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.

Inflation Rate in Vietnam increased to 3.24 percent in May from 3.12 percent in April of 2025. This dataset provides the latest reported value for - Vietnam Inflation Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

This data package includes the underlying data files to replicate the data and charts presented in What caused the US pandemic-era inflation? PIIE Working Paper 23-4.

If you use the data, please cite as: Bernanke, Ben, and Olivier Blanchard. 2023. What caused the US pandemic-era inflation? PIIE Working Paper 23-4. Washington, DC: Peterson Institute for International Economics.

This dataset provides values for INFLATION RATE reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

Explore the journey of Pakistan's inflation from 1960 to 2024. This dataset provides a comprehensive overview of the economic landscape, allowing users to delve into the factors influencing inflation rates over the years. Sources include official government reports, economic analyses, and reputable financial institutions.

Cost of food in the United States increased 2.90 percent in May of 2025 over the same month in the previous year. This dataset provides the latest reported value for - United States Food Inflation - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Please, if you use this dataset or do you like my work please UPVOTE 👁️

This dataset provides a comprehensive historical record of inflation rates worldwide, covering the period from 1960 to the present. It includes inflation data at the national level for multiple countries and territories, making it a valuable resource for economic analysis, financial forecasting, and macroeconomic research.

Data Source: https://datos.bancomundial.org/indicador/FP.CPI.TOTL.ZG?end=2023&start=1960&view=chart

Key Features:

✅ Global Coverage – Inflation rates for countries across all continents.

✅ Long-Term Data – Over 60 years of historical records, ideal for trend analysis.

✅ Regional Classification – Data categorized by region, sub-region, and intermediate region for in-depth geographic analysis.

✅ Standardized Indicators – Based on CPI (Consumer Price Index) inflation rates from reputable sources.

Potential Use Cases:

📊 Economic Research – Analyze inflation trends and economic cycles.

📈 Financial Forecasting – Predict future inflation and its impact on global markets.

🌍 Policy & Development Studies – Examine regional disparities and economic policies.

📚 Machine Learning Applications – Train predictive models using historical inflation trends.

This dataset is an essential tool for economists, data scientists, and financial analysts looking to explore global inflation patterns and their implications on economic stability.

This data package includes the underlying data files to replicate the data and charts presented in The Inflation Surge in Europe by Patrick Honohan, PIIE Policy Brief 24-2.

If you use the data, please cite as: Honohan, Patrick. 2024. The Inflation Surge in Europe. PIIE Policy Brief 24-2. Washington, DC: Peterson Institute for International Economics.

Cost of food in Nigeria increased 21.14 percent in May of 2025 over the same month in the previous year. This dataset provides - Nigeria Food Inflation - actual values, historical data, forecast, chart, statistics, economic calendar and news.

presented in An analysis of pandemic-era inflation in 11 economies, PIIE Working Paper 24-11.

If you use the data, please cite as: Bernanke, Ben, and Olivier Blanchard. 2024. An analysis of pandemic-era inflation in 11 economies. PIIE Working Paper 24-11. Washington: Peterson Institute for International Economics.

Inflation Rate in Thailand decreased to -0.57 percent in May from -0.22 percent in April of 2025. This dataset provides the latest reported value for - Thailand Inflation Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

About this dataset

Context

The dataset presents the distribution of median household income among distinct age brackets of householders in Economy. Based on the latest 2018-2022 5-Year Estimates from the American Community Survey, it displays how income varies among householders of different ages in Economy. It showcases how household incomes typically rise as the head of the household gets older. The dataset can be utilized to gain insights into age-based household income trends and explore the variations in incomes across households.

Key observations: Insights from 2022

In terms of income distribution across age cohorts, in Economy, where there exist only two delineated age groups, the median household income is $83,951 for householders within the 25 to 44 years age group, compared to $47,507 for the 65 years and over age group.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.

