The Gross Domestic Product per capita in European Union was last recorded at 34859.60 US dollars in 2024. The GDP per Capita in European Union is equivalent to 276 percent of the world's average. This dataset provides the latest reported value for - European Union GDP Per Capita - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

This dataset was created in order to document self-reported life evaluations among small-scale societies that exist on the fringes of mainstream industrialized socieities. The data were produced as part of the LICCI project, through fieldwork carried out by LICCI partners. The data include individual responses to a life satisfaction question, and household asset values. Data from Gallup World Poll and the World Values Survey are also included, as used for comparison. TABULAR DATA-SPECIFIC INFORMATION --------------------------------- 1. File name: LICCI_individual.csv Number of rows and columns: 2814,7 Variable list: Variable names: User, Site, village Description: identification of investigator and location Variable name: Well.being.general Description: numerical score for life satisfaction question Variable names: HH_Assets_US, HH_Assets_USD_capita Description: estimated value of representative assets in the household of respondent, total and per capita (accounting for number of household inhabitants) 2. File name: LICCI_bySite.csv Number of rows and columns: 19,8 Variable list: Variable names: Site, N Description: site name and number of respondents at the site Variable names: SWB_mean, SWB_SD Description: mean and standard deviation of life satisfaction score Variable names: HHAssets_USD_mean, HHAssets_USD_sd Description: Site mean and standard deviation of household asset value Variable names: PerCapAssets_USD_mean, PerCapAssets_USD_sd Description: Site mean and standard deviation of per capita asset value 3. File name: gallup_WVS_GDP_pk.csv Number of rows and columns: 146,8 Variable list: Variable name: Happiness Score, Whisker-high, Whisker-low Description: from Gallup World Poll as documented in World Happiness Report 2022. Variable name: GDP-PPP2017 Description: Gross Domestic Product per capita for year 2020 at PPP (constant 2017 international $). Accessed May 2022. Variable name: pk Description: Produced capital per capita for year 2018 (in 2018 US$) for available countries, as estimated by the World Bank (accessed February 2022). Variable names: WVS7_mean, WVS7_std Description: Results of Question 49 in the World Values Survey, Wave 7.

India PFS: RBI: Gross Fixed Capital Formation as % of(GDP) Gross Domestic Productat Current Market Price: Next 3 Quarters: Mean data was reported at 29.600 % in Mar 2019. This records an increase from the previous number of 29.200 % for Dec 2018. India PFS: RBI: Gross Fixed Capital Formation as % of(GDP) Gross Domestic Productat Current Market Price: Next 3 Quarters: Mean data is updated quarterly, averaging 29.850 % from Mar 2008 (Median) to Mar 2019, with 44 observations. The data reached an all-time high of 36.700 % in Dec 2009 and a record low of 26.200 % in Mar 2012. India PFS: RBI: Gross Fixed Capital Formation as % of(GDP) Gross Domestic Productat Current Market Price: Next 3 Quarters: Mean data remains active status in CEIC and is reported by Reserve Bank of India. The data is categorized under India Premium Database’s Business and Economic Survey – Table IN.SE040: Professional Forecasters Survey (PFS): Reserve Bank of India: Quarterly Forecasts: Gross Fixed Capital Formation as % of GDP at Current Market Price.

The World Happiness Report is a partnership of Gallup, the Oxford Wellbeing Research Centre, the UN Sustainable Development Solutions Network, and the WHR’s Editorial Board. The report is produced under the editorial control of the WHR Editorial Board.

The World Happiness Report reflects a worldwide demand for more attention to happiness and well-being as criteria for government policy. It reviews the state of happiness in the world today and shows how the science of happiness explains personal and national variations in happiness.

The report primarily uses data from the Gallup World Poll. As of March 2024, Finland has been ranked the happiest country in the world seven times in a row.

Attribute Information

• Country Name: Name of the country.
• Happiness Rank: Rank of the country
• Happiness Score: Score of the country.
• Upperwhisker : Upper score
  • Lowerwhisker : Lower score
• Economy (GDP per Capita) : GDP
• Social support: Score from social support
• Healthy life expectancy: Score from Life Expectancy
• Freedom to make life choices: Score from Freedom
• Generosity: Score from Generosity
• Perceptions of corruption: Score from Perceptions of corruption

Acknowledgements

https://worldhappiness.report/

Photo by Sasha Freemind on Unsplash

Context

The World Happiness Ranking focuses on the social, urban, and natural environment. Specifically, the ranking relies on self-reports from residents of how they weigh the quality of life they are currently experiencing which englobes three main points: current life evaluation, expected future life evaluation, positive and negative affect (emotion). Half of the underlying data comes from multiple Gallup world polls which asked people to give their assessment of the previously mentioned points, and the other half of the data is comprised of six variables that could be used to try to explain the individuals’ perception in their answers.

Content

The data sources’ datasets were obtained in two different formats. The World Happiness Ranking Dataset is a Comma-separated Values (CSV) file with multiple columns (for the different variables and the score) and a row for each of the analyzed countries.

