positivity project

In this journal article, Blanchflower examines the relationship between age and subjective well-being across 145 developed and developing countries. This article uses information from fourteen different survey series, and the author argues that happiness generally follows a U-shaped pattern: it declines from young adulthood, reaches its lowest point around middle age, and then begins to rise again later in life. According to Blanchflower, the lowest point in happiness occurs during “midlife around age 50” (575). This can be seen in both developing and advanced countries, leading him to conclude that “the happiness curve seems to be everywhere” (575). The author also controls for factors such as education, employment, and marital status in order to separate the effects of age from other personal factors. The study draws from a large and geographically diverse sample rather than focusing only on wealthy Western countries. Still, because much of the evidence comes from surveys comparing different people at one point in time, the study cannot fully separate the effects of aging from generational and cultural differences. This means that some of the changes in happiness may be shaped not only by age, but also by the different social conditions experienced by each generation.

In this article, the authors are examining the relationship between perceived corruption (PC) and subjective well-being (SWB) and institutional trust (IT) as a mediator of the two based on data from 1566 households in Pakistan, which is a developing country. Associated with reducing access to public services and directly affecting how each individual reacts emotionally, corruption can limit one’s well-being physically and psychologically and significantly reduce a society’s IT. The paper tested 4 different hypotheses: “H1: PC has a negative and significant influence on IT (β = 0.43, p < 0.01). H2: Institutional quality mediates the relation between PC and SWB (β = 0.20, p < 0.01). H3: Perceived institutional quality positively and significantly improves SWB. H4: PC erodes SWB.” These claims were all validated from this data and its methodology. Because PC and SWB are variables that play a role in the World Happiness Report, this information could help provide understanding why certain factors may play a role in explaining a country’s happiness. One critique is that the source only utilizes its sample from Pakistan and leaves out other countries, meaning it may not be representative of other countries/regions.

In this article, the authors start off by mentioning the classic question of “does money increase happiness,” arguing that while older studies have found wealthier countries and people have a more positive outlook on their life overall, those studies have neglected that there are other factors/types of happiness (such as daily emotions), the fact that money and happiness might have a different relationship in different groups of people (such as old vs young and rich vs poor), and why the money might increase feelings of well being (including because it allows for people to meet their basic needs, feel psychologically more secure, and achieve material aspirations); the authors ultimately argue that while money is strongly correlated with positive outlooks on life, it doesn’t heavily predict daily emotions, and that daily emotions are controlled more by the overall prosperity of a society (“societal income”) and that income actually increases happiness more in richer societies than poorer ones, countering the idea that money only increases happiness when it’s for fulfilling basic needs. This source uses data from the Gallup Poll of 2005-2006 from 132 countries and 96% of the world’s population, where logged income, national wealth, relative wealth, basic needs, psychological needs, and material prosperity were all measured through a survey. This resource is important as it delves deeper into the general idea that money brings or causes happiness by firstly splitting happiness into different types/ideas rather than some abstract idea, and secondly, also analyzes how while essentially money can help increase certain aspects of what might be considered happiness, it is not the only predictor of happiness and actually doesn’t explain many aspects of it. For our thesis, this source ultimately is tied closely to our dataset, which also utilizes the Gallup poll and tracks income as a predictor of happiness, and helps us show that while income does indeed track/predict some levels of happiness, as analyzed in our dataset, it is not the only factor and it leaves a lot to be explained. Overall, the source is a step forward in the right direction in terms of measuring the association between money and happiness, as it is one of the first sources to acknowledge that happiness is multidimensional and that different aspects of it can be affected in different ways, as well as the fact that the source draws from a wide representative sample of 132 countries.

In this paper, the authors are looking into the idea of being wealthy can increase happiness and reduce inequalities in well being among people. The argument is focusing on how financial status has a greater impact on lower income individuals than on individuals who are higher income, this is suggesting that reducing income inequality can improve overall happiness for both groups. To support the claim, the authors are using a large scale experimental data and survey evidence that compare changes in well being before and after financial support is being distributed. This source is important because it provides supportive evidence on how economic inequality plays a huge role in determining happiness levels. For the thesis, this article directly connects to the economic variables included in the World Happiness Report, such as GDP per capita, while also including the opportunity to have a broader discussion about how wealth is distributed within countries. Overall, the article is significant because it shows that higher national income does not always mean greater happiness unless economic support is able to improve the well being of the population.

Here we find the seemingly contradictory assertion that a nation can earn more money but the people are no happier, which is known as the Easterlin paradox, and he puts forth further proof on the matter with this new evidence from more nations. It is said that money and well-being move together in the short run, but over time the connection disappears. The data is collected from 37 nations, including 17 developed, 9 developing, and 11 nations in transition. For us, this serves as a warning against the usage of GDP in predicting the Ladder Score, since money may work in one year and fail in the long run, which supports the idea that money leaves many things unaccounted for, as noted by Diener. The downside is that this is still a debate, since Stevenson and Wolfers showed similar relations and claim that the correlation is indeed stronger.

