The average for 2024 based on 138 countries was 5.56 points. The highest value was in Finland: 7.74 points and the lowest value was in Afghanistan: 1.72 points. The indicator is available from 2013 to 2024. Below is a chart for all countries where data are available.

This statistic shows the results of a survey, conducted in 2013 among adult Americans, on whether they are as happy now as they expected to be at this stage of their life. 28 percent of respondents said they are even happier than expected now.

The average for 2024 based on 18 countries was 6.16 points. The highest value was in Costa Rica: 6.96 points and the lowest value was in Venezuela: 5.61 points. The indicator is available from 2013 to 2024. Below is a chart for all countries where data are available.

This statistic shows the results of a survey conducted in the United States in 2017 regarding how happy Americans are with their current relationship, on a scale from 1 (not happy at all) to 10 (very happy), by gender. Some 38 percent of female respondents stated they are very happy.

Dataset Card for World Happiness Report

  Dataset Summary





  Context

The World Happiness Report is a landmark survey of the state of global happiness. The first report was published in 2012, the second in 2013, the third in 2015, and the fourth in the 2016 Update. The World Happiness 2017, which ranks 155 countries by their happiness levels, was released at the United Nations at an event celebrating International Day of Happiness on March 20th. The report continues… See the full description on the dataset page: https://huggingface.co/datasets/nateraw/world-happiness.

This statistic shows the results of a survey among American adults on their happiness with their current living standards, by social class. The survey was conducted in July 2012, shortly before the presidential election. 32 percent of Americans who define themselves as members of the middle class stated they were very happy with their life nowadays, while 20 percent of Americans belonging to the lower class stated the same.

Finland was ranked the happiest country in the world, according to the World Happiness Report from 2025. The Nordic country scored 7.74 on a scale from 0 to 10. Two other Nordic countries, Denmark and Iceland, followed in second and third place, respectively. The World Happiness Report is a landmark survey of the state of global happiness that ranks countries by how happy their citizens perceive themselves to be. Criticism The index has received criticism from different perspectives. Some argue that it is impossible to measure general happiness in a country. Others argue that the index places too much emphasis on material well-being as well as freedom from oppression. As a result, the Happy Planet Index was introduced, which takes life expectancy, experienced well-being, inequality of outcomes, and ecological footprint into account. Here, Costa Rica was ranked as the happiest country in the world. Afghanistan is the least happy country Nevertheless, most people agree that high levels of poverty, lack of access to food and water, as well as a prevalence of conflict are factors hindering public happiness. Hence, it comes as no surprise that Afghanistan was ranked as the least happy country in the world in 2024. The South Asian country is ridden by poverty and undernourishment, and topped the Global Terrorism Index in 2024.

A survey from 2023 found that 25 percent of Gen Z respondents in the United States considered themselves to be a happy person. Only 11 percent of respondents stated they considered themselves to be a very unhappy or somewhat unhappy person.

About this dataset

Context

The dataset tabulates the Happy population distribution across 18 age groups. It lists the population in each age group along with the percentage population relative of the total population for Happy. The dataset can be utilized to understand the population distribution of Happy by age. For example, using this dataset, we can identify the largest age group in Happy.

Key observations

The largest age group in Happy, TX was for the group of age 10 to 14 years years with a population of 127 (16.75%), according to the ACS 2019-2023 5-Year Estimates. At the same time, the smallest age group in Happy, TX was the 75 to 79 years years with a population of 5 (0.66%). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group in consideration
• Population: The population for the specific age group in the Happy is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of Happy total population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Happy Population by Age. You can refer the same here

A survey from 2023 found that ** percent of Gen Z adults aged 24 to 26 years in the United States considered themselves to be a very happy or somewhat happy person. This share was almost the same for those aged 18 to 23, but higher for those aged 12 to 17.

About this dataset

Context

The dataset tabulates the data for the Happy, TX population pyramid, which represents the Happy population distribution across age and gender, using estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. It lists the male and female population for each age group, along with the total population for those age groups. Higher numbers at the bottom of the table suggest population growth, whereas higher numbers at the top indicate declining birth rates. Furthermore, the dataset can be utilized to understand the youth dependency ratio, old-age dependency ratio, total dependency ratio, and potential support ratio.

Key observations

• Youth dependency ratio, which is the number of children aged 0-14 per 100 persons aged 15-64, for Happy, TX, is 57.6.
• Old-age dependency ratio, which is the number of persons aged 65 or over per 100 persons aged 15-64, for Happy, TX, is 15.0.
• Total dependency ratio for Happy, TX is 72.7.
• Potential support ratio, which is the number of youth (working age population) per elderly, for Happy, TX is 6.7.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group for the Happy population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Happy for the selected age group is shown in the following column.
• Population (Female): The female population in the Happy for the selected age group is shown in the following column.
• Total Population: The total population of the Happy for the selected age group is shown in the following column.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Happy Population by Age. You can refer the same here

About this dataset

Context

The dataset tabulates the Happy Valley population distribution across 18 age groups. It lists the population in each age group along with the percentage population relative of the total population for Happy Valley. The dataset can be utilized to understand the population distribution of Happy Valley by age. For example, using this dataset, we can identify the largest age group in Happy Valley.