The rankings of national happiness are based on a Cantril ladder survey. Nationally representative samples of respondents are asked to think of a ladder, with the best possible life for them being a 10, and the worst possible life being a 0. They are then asked to rate their own current lives on that 0 to 10 scale. The report correlates the results with various life factors.

1. GDP per capita is in terms of Purchasing Power Parity (PPP) adjusted to constant 2011 international dollars, taken from the World Development Indicators (WDI) released by the World Bank on November 28, 2019. See Statistical Appendix 1 for more details. GDP data for 2019 are not yet available, so we extend the GDP time series from 2018 to 2019 using country-specific forecasts of real GDP growth from the OECD Economic Outlook No. 106 (Edition November 2019) and the World Bank’s Global Economic Prospects (Last Updated: 06/04/2019), after adjustment for population growth. The equation uses the natural log of GDP per capita, as this form fits the data significantly better than GDP per capita.
2. The time series of healthy life expectancy at birth are constructed based on data from the World Health Organization (WHO) Global Health Observatory data repository, with data available for 2005, 2010, 2015, and 2016. To match this report’s sample period, interpolation and extrapolation are used. See Statistical Appendix 1 for more details.
3. Social support is the national average of the binary responses (0=no, 1=yes) to the Gallup World Poll (GWP) question, “If you were in trouble, do you have relatives or friends you can count on to help you whenever you need them, or not?”
4. Freedom to make life choices is the national average of binary responses to the GWP question, “Are you satisfied or dissatisfied with your freedom to choose what you do with your life?”
5. Generosity is the residual of regressing the national average of GWP responses to the question, “Have you donated money to a charity in the past month?” on GDP per capita.
6. Perceptions of corruption are the average of binary answers to two GWP questions: “Is corruption widespread throughout the government or not?” and “Is corruption widespread within businesses or not?” Where data for government corruption are missing, the perception of business corruption is used as the overall corruption-perception measure.
7. Positive affect is defined as the average of previous-day affect measures for happiness, laughter, and enjoyment for GWP waves 3-7 (years 2008 to 2012, and some in 2013). It is defined as the average of laughter and enjoyment for other waves where the happiness question was not asked. The general form for the affect questions is: Did you experience the following feelings during a lot of the day yesterday? See Statistical Appendix 1 for more details.
8. Negative affect is defined as the average of previous-day affect measures for worry, sadness, and anger in all years.

Acknowledgements

The World Happiness Report is a publication of the Sustainable Development Solutions Network, powered by data from the Gallup World Poll, and supported by the Ernesto Illy Foundation, illycaffè, Davines Group, Blue Chip Foundation, the William, Jeff, and Jennifer Gross Family Foundation, and Unilever’s largest ice cream brand Wall’s.

Inspiration

Find the relationship between the ladder score and the other pieces of data.

Abstract

Over the past decade, Albania has been undergoing a transition toward a market economy and a more open society. It has faced severe internal and external challenges, such as lack of basic infrastructure, rapid collapse of output and inflation rise after the collapse of the communist regime, turmoil during the 1997 pyramid crisis, and social and economic instability because of the 1999 Kosovo crisis. Despite these shocks, Albanian economy has recovered from a very low income level through a sustained growth during the past few years, even though it remains one of the poorest countries in Europe, with GDP per capita at around 1,300$. Based on the Living Standard Measurement Study (LSMS) 2002 survey data (wave 1, henceforth), for the first time in Albania INSTAT has computed an absolute poverty line on a nationally representative poverty survey at household level. Based on this welfare measure, one quarter (25.4 percent) of the Albanian population, or close to 790,000 individuals, were defined as poor in 2002. The distribution of poverty is also disproportionately rural, as 68 percent of the poor are in rural areas, against 32 percent in urban areas (as compared to a total urban population well over 40 percent). These estimates are quite sensitive to the choice of the poverty line, as there are a large number of households clustered around the poverty line. Income related poverty is compounded by the severe lack of access to basic infrastructure, education and health services, clean water, etc., and the ability of the Government to address these issues is complicated by high levels of internal and external migration that are not well understood. The availability of a nationally representative survey is crucial as the paucity of household-level information has been a constraining factor in the design, implementation and evaluation of economic and social programs in Albania. Two recent surveys carried out by the Albanian Institute of Statistics (INSTAT) -the 1998 Living Conditions Survey (LCS) and the 2000 Household Budget Survey (HBS) - drew attention, once again, to the need for accurately measuring household welfare according to well-accepted standards, and for monitoring these trends on a regular basis. This target is well-achieved by drawing information over time on a panel component of LSMS 2002 households, namely the Albanian Panel Survey (APS), conducted in 2003 and 2004. An increasing attention to the policies aimed at achieving the Millennium Development Goals (MDGs) is paid by the National Parliament of Albania, recently witnessed by the resolution approved in July 2003, where it pushes “… the total commitment of both state structures and civil society to achieve the MDGs in Albania by 2015”. The path towards a sustained growth is constantly monitored through the National Reports on Progress toward Achieving the MDGs, which involves a close collaboration of the UN with the national institutions, led by the National Strategy for Social and Economic Development (NSSED) Department of the Ministry of Finance. Also, in the process leading to the Poverty Reduction Strategy Paper (PRSP; also known in Albania as Growth and Poverty Reduction Strategy, GPRS), the Government of Albania reinforced its commitment to strengthening its own capacity to collect and analyse on a regular basis information it needs to inform policy-makers. In its first phase (2001-2006), this monitoring system will include the following data collection instruments:

(i) Population and Housing Census (ii) Living Standards Measurement Surveys every 3 years (iii) Annual panel surveys.

The focus during this first phase of the monitoring system is on a periodic LSMS (in 2002 and 2005), followed by panel surveys on a sub-sample of LSMS households (APS 2003, 2004 and 2006), drawing heavily on the 2001 census information. Here our target is to illustrate the main characteristics of the APS 2004 data with reference to the LSMS. The survey work was undertaken by the Living Standards Unit of INSTAT, with the technical assistance of the World Bank.

Geographic coverage

National

Analysis unit

Households

Kind of data

Sample survey data [ssd]

Sampling procedure

(a) SAMPLE DESIGN

Panel sample, with LSMS 2002 and 2004 The APS 2004 collects information on 1,797 valid observations at household level and 7,476 at individual level. The sample of the second and third waves of the panel (APS) has been selected from the LSMS 2002 in order to be representative of Albanian households and individuals at national level. The LSMS 2002 differs from the APS 2003 and 2004 in that the former is designed to be representative at regional level (Mountain, Central, Coastal and Tirana) as well as for urban and rural domains, while the latter are for last domains only (urban and rural) LSMS 2002 sample design The LSMS is based on a probability sample of housing units (HUs) within the 16 strata of the sampling frame. It is divided in three regions: Coastal, Central, and Mountain Area. In addition, urban areas of Tirana are also considered as a separate region/stratum. The three regions are further stratified in major cities (the most important cities in the region), other urban (other cities in the region), and rural. The city of Tirana and its suburbs have been implicitly stratified to improve the efficiency of the sample design. Each stratum has been divided in Enumeration Area (EA), in accordance with the 2001 Census data, and each Primary Sampling Unit (PSU) selected with probabilities proportional to the number of occupied HUs in the EA. Every EA includes occupied and unoccupied HUs. Occupied rather than total units have been used because of the large number of empty dwellings registered in the Census data. The Housing Unit, defined as the space occupied by one household, is taken as sampling unit because is more permanent and easier to identify compared to the household. 10 EAs for each major city (75 for Tirana) and 65 EAs for each rural region -with the exception of the mountain area which is over-represented (75 EAs)- are selected. 8 households, plus 4 eventual substitutes, have been systematically selected in each EAs. As the LSMS consists of 450 EAs, total sample size is 3,600 households.

(b) STRATIFICATION

The panel component selected from the LSMS is designed to provide a nationally representative sample of households and individuals within Albania. It consists of roughly half of the households in the 2002 LSMS, interviewed both in 2003 and 2004. Contrarily to what done for the LSMS, no over-sampling in the Mountain Area has been performed for the panel survey. The sample is designed to minimize the variability in households' selection probabilities. It ensures national representativeness by matching the sample distribution across strata with the population distribution drawn from 2001 Census data. In Table 3 the ex-ante sampling scheme of the 2003-2004 APS is shown. Compared to the LSMS design, statistical precision has improved. Under equal stratum population variances hypothesis, sample design effects are expected to be around 1.02, compared to the 1.28 of the LSMS sample. Moreover, further precision is obtained by keeping all 450 EAs of LSMS in the panel sample, thus reducing the eventual bias due to clustering because of new design. Finally, the panel survey has a number of peculiar features that should be considered when using the data. The sample is designed to focus on individuals, who have been also traced when moving from the original household to a new one. This possibility represents the only way a household can enter the panel sample if it has not been already interviewed in the wave 1 (or in wave 2 for the APS 2004). If an original survey member (OSM) moves to a new household, his/her old and new household -and their members- are both included in the panel sample. Though a moved OSM will be present in the roster of both sampled households, he/she is a valid member only in the new one. In the old household he/she is considered as "moved away", hence not a valid member. This might generate some confusion. Three modalities exist to classify an individual in the third wave. First, when he/she is an OSM, that is a respondent interviewed both in wave 1 and 2. Second, when he is a re-joiner from 2002, that is an OSM not interviewed in 2003 (i.e. because temporarily absent) who returns in 2004. Third, when he/she is a new member, whenever he/she is a newborn of an original household, a member joined by an OSM or a person who co-resides with an original survey household. So, the APS is an indefinite life panel study, without replacement by drawing new sample units. From wave 2, only individuals aged 15 years and over are considered valid members, hence eligible for the interview. Individuals moved out of Albania are not accounted as valid for this survey year, though they are still eligible for future waves.