Age groups classifications include:

• Under 25 years
• 25 to 44 years
• 45 to 64 years
• 65 years and over

Variables / Data Columns

• Age Of The Head Of Household: This column presents the age of the head of household
• Median Household Income: Median household income, in 2022 inflation-adjusted dollars for the specific age group

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 Economy median household income by age. You can refer the same here

This national survey focuses on attitudes toward economic conditions, causes of inflation, and wage-price controls.Questions include personal financial status, equity of various price increases, overall performance and effectiveness of Pay Board and Price Commission, prices of food and other goods, wage increases, wage- price freeze. There are also some current events questions that focus on the upcoming presidential election and include rating of Richard Nixon, Spiro Agnew, and George McGovern.

About this dataset

Context

The dataset presents the mean household income for each of the five quintiles in Economy, PA, as reported by the U.S. Census Bureau. The dataset highlights the variation in mean household income across quintiles, offering valuable insights into income distribution and inequality.

Key observations

• Income disparities: The mean income of the lowest quintile (20% of households with the lowest income) is 27,563, while the mean income for the highest quintile (20% of households with the highest income) is 237,054. This indicates that the top earners earn 9 times compared to the lowest earners.
• *Top 5%: * The mean household income for the wealthiest population (top 5%) is 380,022, which is 160.31% higher compared to the highest quintile, and 1378.74% higher compared to the lowest quintile.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Income Levels:

• Lowest Quintile
• Second Quintile
• Third Quintile
• Fourth Quintile
• Highest Quintile
• Top 5 Percent

Variables / Data Columns

• Income Level: This column showcases the income levels (As mentioned above).
• Mean Household Income: Mean household income, in 2022 inflation-adjusted dollars for the specific income level.

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 Economy median household income. You can refer the same here

Techsalerator's News Events Data for Central African Republic: A Comprehensive Overview

Techsalerator's News Events Data for Central African Republic provides a robust resource for businesses, researchers, and media organizations. This dataset aggregates information on significant news events across the Central African Republic, drawing from diverse media sources, including news outlets, online publications, and social platforms. It offers valuable insights for those aiming to track trends, analyze public sentiment, or monitor industry-specific developments.

Key Data Fields Event Date: Captures the exact date of the news event, crucial for tracking trends over time or for businesses responding to market shifts.

Event Title: A brief headline describing the event, allowing users to quickly categorize and assess news content based on relevance to their interests.

Source: Identifies the news outlet or platform where the event was reported, helping users track credible sources and assess the reach and influence of the event.

Location: Provides geographic information on where the event took place within Central African Republic, valuable for regional analysis or localized marketing efforts.

Event Description: A detailed summary of the event, outlining key developments, participants, and potential impact, helping researchers and businesses understand the context and implications of the event.

Top 5 News Categories in Central African Republic Politics: Major news coverage on government decisions, political movements, elections, and policy changes that affect the national landscape.

Economy: Focuses on Central African Republic’s economic indicators, inflation rates, international trade, and corporate activities influencing business and finance sectors.

Social Issues: News events covering protests, public health, education, and other societal concerns that drive public discourse.

Sports: Highlights events in popular sports, often drawing widespread attention and engagement across the country.

Technology and Innovation: Reports on tech developments, startups, and innovations within the Central African Republic’s emerging tech ecosystem.

Top 5 News Sources in Central African Republic Radio Ndeke Luka: A leading source of news and information, providing extensive coverage of political, economic, and social issues.

Centrafrique Presse: A prominent outlet offering news on national affairs, including politics, economy, and societal concerns.

RFI (Radio France Internationale): An international broadcaster providing updates on major events and developments in Central African Republic.

Le Démocrate: A local publication focusing on national and regional news, including political, economic, and social topics.

TV Centrafrique: A national television network offering coverage of current affairs, including politics, sports, and major events.

Accessing Techsalerator’s News Events Data for Central African Republic To access Techsalerator’s News Events Data for Central African Republic, please contact info@techsalerator.com with your specific needs. We will provide a customized quote based on the data fields and records you require, with delivery available within 24 hours. Ongoing access options can also be discussed.

Included Data Fields Event Date Event Title Source Location Event Description Event Category (Politics, Economy, Sports, etc.) Participants (if applicable) Event Impact (Social, Economic, etc.)

Techsalerator’s dataset is a valuable tool for keeping track of significant events in Central African Republic. It supports informed decision-making for business strategy, market analysis, or academic research, providing a comprehensive view of the country’s news landscape.