In this paper, the authors examine whether cultural differences make it difficult to accurately compare happiness across countries. They separate culture into two possible effects: cultural bias, where culture affects how people understand or answer survey questions, and cultural impact, where culture actually shapes how people experience their lives. Using multiple waves of Gallup World Poll data from more than 150 countries and territories, the authors analyze cultural values, differences in how positively people evaluate different parts of life, and the happiness of migrants living outside their countries of origin. They find that objective life circumstances, such as income, health, employment, and social conditions, explain most international differences in subjective well-being. However, culture may explain around 20 percent of the country-level variation that remains unexplained after these factors are considered. This source is important to our research because our dataset also uses Gallup World Poll data to compare Ladder Scores across countries. It supports Wierzbicka’s argument that culture can influence happiness reports, but it also shows that cultural differences do not make international comparisons completely unreliable because life circumstances still explain most of the variation. One limitation is that the authors cannot fully separate cultural bias from the actual influence of culture on people’s well-being. In addition, some of the unexplained country differences may come from other factors that were not included in their models. For our project, this source helps us argue that culture and language should be considered when interpreting Ladder Scores, while avoiding the conclusion that all geographical differences are simply caused by culture.

In this article, the authors attempt to find if whether there is a correlation between religion and happiness, as while previous studies had found that religion generally was associated with feelings of happiness, they failed to distinguish two different aspects of religion: the material aspect (such as community membership and following religious rules) and the spiritual aspect (one’s personal faith and beliefs about the supernatural); the authors ultimately conclude that religion has pros and cons with happiness with religious belief/spiritual ideas increasing feelings of happiness, but material aspects actually causing a decrease in happiness once belief is controlled, finding that in general, spiritual aspects of religion are correlated with more happiness while material aspects of religion are correlated with less happiness. For evidence, the article utilizes the European Social Survey (ESS) from 2000 - 2008 and collects the following variables: religious affiliation, religious membership (material aspects), and religiosity (spiritual aspects). This resource is important as it finds a few underlying patterns below the general claim of religion having a singular effect on someone’s happiness: it finds that religion is somewhat like an investment, where while membership alone tends to decrease happiness due to rigidity and having to follow rules, religiosity/beliefs increase it due to the ideas having a comforting and guiding effect on people, often more than the initial decrease, which is why on the surface, religion appears to increase happiness. For our thesis specifically, this resource is important as it introduces a variable not talked about in our data set, which is culture; religion is a major part of many country’s cultures and peoples lives, so it could be thought of to have an impact on a person’s happiness. Therefore, this resource opens the discussion to other methods of measuring happiness, beyond for instance, the Cantril Ladder and numerical aspects, such as logged GDP per capita and perceptions of corruption as an index. One main criticism of this source, however, is that firstly, it mainly measures the relation between happiness and Abrahamic religions (Christianity and Islam) as those are the most prevalent in Europe; a second is that the source utilizes a dataset which only contains European countries, meaning that potential different trends in different regions might be left out.

In this article by the World Happiness Report, the authors examine how happiness differs among populations by age across countries and global regions. Instead of treating each country’s average happiness score to represent its entire population, the authors chose to divide respondents into four age groups: people under 30, people between 30 and 44, people between 45 and 59, and people who were aged 60 and older. They compare life evaluation and emotional well being data from 2021-2023 with results from 2006-2010. The report’s happiness rankings are based on the Gallup World Poll’s Cantril Ladder question, which asks individuals to rate their lives scale from zero to ten. There are around 1,000 responses collected from each country annually, and the rankings use three-year averages to produce more precise estimates. The authors emphasize that “rankings differ a lot for the young and old,” demonstrating that national averages may hide major differences between demographic groups. This resource finds that younger people report lower happiness than older people in countries such as the United States and Canada, while the opposite is true in several Central and Eastern European countries. The authors conclude that “age and generation both matter for happiness,” meaning that people’s social and historical experiences can shape how they evaluate their lives. This source is credible because it uses large-scale international survey data, and it was written by established happiness researchers as well as published on the World Happiness Report website. It is useful for our project because it shows that national happiness rankings do not represent every age group equally and should be interpreted carefully.

In this article, the authors examine how personal well being changes when facing different stages of life and identify the factors that consistently are able to predict happiness levels across countries and cultures. While many studies focus mainly on average happiness levels. The authors believe age, health, and economic status contribute to changes in life satisfaction as time goes on. To support their conclusions, they analyze data from large international surveys that include participants from many countries, which allows them to compare trends in personal well-being across cultures and age groups. This resource is important because it demonstrates that happiness cannot be explained by one variable alone and instead it reflects the interaction of multiple variables all together such as demographic, social, and economic factors. For the thesis, this article closely relates to the World Happiness Report dataset because it explains why countries with similar levels of wealth may still report different happiness scores. It also helps show the truth behind our argument that understanding global happiness requires looking beyond income alone and considering the broader social and demographic factors that shape well being.