Mode of data collection

Face-to-face [f2f]

Cleaning operations

A first data cleaning took place in Albania and implemented by INSTAT in collaboration with ISER and Government of Albania consultants. The cleaning process has involved following activities: 1. defining data checking routines and writing the syntax code of the cleaning programs; 2. generating lists of outliers and inconsistencies for each module to be checked against paper questionnaires; During the first few days, data cleaning operators have been working on the Export Procedure of the Data Entry Program to check if data export succeeded and to finalize the English version of the dictionaries and error messages. Some changes were made to the Export Procedure due to a problem on the “Agriculturea2” file conversion and to the

Context

Happiness and well-being are essential indicators of societal progress, often influenced by economic conditions such as GDP and inflation. This dataset combines data from the World Happiness Index (WHI) and inflation metrics to explore the relationship between economic stability and happiness levels across 148 countries from 2015 to 2023. By analyzing key economic indicators alongside social well-being factors, this dataset provides insights into global prosperity trends.

Content

This dataset is provided in CSV format and includes 16 columns, covering both happiness-related features and economic indicators such as GDP per capita, inflation rates, and corruption perception. The main columns include:

Happiness Score & Rank (World Happiness Index ranking per country) Economic Indicators (GDP per capita, inflation metrics) Social Factors (Freedom, Social Support, Generosity) Geographical Information (Country & Continent)

Acknowledgements

The dataset is created using publicly available data from World Happiness Report, Gallup World Poll, and the World Bank. It has been structured for research, machine learning, and policy analysis purposes.

Inspiration

How do economic factors like inflation, GDP, and corruption affect happiness? Can we predict a country's happiness score based on economic conditions? This dataset allows you to analyze these relationships and build models to predict well-being trends worldwide.

Detailed information about each of the Predictors

1. Log GDP per capita is in terms of Purchasing Power Parity (PPP) adjusted to a constant 2017 international dollars, taken from the World Development Indicators (WDI) by the World Bank (version 17, metadata last updated on January 22, 2023). See Statistical Appendix 1 for more details. GDP data for 2022 are not yet available, so we extend the GDP time series from 2021 to 2022 using country-specific forecasts of real GDP growth from the OECD Economic Outlook No. 112 (November 2022) or, if missing, from the World Bank’s Global Economic Prospects (last updated: January 10, 2023), after adjustment for population growth. The equation uses the natural log of GDP per capita, as this form fits the data significantly better than GDP per capita. 2. The time series for Healthy life expectancy at birth is constructed based on data from the World Health Organization (WHO) Global Health Observatory data repository, with data available for 2005, 2010, 2015, 2016, and 2019. To match this report’s sample period (2005-2022), interpolation and extrapolation are used. See Statistical Appendix 1 for more details. 3. Social support (0-1) is the national average of the binary responses (0=no, 1=yes) to the Gallup World Poll (GWP) question “If you were in trouble, do you have relatives or friends you can count on to help you whenever you need them, or not?” 4. Freedom to make life choices (0-1) is the national average of binary responses to the GWP question “Are you satisfied or dissatisfied with your freedom to choose what you do with your life?” 5. Generosity is the residual of regressing the national average of GWP responses to the donation question “Have you donated money to a charity in the past month?” on log GDP per capita. 6. Perceptions of corruption (0-1) are the average of binary answers to two GWP questions: “Is corruption widespread throughout the government or not?” and “Is corruption widespread within businesses or not?” Where data for government corruption are missing, the perception of business corruption is used as the overall corruption perception measure. 7. Positive affect is defined as the average of previous-day effects measures for laughter, enjoyment, and interest. The inclusion of interest (first added for World Happiness Report 2022), gives us three components in each of positive and negative affect, and slightly improves the equation fit in column 4. The general form for the affect questions is: Did you experience the following feelings during a lot of the day yesterday? 8. Negative affect is defined as the average of previous-day effects measures for worry, sadness, and anger.

The World Happiness Report is a publication of the Sustainable Development Solutions Network, powered by the Gallup World Poll data. The World Happiness Report reflects a worldwide demand for more attention to happiness and well-being as criteria for government policy. It reviews the state of happiness in the world today and shows how the science of happiness explains personal and national variations in happiness.

Life evaluations from the Gallup World Poll provide the basis for the annual happiness rankings. They are based on answers to the main life evaluation question. The Cantril ladder asks respondents to think of a ladder, with the best possible life for them being a 10 and the worst possible life being a 0. They are then asked to rate their own current lives on a 0 to 10 scale. The rankings are from nationally representative samples over three years.

