impact of these features on increasing the HS and provides guidelines on how happiness can be maintain during unwanted situations. Future research will explore advanced methods and include other related features with real-time monitoring for more comprehensive insights.

Feeling Good, Living Well: The Importance of Happiness for Health

This paper examines the role of factors which could have influenced subjective well-being (SWB) in European countries at a national level between 2010 and 2019. Macroeconomic variables in much of the existing literature have looked at GDP, inflation, government size and expenditure and their relationship to SWB. The current analysis included corruption, property rights, poverty, life expectancy, working time and emissions to enrich the existing body of literature. The World Happiness Index (WHI) is used to measure SWB in this study. The correlation analysis in this study shows a high level of correlation between WHI and the Human Development Index (HDI) which suggests the WHI is a suitable proxy for measuring subjective well-being. Next, the fixed and random effects models were estimated since the dataset was longitudinal, and we have also compared panel regression models with OLS regression models. This analysis revealed positive relationships of GDP, income and property rights on WHI, while poverty and unemployment impact WHI negatively, thus we can conclude positive relationship between material aspects of life and subjective well-being. Corruption and working time impact SWB in a negative way while the impact of life expectancy is positive. The regression models with inflation and emissions were not found to be significant in the research. The results were compared with existing studies based on individual as well as aggregated data. Similarities in results prove that it is possible to analyze determinants of SWB from aggregated data on national level. At the end, we formulate proposals for improving quality of life in the analyzed countries.

Abstract. The purpose of this study was to use data from the World Happiness Report to conduct an in-depth analysis of the factors that influence the World Happiness Index (WHI) and to look for other factors that may influence happiness. In this paper, the correlation graph shows that among the original six variables, Social Support has the strongest correlation with the ladder score, which means that Social Support has the greatest impact on the happiness index, followed by GDP per capita; Generosity, on the other hand, was the weakest associated with ladder scores and had the least effect on happiness. Then the linear regression and scatter plot are used to prove this conclusion. Therefore, this paper can consider whether to delete Generosity as an influential factor. A map was then used to show happiness levels and geographical distribution in different countries. At the same time, the distribution of the Gini coefficient is also shown by a regional distribution map. From the perspective of the Gini coefficient and education level, these two factors also have a certain positive correlation with the happiness index, which are likely to be the potential influencing factors of the happiness index. From a global map perspective, the happiest countries are mostly located in Europe, North America and Oceania, while the happiest countries are mostly located in Africa. The study's sample size was not large enough, it was prone to make errors and raise questions about happiness scores in some countries.

Inadequate sleep is an important public health problem that can affect one in every three adults; however, it received little attention in the economics of happiness research. The objective of this article is to examine whether sleep adequacy contributes to the explanation of variation in happiness index levels across countries. Analysis was undertaken using ordinary least squares regression method. The dependent variable is the self-reported happiness index developed by the Gallup poll and published in the World Happiness Report. Two alternative model specifications were used. The first included average sleep minutes per country, GDP per capita(purchasing power parity), unemployment rate, and environmental performance index. The second model specification included average sleep minutes per country, GDP (purchasing power parity), and economic freedom index. Both model specifications met several robustness checks, and showed overall significance and significant coefficients. Results showed that an increase in average sleep duration by 10 minutes is associated with an improvement in the happiness score by 0.1 and 0.15 points in the first and second model specifications respectively, noting an average happiness score of 6.2 in the country sample. The conclusion that sleep duration contributes to explaining variation in happiness levels across countries is a call for policy makers to consider policies targeting improvement in sleep adequacy as priority, and to direct more resources to further research in the area of sleep economics. Previous studies in the area of happiness economics did not consider sleep in explaining differences in happiness among countries, and previous studies in the area of economics of sleep did not consider the happiness index at a global level.