As a result, the method differentiates between two distinct parts of happiness: a life evaluation and emotional well-being, which is very useful for us. Life evaluation is about rating your life in accordance with the Cantril ladder, while emotional well-being is about the moods you experience daily – happiness, stress, and others. The research discovered that while people’s life evaluations increase with their income, it is different in terms of emotional well-being, which increases only until a certain amount of money is achieved. This means that the more money a person has, the better they evaluate their lives, but this does not have any effect on their current emotions. The material is based on the responses gathered by the researchers through the Gallup Healthways Well-Being Index, which was conducted around 1 thousand interviews per day during the years 2008-2009, making it a large sample. This is important to note because we are conducting our analysis based on the Cantril ladder, which is a life measurement scale and not the mood scale. This means that the results of the study suggest that our Ladder Score might correlate with income in a different way than how people’s feelings are supposed to do, which is indeed what we are after. Of course, it is important to note that the research was done on the US population only, and it may not be valid in poorer countries.

The authors examine why Finland, Denmark, Norway, Sweden, and Iceland are consistently ranked among the happiest countries in the World Happiness Report. They argue that Nordic happiness comes from several connected factors, including generous welfare benefits, high-quality government institutions, low corruption, freedom to make life choices, and strong social trust. Using previous research and Gallup World Poll data, they compare the Nordic countries with wealthy non-Nordic countries and find that wealth alone cannot explain their higher Ladder Scores. The authors also challenge common explanations such as cold weather, small populations, and cultural homogeneity, since these factors do not appear to have a major effect on life satisfaction. This source is important to our research because our visualizations show that Nordic and Western European countries have some of the highest Ladder Scores. It provides possible explanations for this geographical pattern and shows why GDP is not the only factor connected to happiness. However, the authors acknowledge that it is difficult to determine cause and effect because institutional quality, welfare benefits, freedom, and social trust are strongly connected. The chapter also focuses on overall life evaluation rather than daily positive emotions. This distinction is important because the Ladder Score in our dataset measures how people evaluate their lives, not how happy or cheerful they feel every day.

In this article, the authors analyze Bhutan’s Gross National Happiness (GNH), which the country has utilized in favor of GDP as a measure of GDP as GNH is multidimensional and considers more cultural, emotional, and spiritual aspects of one’s life while GDP only measures production of goods and not people’s actual perceived well being; in their analysis, the main argument the authors make is that GNH is not a sudden tool created by Bhutanese elites to keep their rule, but was rather developed overtime by incorporating ideals from Bhutanese culture, including Buddhist philosophy, and for keeping a sense of national security, which makes the authors encourage on how other countries, perhaps more multicultural, could make happiness indexes that represent all citizens. The authors use the 5-7th five year plans of Bhutan, their historical context and geography as a Buddhist kingdom, and Buddhist views to encourage the rise of GNH. Overall, this source is significant as it provides a deep dive into other methods of analyzing happiness in a society in contrast to the Cantril ladder, and opens up into the idea that perhaps in terms of happiness indexes, one size does not fit all societies. In my thesis, this paper has a more supplemental role, as we plan to utilize mentions of this paper for our timeline in terms of analyzing has happiness has been measured and introducing the idea that happiness can be measured in other ways; however, unlike the past 2 papers, it’s not meant to be supporting a very concrete/established idea, but rather, more of a theoretical idea of what is really means to measure happiness. One main critique of this paper given the context in which we are using it is that it is more of a rebuttal/defensive paper rather than just being a neutral standpoint. The paper was meant to be a rebuttal to those who called GNH a tool used by Bhutanese elites to maintain their power, which forces the paper to have some bias towards the model; additionally, for a paper meant to serve as a rebuttal of GNH not being a tool of the elite, it doesn’t really discuss how effective the GNH has been and is in truly measuring happiness.

In this article, the authors start off by arguing how he believes happiness and meaning are not the only ways to have a fulfilling life and introduce the idea of a “psychologically rich life” as a third dimension of well being. Then go on to explain that individuals may experience a high quality of life through challenges, and experiences that impact individuals perspectives on certain aspects, even if those experiences are not always associated with the traditional definition of happiness. To support the claim, the authors end up reviewing psychological research, cross cultural studies, and survey data examining how people define life satisfaction and fulfillment across different societies. This resource is very important because it shows the traditional definition of well being on a different scale by showcasing that happiness scores alone do not capture every aspect of human happiness. For the thesis, this article provides additional support for explaining the concept behind international happiness rankings since different cultures may value different aspects of well being. It also highlights a limitation of the World Happiness Report by suggesting that numerical happiness scores may overlook other meaningful aspects of quality of life.