We use observed data on the six variables and estimates of their associations with life evaluations to explain the variation across countries. They include GDP per capita, social support, healthy life expectancy, freedom, generosity, and corruption. Our happiness rankings are not based on any index of these six factors – the scores are instead based on individuals’ own assessments of their lives, in particular, their answers to the single-item Cantril ladder life-evaluation question, much as epidemiologists estimate the extent to which life expectancy is affected by factors such as smoking, exercise, and diet.

The World Happiness Report and much of the growing international interest in happiness exist thanks to Bhutan. They sponsored Resolution 65/309, “Happiness: Towards a holistic approach to development,” adopted by the General Assembly of the United Nations on 19 July 2011, inviting national governments to “give more importance to happiness and well-being in determining how to achieve and measure social and economic development.”

On 2 April 2012, chaired by Prime Minister Jigmi Y. Thinley and Jeffrey D. Sachs, the first World Happiness Report was presented to review evidence from the emerging science of happiness for the ‘Defining a New Economic Paradigm: The Report of the High-L...

This statistic shows the results of a survey, conducted in 2013 among adult Americans, on whether they believe the glass is half full or half empty. 50 percent of respondents said they consider themselves optimists.

The optimism and pessimism of the American people

Optimism is defined as a mental attitude or worldview that favors a positive outcome, while pessimism favors a negative outcome or prediction. Depression in the United States is very common. In 2013, around 8.7 percent of U.S. adults aged between 18 and 25 reported that they had a major depression episode within the past year. Major depressive episodes in the United States are most common among American females. The number of prescription antidepressant drug use among women in the United States has increased by more than 10 percent between 1988 and 2012. Also in 2013, about one third of U.S. adults stated that they were happier than expected.

The general optimism and pessimism in a nation are often the result of its economic situation. The unemployment rate in the United States has been steadily decreasing every year since 2010; furthermore, it is expected to constantly decrease further until 2020. The prospering economy and increasing gross domestic product per capita in the United States is another source of optimism for the American people: The GDP per capita in the United States in 2014 was around 54,600 U.S. dollars. Moreover, it has been steadily increasing since 2010. In a survey conducted in July 2012, one third of Americans who defined themselves as lower-class stated that they were “not too happy” with their current lives. On the other hand, there was a larger percentage of people whom, according to themselves, belong to the upper class that stated that they were “very happy” with their current lives. In addition, upper- and middle-class American adults are more optimistic about the country’s long-term economic future in comparison to lower-class American adults.

Abstract

The World Values Survey (www.worldvaluessurvey.org) is a global network of social scientists studying changing values and their impact on social and political life, led by an international team of scholars, with the WVS association and secretariat headquartered in Stockholm, Sweden.

The survey, which started in 1981, seeks to use the most rigorous, high-quality research designs in each country. The WVS consists of nationally representative surveys conducted in almost 100 countries which contain almost 90 percent of the world’s population, using a common questionnaire. The WVS is the largest non-commercial, cross-national, time series investigation of human beliefs and values ever executed, currently including interviews with almost 400,000 respondents. Moreover the WVS is the only academic study covering the full range of global variations, from very poor to very rich countries, in all of the world’s major cultural zones.

The WVS seeks to help scientists and policy makers understand changes in the beliefs, values and motivations of people throughout the world. Thousands of political scientists, sociologists, social psychologists, anthropologists and economists have used these data to analyze such topics as economic development, democratization, religion, gender equality, social capital, and subjective well-being. These data have also been widely used by government officials, journalists and students, and groups at the World Bank have analyzed the linkages between cultural factors and economic development.

Geographic coverage

National.

Analysis unit

Household Individual

Universe

National Population, both sexes,18 and more years.

Kind of data

Sample survey data [ssd]

Sampling procedure

Sample size: 3401

The different stages in the sampling procedure were: - Self representative PSU´s (provinces) - Selected provinces (PPS selection with implied stratification according to income) - Districts within provinces - Urban and rural locations within districts (villages selected PPS within rural areas; neighbourhoods and streets selected within urban locations, households identified with systematic random selection, age and gender quotas used in the final selection of individuals).

The final numbers of clusters or sampling points were 22 PSU´s. The sampled unit we got from the office sampling was the address and the selection method that was used to identify a respondent was move on the next address until quota is filled. The quota control was 3 age groups and 2 gender groups were used as quotas. The stratification factors that was used: Per capita gdp. There were some limitations in the sample. It was a quota sample in the last stage as explained above. Overall, the design yields very satisfactory results.

Remarks about sampling: 3 age groups (18-27; 28-40; 41+) and 2 gender groups were used as quota controls. There were stratification factors per capita gdp. A known limitation of the realized sample: this was a quota sample in the last stage as explained. Overall, the design yields very satisfactory results

Mode of data collection

Face-to-face [f2f]

Research instrument

The WVS questionnaire was translated from the English questionnaire by a member of the research team. The translated questionnaire was not back-translated into English and also was pre-tested. There were some questions that caused problems when the questionnaire was translated especially questions assuming a church organisation were problematic. Also some of the irrelevant questions were omitted; some were asked nevertheless. There have not been any optional WVS questions and/or items been included, however country-specific questions were included. They were mostly included at the end of the questionnaire but some country specific additions were made to a confidence in institutions and b) neighbours questions. A number of questions were omitted because they sounded totally irrelevant for the local population or because previous surveys indicated that they did not work for this population. The sample was designed to be representative of the entire adult population, i.e. 18 years and older, of your country. The lower age cut-off for the sample was 18 and there was not any upper age cut-off for the sample.