The aim of this investigation was to measure levels of ethnic or cultural background diversity, social cohesion and modern prejudice, and the impact of such diversity, cohesion and prejudice on the quality of life. Using a sample of 743 residents of Prince George, British Columbia, we identified diverse ethnic or cultural groups, and created several indexes of heterogeneous social networks and a measure of modern prejudice. Dividing the total sample into three roughly distinct groups containing, respectively, respondents self-reporting an ethnic or cultural background that was aboriginal, non-aboriginal visible minority or anything else, we discovered that all significant comparisons indicated that people with aboriginal backgrounds reported a generally lower quality of life than those in the other two groups. The quality of life scores of the other two groups were practically indistinguishable. Given the demographic structure of our sample, the revealed differences could not be attributed to differences in socio-economic classes. Members of the largest group of respondents tended to be most prejudiced and optimistic, people with aboriginal backgrounds tended to be least prejudiced and optimistic and people with visible minority backgrounds tended to be between the other two groups. Regressions revealed that a variety of ethnic/culture-related phenomena could only explain 8%, 9% and 10%, respectively, of the variation in scores for happiness, life satisfaction and satisfaction with the overall quality of life. When domain satisfaction scores were added to the set of predictors, we were able to explain 48%, 69% and 54%, respectively, of the variation in scores for happiness, life satisfaction and satisfaction with the overall quality of life. In the presence of the domain satisfaction scores, the scores on the ethnic/cultural related phenomena added only one percentage point of explanatory power for happiness and life satisfaction, and three percentage points for satisfaction with the overall quality of life. All things considered, then, it is fair to say that this project showed that ethnic or cultural background diversity, social cohesion and modern prejudice had relatively very little impact on the quality of life of our sample of respondents.

This study addresses the research objective of predicting global happiness and identifying its key drivers. We propose a novel predictive framework that integrates unsupervised and supervised machine learning techniques to uncover the complex patterns underlying happiness scores across nations. Initially, we apply K-Means clustering to group countries based on similarities in their happiness patterns. For the first time, these cluster assignments are subsequently incorporated as additional features into ensemble learning models-specifically, Random Forests and XGBoost-to enhance the prediction of happiness scores. This hierarchical analysis approach yields a significant improvement in predictive performance, with an approximate 12% increase in R² compared to models that do not include clustering information. Using data from the World Happiness Report, our analysis reveals that global happiness can be categorized into three distinct groups (high, medium, and low). Among the various determinants examined, social support and GDP emerge as the most influential factors contributing to the happiness index. These findings not only advance the methodological framework for predicting happiness but also provide robust evidence for policymakers seeking to implement targeted interventions aimed at improving public well-being and promoting social progress.

In economic sciences, most analyses focus on the economic person construct. However, this that formalization does not capture the complex nature of human behaviour. This paper estimates the weight that economic and noneconomic dimensions of human behaviour have on wellbeing. A utility function is considered that models behaviour from a complex standpoint, where the motivations of the economic individual (homo economicus) are analysed in a broad perspective by integrating emotional wellbeing and human virtues into the model (homo virtus). Three empirical measures of wellbeing are used: The Well-Being Index developed by the Boston Consulting Group’s Sustainable Economic Development Assessment (2008–2018), the Index of Economic Well-Being from the Centre for the Study of Living Standards (1980–2014), and the Happiness Score from the World Happiness Report (2005–2018). Depending on data availability, the model is estimated globally for all countries, OECD countries, European countries, and developing countries using linear regression methods. The results indicate that, on average, the homo virtus dimension of behaviour has a weight of 11% in countries’ wellbeing functions, while the economic perspective has a weight of 89%. Additionally, the results show that richer countries value economic factors more than poorer countries. The analyses also show that the maximum level of emotional satisfaction is higher for European and OECD countries than for developing countries.

In this research, we investigate the public understanding of the World Happiness Report within the context of its highest-ranking country: Finland. We analyse how two actors, Finnish online media and their readers, understood the publication as well as the concept being measured: happiness. Digital media adopted an ambivalent stance towards both the World Happiness Report ('sports victory' vs 'societal problems') and the concept of happiness ('reticence to define happiness' vs 'secrets of Finnish happiness'). Readers agreeing with the World Happiness Report define Finland as an 'almost utopia' while readers disagreeing with the World Happiness Report, in addition to presenting a reversed image of Finland ('almost dystopia'), further justify their distrust towards the World Happiness Report by attacking the publication, its authors and the participants (Finns). Both actors carefully construct their understanding of happiness to fit their arguments aimed at the glorification/scandalization of the World Happiness Report.