This is the latest version of the Global VAR (GVAR) dataset - a global modelling framework for analyzing the international macroeconomic transmission of shocks while accounting for drivers of economic activity, interlinkages and spillovers between different countries, and the effects of unobserved or observed common factors. This dataset includes quarterly macroeconomic variables for 33 economies (log real GDP, y, the rate of inflation, dp, short-term interest rate, r, long-term interest rate, lr, the log deflated exchange rate, ep, and log real equity prices, eq, as well as quarterly data on commodity prices (oil prices, poil, agricultural raw material, pmat, and metals prices, pmetal), from 1979Q2 to 2023Q3. These 33 countries cover more than 90% of world GDP.

It would be appreciated if use of the updated dataset could be acknowledged as: “Mohaddes, K. and M. Raissi (2024). Compilation, Revision and Updating of the Global VAR (GVAR) Database, 1979Q2-2023Q3. University of Cambridge: Judge Business School (mimeo)”.

For more details on Global VAR (GVAR) modelling, see also www.mohaddes.org/gvar

Inflation Rate in Indonesia decreased to 1.60 percent in May from 1.95 percent in April of 2025. This dataset provides - Indonesia Inflation Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Abstract

Food price inflation is an important metric to inform economic policy but traditional sources of consumer prices are often produced with delay during crises and only at an aggregate level. This may poorly reflect the actual price trends in rural or poverty-stricken areas, where large populations reside in fragile situations. This data set includes food price estimates and is intended to help gain insight in price developments beyond what can be formally measured by traditional methods. The estimates are generated using a machine-learning approach that imputes ongoing subnational price surveys, often with accuracy similar to direct measurement of prices. The data set provides new opportunities to investigate local price dynamics in areas where populations are sensitive to localized price shocks and where traditional data are not available.

        A dataset of monthly food price inflation estimates (aggregated for all food products available in the data) is also available for all countries covered by this modeling exercise.

Geographic coverage notes

The data cover the following sub-national areas: Cordillera Administrative region, Region XIII, Region VI, Region V, Region III, Autonomous region in Muslim Mindanao, Region IV-A, Region VIII, Region VII, Region X, Region II, Region IV-B, Region XII, Region XI, Region I, National Capital region, Region IX, Market Average

About this dataset

Context

The dataset presents median income data over a decade or more for males and females categorized by Total, Full-Time Year-Round (FT), and Part-Time (PT) employment in Economy. It showcases annual income, providing insights into gender-specific income distributions and the disparities between full-time and part-time work. The dataset can be utilized to gain insights into gender-based pay disparity trends and explore the variations in income for male and female individuals.

Key observations: Insights from 2023

Based on our analysis ACS 2019-2023 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In Economy, the median income for all workers aged 15 years and older, regardless of work hours, was $40,197 for males and $22,500 for females.

These income figures highlight a substantial gender-based income gap in Economy. Women, regardless of work hours, earn 56 cents for each dollar earned by men. This significant gender pay gap, approximately 44%, underscores concerning gender-based income inequality in the town of Economy.

Surprisingly, within the subset of full-time workers, women earn a higher income than men, earning 1.18 dollars for every dollar earned by men. This suggests that within full-time roles, womens median incomes significantly surpass mens, contrary to broader workforce trends.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.

Gender classifications include:

• Male
• Female

Employment type classifications include:

• Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
• Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

Variables / Data Columns

• Year: This column presents the data year. Expected values are 2010 to 2023
• Male Total Income: Annual median income, for males regardless of work hours
• Male FT Income: Annual median income, for males working full time, year-round
• Male PT Income: Annual median income, for males working part time
• Female Total Income: Annual median income, for females regardless of work hours
• Female FT Income: Annual median income, for females working full time, year-round
• Female PT Income: Annual median income, for females working part time

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 Economy median household income by race. You can refer the same here

This data package includes the underlying data files to replicate the data and charts presented in Did supply chains deliver pandemic-era inflation? by Phil Levy, PIIE Policy Brief 24-10.

If you use the data, please cite as: Levy, Phil. 2024. Did supply chains deliver pandemic-era inflation?, PIIE Policy Brief 24-10. Washington, DC: Peterson Institute for International Economics.