Sampling error estimates

Estimated error: 1.7

PFS: RBI: Current Gross Fixed Capital Formation as % of GDP at Current Market Price: Current Quarter: Maximum在2019-03达31.000 %，相较于2018-12的29.300 %有所增长。PFS: RBI: Current Gross Fixed Capital Formation as % of GDP at Current Market Price: Current Quarter: Maximum数据按季度更新，2008-03至2019-03期间平均值为31.850 %，共44份观测结果。该数据的历史最高值出现于2011-03，达38.000 %，而历史最低值则出现于2011-12，为28.500 %。CEIC提供的PFS: RBI: Current Gross Fixed Capital Formation as % of GDP at Current Market Price: Current Quarter: Maximum数据处于定期更新的状态，数据来源于Reserve Bank of India，数据归类于India Premium Database的Business and Economic Survey – Table IN.SE040: Professional Forecasters Survey (PFS): Reserve Bank of India: Quarterly Forecasts: Gross Fixed Capital Formation as % of GDP at Current Market Price。

🌍 Global Happiness, Wellbeing & Development Indicators (2002–2024)

Integrated OWID datasets on happiness, GDP, governance, corruption, freedom, HDI, and life expectancy.

⭐ Overview

This dataset is a curated integration of multiple global indicators related to happiness, wellbeing, governance, corruption, freedom, gender rights, economic prosperity, and demographic development. All files are sourced from Our World in Data (OWID) and represent harmonized, research-grade metrics used by economists, policy analysts, academics, and data professionals around the world.

The goal of this dataset is to provide a single, easy-to-use resource for exploring the key factors that influence national wellbeing and quality of life across more than 170 countries from 2002 to 2024.

⭐ What’s Included

This dataset brings together multiple dimensions of global wellbeing:

- Happiness & Life Satisfaction - Cantril Ladder (0–10 life evaluation) - Share of people reporting happiness - Time-series emotional wellbeing indicators

- Economic Indicators - GDP per capita (PPP, constant 2021$) - Historical population estimates

- Governance & Institutional Quality - Corruption Perception Index (CPI) - Freedom House civil & political liberties - Women’s civil rights index

- Human Development & Health - Augmented Human Development Index (AHDI) - Life expectancy at birth

Each file has been kept exactly as published by OWID, with no modification of values, ensuring full transparency and reproducibility.

⭐ Why This Dataset Matters

Understanding what drives national wellbeing is a central question in modern economics, social science, and development policy. This dataset enables powerful analysis such as:

• Which countries achieve high happiness at lower income levels?
• Does economic growth lead to improvements in wellbeing?
• How do corruption, freedom, and gender rights influence happiness?
• Which regions show consistent improvement in human development?
• How do life expectancy and governance interact with wellbeing trends?

This collection is ideal for:

• Exploratory Data Analysis (EDA)
• Cross-country comparisons
• Regression modelling & causal inference
• Time-series and panel-data analytics
• Dashboard development
• Machine learning experiments
• Academic and applied research

⭐ Data Source

All datasets are published by Our World in Data (OWID), using original data from:

• Gallup World Poll
• World Bank
• Transparency International
• UN Population Division
• V-Dem Institute
• Freedom House
• International survey archives

Licensed under Creative Commons BY 4.0.

⭐ Temporal & Geospatial Coverage

• Years: 2002–2024
• Countries: 170+
• Regions: All OWID regions (Africa, Asia, Americas, Europe, Oceania)

⭐ Intended Audience

• Data Analysts
• Data Scientists
• Policy Researchers
• Social Scientists
• Students & educators
• Kaggle learners
• Anyone interested in global wellbeing

⭐ Summary

This dataset provides a comprehensive, ready-to-use foundation for studying global happiness, development, and governance. Whether you’re building visualizations, statistical models, dashboards, or research papers, this single dataset gives you everything you need to explore what shapes human wellbeing around the world.