Key observations

The largest age group in Happy Valley, OR was for the group of age 5 to 9 years years with a population of 2,391 (9.35%), according to the ACS 2019-2023 5-Year Estimates. At the same time, the smallest age group in Happy Valley, OR was the 80 to 84 years years with a population of 496 (1.94%). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group in consideration
• Population: The population for the specific age group in the Happy Valley is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of Happy Valley total population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Happy Valley Population by Age. You can refer the same here

This statistic shows the results of a 2014 Popsugar survey among American women asking them which three brands make them the happiest. During the survey, **** percent of female respondents said MAC make them the happiest.

We survey 561 students from U.S. medical schools shortly after they submit choice rankings over residencies to the National Resident Matching Program. We elicit (a) these choice rankings, (b) anticipated subjective well-being (SWB) rankings, and (c) expected features of the residencies (such as prestige). We find substantial differences between choice and anticipated-SWB rankings in the implied tradeoffs between residency features. In our data, evaluative SWB measures (life satisfaction and Cantril's ladder) imply tradeoffs closer to choice than does affective happiness (even time-integrated), and as close as do multi-measure SWB indices. We discuss implications for using SWB data in applied work.

Financial overview and grant giving statistics of American Friends of Happy Hearts Inc.

The statistic above provides information about the income level in the United States at which money won't make you happier. In 2010, a household in Hawaii needs to make about 122 thousand U.S. dollars per year to reach the happiness plateau, in which more income doesn't provide better emotional well-being. The state-by-state comparison takes into account the disparity in cost of living between the states.

Since 2020, the world has faced two unprecedented shocks: lockdowns (regulation) and the invasion of Ukraine (war). Although we realise the health and economic effects of these shocks, more research is needed on the effect on happiness and whether the type of shock plays a role. Therefore, in this paper, we determine whether these macro-level shocks affected happiness, how these effects differ, and how long it takes for happiness to adapt to previous levels. The latter will allow us to test whether adaptation theory holds at the macro level. We use a unique dataset of ten countries spanning the Northern and Southern hemispheres derived from tweets extracted in real-time per country. Applying Natural Language Processing, we obtain these tweets’ underlying sentiment scores, after which we calculate a happiness score (Gross National Happiness) and derive daily time series data. Our Twitter dataset is combined with Oxford’s COVID-19 Government Response Tracker data. Considering the results of the Difference-in-Differences and event studies jointly, we are confident that the shocks led to lower happiness levels, both with the lockdown and the invasion shock. We find that the effect size is significant and that the lockdown shock had a bigger effect than the invasion. Considering both types of shocks, the adaptation to previous happiness levels occurred within two to three weeks. Following our findings of similar behaviour in happiness to both types of shocks, the question of whether other types of shocks will have similar effects is posited. Regardless of the length of the adaptation period, understanding the effects of macro-level shocks on happiness is essential for policymakers, as happiness has a spillover effect on other variables such as production, safety and trust.

About this dataset

Context

The dataset tabulates the population of Happy by gender, including both male and female populations. This dataset can be utilized to understand the population distribution of Happy across both sexes and to determine which sex constitutes the majority.

Key observations

There is a slight majority of female population, with 50.26% of total population being female. Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis. No further analysis is done on the data reported from the Census Bureau.

Variables / Data Columns

• Gender: This column displays the Gender (Male / Female)
• Population: The population of the gender in the Happy is shown in this column.
• % of Total Population: This column displays the percentage distribution of each gender as a proportion of Happy total population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Happy Population by Race & Ethnicity. You can refer the same here

U.S. Census Bureau QuickFacts statistics for Happy Valley city, Oregon. QuickFacts data are derived from: Population Estimates, American Community Survey, Census of Population and Housing, Current Population Survey, Small Area Health Insurance Estimates, Small Area Income and Poverty Estimates, State and County Housing Unit Estimates, County Business Patterns, Nonemployer Statistics, Economic Census, Survey of Business Owners, Building Permits.

Since 2020, the world has faced two unprecedented shocks: lockdowns (regulation) and the invasion of Ukraine (war). Although we realise the health and economic effects of these shocks, more research is needed on the effect on happiness and whether the type of shock plays a role. Therefore, in this paper, we determine whether these macro-level shocks affected happiness, how these effects differ, and how long it takes for happiness to adapt to previous levels. The latter will allow us to test whether adaptation theory holds at the macro level. We use a unique dataset of ten countries spanning the Northern and Southern hemispheres derived from tweets extracted in real-time per country. Applying Natural Language Processing, we obtain these tweets’ underlying sentiment scores, after which we calculate a happiness score (Gross National Happiness) and derive daily time series data. Our Twitter dataset is combined with Oxford’s COVID-19 Government Response Tracker data. Considering the results of the Difference-in-Differences and event studies jointly, we are confident that the shocks led to lower happiness levels, both with the lockdown and the invasion shock. We find that the effect size is significant and that the lockdown shock had a bigger effect than the invasion. Considering both types of shocks, the adaptation to previous happiness levels occurred within two to three weeks. Following our findings of similar behaviour in happiness to both types of shocks, the question of whether other types of shocks will have similar effects is posited. Regardless of the length of the adaptation period, understanding the effects of macro-level shocks on happiness is essential for policymakers, as happiness has a spillover effect on other variables such as production, safety and trust.