The researchers Oishi and his colleagues abandoned the common practice of asking about earnings without reason. Instead, they studied how the distribution of earnings affects individuals’ wellbeing. They found that Americans were happier in years when earnings were more equally distributed and less happy in years when earnings inequality was increasing. Their findings come from the General Social Survey, conducted continuously from 1972 until 2008. According to their version of events, when income inequality increases, people tend to believe that others become less fair and trustworthy. Moreover, it should be noted that the lower the income level is, the greater the effect of income inequality is. The good news is that their results might support our work because we also have GDP per capita and no information on how income is distributed domestically, but their conclusions are alarming. The limitations of their research include a narrow basis of data because their survey is limited to the USA only, and what is worse, their results do not prove that it is precisely income inequality that is affecting the individuals’ life quality.

In this article, the authors are examining the relationship between perceived corruption (PC) and subjective well-being (SWB). The article mentions the “Boiling Frog Parable”, which is the idea of how a frog would leave a pot of water if it is boiling already compared to if it was to be gradually heated; this exemplifies how people may not perceive corruption if they do not understand that it has been happening for a while. Noting how European countries tend to have a higher SWB level compared to others, the authors conclude that similar institutional frameworks should follow to improve ethical progress. However, there still remains a possibility that the parable applies, which may alter a country’s perceived corruption even though corruption may exist at a greater magnitude. Analyzing directly from our database, this source relates heavily to our project. One critique that I have is that how do you define a country’s corruption more objectively when taking into account citizens’ perception and the Boiling Frog Parable.

In this article, Rojas utilizes the conceptual-referent theory of happiness (CRT) to explain the weak but statistically significant relationship between income and well-being. CRT is based on the idea that different personal upbringing leads to different understandings of what a happy life looks like. Balanced by household income, gender, and the urban-rural spectrum, the survey uses 1540 questionnaires across Central Mexico. Regardless of individual differences, this aforementioned relationship followed the same CRT explanation, demonstrating that income may or may not be necessary for a person’s happiness. With different countries having different income levels, this information can provide evidence that GDP per capita from the World Happiness Report might not be a reliable measure of happiness. One critique is that this survey only comes from Central Mexico so the results in other countries may be completely different.

Swami and his colleagues examine whether the Satisfaction With Life Scale measures life satisfaction consistently across different countries, languages, gender identities, and age groups. The scale asks participants to respond to five statements that ask about how satisfied they are with their lives. This data collected 56,968 participants in 65 nations and 40 languages between 2020 and 2022. Using this data, the researchers test whether people from different backgrounds interpret the scale in similar ways. They explain that the data is a “widely used self-report measure of subjective well-being,” but previous research had not tested it across such a large and diverse international sample. The study finds that the scale generally measures the same “common unidimensional construct” across the aforementioned categories, meaning that it can be useful for comparing life satisfaction between different populations. However, the authors also find some variation in how individual questions on the scale are interpreted across countries and languages. These differences demonstrate that culture and the way these surveys are translated may influence the way people respond, even when the overall scale remains reliable. The researchers found large differences in average life satisfaction between different nations, while the differences surrounding gender and identity are much smaller. They also admit that their sample did not nationally represent the population and it also included more women and younger adults. This places limits on how broadly their findings can be applied to society. This peer reviewed source is credible because similarly to the previous reading, it uses a large international dataset, as well as following consistent research procedures. This resource supports the use of life satisfaction surveys for comparisons when it comes to the international level while also demonstrating that there are various other influences that must be considered when interpreting global happiness data.

In this article, Wierzbicka questions whether happiness can be accurately compared across different languages and cultures. She argues that happiness studies often assume that words such as happy, heureux, and glücklich have the same meaning, even though they may describe different levels or types of positive feelings. For example, the English word happy can describe moderate satisfaction, while similar words in several European languages often refer to a stronger or more complete state of happiness. She also explains that Chinese words related to happiness do not have exactly the same meaning as the English word. In addition, cultural expectations can affect how people report positive feelings. American culture, for example, often encourages smiling, cheerfulness, and positive expressions, while other cultures may be less likely to openly express happiness. Therefore, higher reported happiness does not necessarily mean that people in one country are actually happier than people in another. This source is important to our research because the World Happiness dataset compares Ladder Scores across countries with different languages and cultural backgrounds. It helps us examine whether people interpret and report happiness differently. However, the article mainly relies on linguistic examples and personal accounts rather than international survey data, so it does not prove that language causes differences in national happiness scores. Overall, it supports our use of language as one possible cultural influence when interpreting the dataset.