PFS: RBI: Current Gross Fixed Capital Formation as % of GDP at Current Market Price: Current Quarter: Minimum在2019-03达23.000 %，相较于2018-12的27.900 %有所下降。PFS: RBI: Current Gross Fixed Capital Formation as % of GDP at Current Market Price: Current Quarter: Minimum数据按季度更新，2008-03至2019-03期间平均值为27.550 %，共44份观测结果。该数据的历史最高值出现于2008-03，达33.500 %，而历史最低值则出现于2012-03，为7.200 %。CEIC提供的PFS: RBI: Current Gross Fixed Capital Formation as % of GDP at Current Market Price: Current Quarter: Minimum数据处于定期更新的状态，数据来源于Reserve Bank of India，数据归类于India Premium Database的Business and Economic Survey – Table IN.SE040: Professional Forecasters Survey (PFS): Reserve Bank of India: Quarterly Forecasts: Gross Fixed Capital Formation as % of GDP at Current Market Price。

World Happiness Report

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 to gain global recognition as governments, organizations and civil society increasingly use happiness indicators to inform their policy-making decisions. Leading experts across fields – economics, psychology, survey analysis, national statistics, health, public policy and more – describe how measurements of well-being can be used effectively to assess the progress of nations. The reports review the state of happiness in the world today and show how the new science of happiness explains personal and national variations in happiness.

Content The happiness scores and rankings use data from the Gallup World Poll. The scores are based on answers to the main life evaluation question asked in the poll. This question, known as the Cantril ladder, asks respondents to think of a ladder with the best possible life for them being a 10 and the worst possible life being a 0 and to rate their own current lives on that scale. The scores are from nationally representative samples for the years 2013-2016 and use the Gallup weights to make the estimates representative. The columns following the happiness score estimate the extent to which each of six factors – economic production, social support, life expectancy, freedom, absence of corruption, and generosity – contribute to making life evaluations higher in each country than they are in Dystopia, a hypothetical country that has values equal to the world’s lowest national averages for each of the six factors. They have no impact on the total score reported for each country, but they do explain why some countries rank higher than others.

Inspiration What countries or regions rank the highest in overall happiness and each of the six factors contributing to happiness? How did country ranks or scores change between the 2015 and 2016 as well as the 2016 and 2017 reports? Did any country experience a significant increase or decrease in happiness?

What is Dystopia?

Dystopia is an imaginary country that has the world’s least-happy people. The purpose in establishing Dystopia is to have a benchmark against which all countries can be favorably compared (no country performs more poorly than Dystopia) in terms of each of the six key variables, thus allowing each sub-bar to be of positive width. The lowest scores observed for the six key variables, therefore, characterize Dystopia. Since life would be very unpleasant in a country with the world’s lowest incomes, lowest life expectancy, lowest generosity, most corruption, least freedom and least social support, it is referred to as “Dystopia,” in contrast to Utopia.

What are the residuals?

The residuals, or unexplained components, differ for each country, reflecting the extent to which the six variables either over- or under-explain average 2014-2016 life evaluations. These residuals have an average value of approximately zero over the whole set of countries. Figure 2.2 shows the average residual for each country when the equation in Table 2.1 is applied to average 2014- 2016 data for the six variables in that country. We combine these residuals with the estimate for life evaluations in Dystopia so that the combined bar will always have positive values. As can be seen in Figure 2.2, although some life evaluation residuals are quite large, occasionally exceeding one point on the scale from 0 to 10, they are always much smaller than the calculated value in Dystopia, where the average life is rated at 1.85 on the 0 to 10 scale.

What do the columns succeeding the Happiness Score(like Family, Generosity, etc.) describe?

The following columns: GDP per Capita, Family, Life Expectancy, Freedom, Generosity, Trust Government Corruption describe the extent to which these factors contribute in evaluating the happiness in each country. The Dystopia Residual metric actually is the Dystopia Happiness Score(1.85) + the Residual value or the unexplained value for each country as stated in the previous answer.

If you add all these factors up, you get the happiness score so it might be un-reliable to model them to predict Happiness Scores.

Interventions selected via the modified Delphi process among local experts on public health in Gaza, 2021.

India PFS: RBI: Gross Fixed Capital Formation as % of(GDP) Gross Domestic Productat Current Market Price: Current Fiscal Year: Median data was reported at 29.000 % in Mar 2019. This records a decrease from the previous number of 29.100 % for Dec 2018. India PFS: RBI: Gross Fixed Capital Formation as % of(GDP) Gross Domestic Productat Current Market Price: Current Fiscal Year: Median data is updated quarterly, averaging 29.500 % from Mar 2008 (Median) to Mar 2019, with 43 observations. The data reached an all-time high of 35.100 % in Jun 2009 and a record low of 26.400 % in Dec 2017. India PFS: RBI: Gross Fixed Capital Formation as % of(GDP) Gross Domestic Productat Current Market Price: Current Fiscal Year: Median data remains active status in CEIC and is reported by Reserve Bank of India. The data is categorized under India Premium Database’s Business and Economic Survey – Table IN.SE006: Professional Forecasters Survey (PFS): Reserve Bank of India: Annual Forecasts: Gross Fixed Capital Formation as % of GDP at Current Market Price.