This study is devoted to generalizing the experience of constructing international and national, including Russian, life satisfaction indicators with the aim of theoretical substantiation and development of a methodology for constructing an indicator that has practical significance for characterizing the country’s progress in the direction of increasing the subjective well-being of its population. The fundamental basis for quantitative assessment of life satisfaction is the economic theory of happiness, which focuses on a multifaceted analysis of subjective well-being. Supporters of the economics of happiness argue that happiness can be measured through life satisfaction. The economics of happiness uses global and national population surveys on life satisfaction, happiness, and subjective well-being to assess the impact on the cognitive and emotional aspects of life of factors such as income, inflation, work, work-life balance, education, health, age, family relationships, moral values, environment, etc. The economic meaning and practical significance of life satisfaction indicators have specifics depending on the mission, level of coverage, and method of data collection and processing. This article reviews international life satisfaction assessments: the Happy Planet Index, the Legatum Prosperity Index, the OECD Better Life Index, How’s Life? - Measuring Well-Being, and the World Happiness Report. The specifics of national life satisfaction assessments are illustrated by examples of Bhutan’s Gross National Happiness (GNH) Index, The Australian Unity Wellbeing Index, and the UK Measures of National Well-being Dashboard. The most authoritative assessments in Russia include indices calculated by the VCIOM, the Public Opinion Foundation (FOM), the ROMIR Research Holding, and quality of life ratings for the population in the country’s regions. A quality of life satisfaction index for Russia has been developed based on a comprehensive approach (taking into account qualitative and quantitative variables), and a comparative analysis of happiness levels has been conducted for the four indices reviewed in the article that assess the happiness of the Russian population.

Background: Various complications of the disease and its treatment can lead to a decrease in life satisfaction among hemophilia patients. As family functioning plays a crucial role in the well-being of patients, this study aimed to determine the effect of family-oriented empowerment on the life satisfaction and happiness of patients with hemophilia. Methods: This quasi-experimental study included 36 hemophilia patients who met the study criteria and were randomly assigned into the control and experiment groups (18 participants in each group). Data were collected using a demographic questionnaire, Diener's life satisfaction questionnaire, and the Oxford happiness questionnaire. The questionnaires were completed before and one month after the intervention. Data were analyzed using SPSS 24. Results: The independent t-test did not reveal a significant difference in the mean scores of life satisfaction and happiness between the control and experiment groups before the intervention. However, a significant difference was observed in the average scores of life satisfaction and happiness between the control and experiment groups after the intervention (P < 0.001). Conclusions: The results demonstrated a positive effect of family-centered empowerment intervention on the life satisfaction and happiness of hemophilia patients.

Background: During the recent decades, happiness and psychological wellbeing have been among the most attractive issues for researchers in the fields of social sciences and health. Medical and paramedical students in comparison with other college students are less happy due to work circumstance in hospital and special education. Objectives: The aim of the present study was to evaluate happinessamongcollege students of Qazvin University of Medical Sciences in terms of socio-demographic variables. Materials and Methods: In this cross-sectional web-based study, all the students of Qazvin University of Medical Sciences in Iran who had course classes were invited to participate in the study and 541 students filled out the web-based questionnaire including questions for measuring happiness oxford happiness questionnaire (OHQ), health status, stress experience in the past six months, cigarette and hookah smoking, physical activity rapid assessment of physical activity (RAPA), as well as socio-economic and demographic information. Results: The mean happiness score was 114.59 ± 18.31. Socio-economic status, physical activity, and experience of stress in the last 6 months were related to the happiness score (P = 0.009, P < 0.001, P < 0.001, respectively). However, gender, cigarette smoking, hookah smoking and body mass index were not significantly correlated with happiness. Conclusions: The findings of the present study show that a happiness score among our sample study was slightly low and people with high happiness scores had a healthier lifestyle, i.e. more physical activity and less tobacco smoking. College students should be encouraged to do regular exercise as a way to increase the happiness level. Keywords: Happiness, Tobacco Smoking, Life Satisfaction, Physical Activity, Students