This dataset covers typical areas of the Qinghai Tibet Plateau from 2018 to 2024, and constructs a vulnerability assessment system consisting of 18 core indicators at the county level. The data sources include authoritative publications such as the "National Sixth/Seventh Population Census Bulletin," "China County Construction Statistical Yearbook," "China County Statistical Yearbook," and statistical bulletins of various cities and counties. Combined with field research data from government departments, it is formed through multi-source data integration and standardization processing. The indicator system covers dimensions such as population structure (proportion of vulnerable population under 15 years old and proportion of population over 65 years old), economic foundation (per capita GDP, proportion of household savings deposits), infrastructure (road density, number of fixed telephone users), social services (proportion of beds, green land area), industrial structure (proportion of secondary/tertiary industry employment), disaster prevention (proportion of monitoring equipment, number of school disaster demonstration campuses), etc. All indicators are defined through strict statistical criteria (such as highway density=highway mileage/area), and the accuracy and timeliness of data sources are verified with relevant departments. At the same time, regular review and correction of data are conducted to ensure its reliability and validity. This dataset provides important quantitative support for regional sustainable development and disaster prevention and reduction planning.

Context

This year marks the 10th anniversary of the World Happiness Report, which uses global survey data to report how people evaluate their own lives in more than 150 countries worldwide. The World Happiness Report 2022 reveals a bright light in dark times. The pandemic brought not only pain and suffering but also an increase in social support and benevolence.

Content

This dataset contains the Happiness Score for 146 countries along with the factors used to explain the score. The scores are based on individuals' own assessments of their lives, as revealed by their answers to the single-item Cantril ladder life-evaluation question. Sustainable Development Solutions Network observed data on the six variables and estimates of their associations with life evaluations to explain the observed variation of life evaluations across countries, much as epidemiologists estimate the extent to which life expectancy is affected by factors such as smoking, exercise and diet. Before diving in, let’s briefly touch on how happiness levels are measured in this report. Some clear indicators are health and wealth, which are measured using key metrics like GDP per capita and life expectancy rates. The report also looks at more intangible aspects by collecting survey responses from each country, to gauge things like:

• Social support
• Freedom to make life choices
• Generosity
• Perceptions of government/ business corruption
• Dystopia(1.83) : the value for Dystopia (1.83) is the predicted Cantril ladder for a hypothetical country with the world's lowest values for each of the six variables.

The data is explained in much statistical detail here

Acknowledgements

The World Happiness Report is a publication of the Sustainable Development Solutions Network, powered by the Gallup World Poll data.

I did not create this data, only sourced it. The credit goes to the original Authors:

Editors: John Helliwell, Richard Layard, Jeffrey D. Sachs, Jan-Emmanuel De Neve, Lara B. Aknin, Shun Wang; and Sharon Paculor, Production Editor

Citation: Helliwell, J. F., Layard, R., Sachs, J. D., De Neve, J.-E., Aknin, L. B., & Wang, S. (Eds.). (2022). World Happiness Report 2022. New York: Sustainable Development Solutions Network.

Inspiration

• Compare happiness score with other attributes
• EDA and Visualization
• Country ranking highest in specific attributes

PFS: RBI: Gross Fixed Capital Formation as % of GDP at Current Market Price: Next 2 Quarters: Maximum在2019-03达29.800 %，相较于2018-12的29.900 %有所下降。PFS: RBI: Gross Fixed Capital Formation as % of GDP at Current Market Price: Next 2 Quarters: Maximum数据按季度更新，2008-03至2019-03期间平均值为31.550 %，共44份观测结果。该数据的历史最高值出现于2010-03，达37.800 %，而历史最低值则出现于2018-06，为29.300 %。CEIC提供的PFS: RBI: Gross Fixed Capital Formation as % of GDP at Current Market Price: Next 2 Quarters: Maximum数据处于定期更新的状态，数据来源于Reserve Bank of India，数据归类于India Premium Database的Business and Economic Survey – Table IN.SE040: Professional Forecasters Survey (PFS): Reserve Bank of India: Quarterly Forecasts: Gross Fixed Capital Formation as % of GDP at Current Market Price。

India PFS: RBI: Gross Fixed Capital Formation as % of(GDP) Gross Domestic Productat Current Market Price: Current Fiscal Year: Mean data was reported at 29.100 % in Mar 2019. This stayed constant from the previous number of 29.100 % for Dec 2018. India PFS: RBI: Gross Fixed Capital Formation as % of(GDP) Gross Domestic Productat Current Market Price: Current Fiscal Year: Mean data is updated quarterly, averaging 29.500 % from Mar 2008 (Median) to Mar 2019, with 43 observations. The data reached an all-time high of 35.000 % in Jun 2009 and a record low of 26.500 % in Dec 2017. India PFS: RBI: Gross Fixed Capital Formation as % of(GDP) Gross Domestic Productat Current Market Price: Current Fiscal Year: Mean data remains active status in CEIC and is reported by Reserve Bank of India. The data is categorized under India Premium Database’s Business and Economic Survey – Table IN.SE006: Professional Forecasters Survey (PFS): Reserve Bank of India: Annual Forecasts: Gross Fixed Capital Formation as % of GDP at Current Market Price.