Damascus in Syria was ranked as the least expensive city worldwide in 2023, with an index score of ** out of 100. The country has been marred by civil war over the last decade, hitting the country's economy hard. Other cities in the Middle East and North Africa, such as Tehran, Tripoli, and Tunis, are also present on the list. On the other hand, Singapore and Zurich were ranked the most expensive cities in the world.

West Virginia and Kansas had the lowest cost of living across all U.S. states, with composite costs being half of those found in Hawaii. This was according to a composite index that compares prices for various goods and services on a state-by-state basis. In West Virginia, the cost of living index amounted to **** — well below the national benchmark of 100. Virginia— which had an index value of ***** — was only slightly above that benchmark. Expensive places to live included Hawaii, Massachusetts, and California. Housing costs in the U.S. Housing is usually the highest expense in a household’s budget. In 2023, the average house sold for approximately ******* U.S. dollars, but house prices in the Northeast and West regions were significantly higher. Conversely, the South had some of the least expensive housing. In West Virginia, Mississippi, and Louisiana, the median price of the typical single-family home was less than ******* U.S. dollars. That makes living expenses in these states significantly lower than in states such as Hawaii and California, where housing is much pricier. What other expenses affect the cost of living? Utility costs such as electricity, natural gas, water, and internet also influence the cost of living. In Alaska, Hawaii, and Connecticut, the average monthly utility cost exceeded *** U.S. dollars. That was because of the significantly higher prices for electricity and natural gas in these states.

This dataset provides insights into the cost of living and average monthly income across various countries and regions worldwide from 2000 to 2023. It includes critical economic indicators such as housing costs, taxes, healthcare, education, transportation expenses, and savings rates. The data is ideal for analyzing economic trends, regional comparisons, and financial planning.

Column Descriptions: Country: The name of the country where the data was recorded. Region: The geographical region to which the country belongs (e.g., Asia, Europe). Year: The year when the data was recorded. Average_Monthly_Income: The average monthly income of individuals in USD. Cost_of_Living: The average monthly cost of living in USD, including essentials like housing, food, and utilities. Housing_Cost_Percentage: The percentage of income spent on housing expenses. Tax_Rate: The average tax rate applied to individuals' income, expressed as a percentage. Savings_Percentage: The portion of income saved monthly, expressed as a percentage. Healthcare_Cost_Percentage: The percentage of income spent on healthcare services. Education_Cost_Percentage: The percentage of income allocated to educational expenses. Transportation_Cost_Percentage: The percentage of income spent on transportation costs.

Russia Living Cost: Average per Month: Annual data was reported at 14,375.000 RUB in 2023. This records an increase from the previous number of 12,654.000 RUB for 2022. Russia Living Cost: Average per Month: Annual data is updated yearly, averaging 12,654.000 RUB from Dec 2021 (Median) to 2023, with 3 observations. The data reached an all-time high of 14,375.000 RUB in 2023 and a record low of 11,653.000 RUB in 2021. Russia Living Cost: Average per Month: Annual data remains active status in CEIC and is reported by Federal State Statistics Service. The data is categorized under Russia Premium Database’s Household Survey – Table RU.HF001: Living Cost.

As of 2022, Israel had the highest price level index among listed countries, amounting to 138, with 100 being the average of OECD countries. Switzerland and Iceland followed on the places behind. On the other hand, Turkey and India had the lowest price levels compared to the OECD average. This price index shows differences in price levels in different countries. Another very popular index indicating the value of money is the Big Mac index, showing how much a Big Mac costs in different countries. This list was also topped by Switzerland in 2023.

Living Cost: Average per Month: Children: Annual data was reported at 13,944.000 RUB in 2023. This records an increase from the previous number of 12,274.000 RUB for 2022. Living Cost: Average per Month: Children: Annual data is updated yearly, averaging 12,274.000 RUB from Dec 2021 (Median) to 2023, with 3 observations. The data reached an all-time high of 13,944.000 RUB in 2023 and a record low of 11,303.000 RUB in 2021. Living Cost: Average per Month: Children: Annual data remains active status in CEIC and is reported by Federal State Statistics Service. The data is categorized under Russia Premium Database’s Household Survey – Table RU.HF004: Living Cost: Children.

Living Cost: Average per Month: CR: City of Sevastopol data was reported at 15,762.000 RUB in 2024. This records an increase from the previous number of 14,519.000 RUB for 2023. Living Cost: Average per Month: CR: City of Sevastopol data is updated yearly, averaging 14,219.000 RUB from Dec 2021 (Median) to 2024, with 4 observations. The data reached an all-time high of 15,762.000 RUB in 2024 and a record low of 11,380.000 RUB in 2021. Living Cost: Average per Month: CR: City of Sevastopol data remains active status in CEIC and is reported by Federal State Statistics Service. The data is categorized under Russia Premium Database’s Household Survey – Table RU.HF001: Living Cost.

At **** U.S. dollars, Switzerland has the most expensive Big Macs in the world, according to the January 2025 Big Mac index. Concurrently, the cost of a Big Mac was **** dollars in the U.S., and **** U.S. dollars in the Euro area. What is the Big Mac index? The Big Mac index, published by The Economist, is a novel way of measuring whether the market exchange rates for different countries’ currencies are overvalued or undervalued. It does this by measuring each currency against a common standard – the Big Mac hamburger sold by McDonald’s restaurants all over the world. Twice a year the Economist converts the average national price of a Big Mac into U.S. dollars using the exchange rate at that point in time. As a Big Mac is a completely standardized product across the world, the argument goes that it should have the same relative cost in every country. Differences in the cost of a Big Mac expressed as U.S. dollars therefore reflect differences in the purchasing power of each currency. Is the Big Mac index a good measure of purchasing power parity? Purchasing power parity (PPP) is the idea that items should cost the same in different countries, based on the exchange rate at that time. This relationship does not hold in practice. Factors like tax rates, wage regulations, whether components need to be imported, and the level of market competition all contribute to price variations between countries. The Big Mac index does measure this basic point – that one U.S. dollar can buy more in some countries than others. There are more accurate ways to measure differences in PPP though, which convert a larger range of products into their dollar price. Adjusting for PPP can have a massive effect on how we understand a country’s economy. The country with the largest GDP adjusted for PPP is China, but when looking at the unadjusted GDP of different countries, the U.S. has the largest economy.

The dataset obtained consists of details of countries from year 2012-2023. The dataset consists of crime index, safety index, quality of life index, purchasing power index, cost of living index and unemployment rate in each country. Unemployment rate is based on age group 15+, 15-25+ and 25+ attributes.

The dataset is obtained by web scraping and the authenticity of data is not confirmed by the source.

Code used for web scraping: https://www.kaggle.com/code/mrudular/web-scraping-world-indices.

Data sources: 1. https://www.numbeo.com/cost-of-living/ 2. International Labour Organization. ILO modelled estimates database, ILOSTAT. https://ilostat.ilo.org/data/. Accessed 07-09-2023.

As of September 2025, Mumbai had the highest cost of living among other cities in the country, with an index value of ****. Gurgaon, a satellite city of Delhi and part of the National Capital Region (NCR) followed it with an index value of ****.  What is cost of living? The cost of living varies depending on geographical regions and factors that affect the cost of living in an area include housing, food, utilities, clothing, childcare, and fuel among others. The cost of living is calculated based on different measures such as the consumer price index (CPI), living cost indexes, and wage price index. CPI refers to the change in the value of consumer goods and services. The wage price index, on the other hand, measures the change in labor services prices due to market pressures. Lastly, the living cost indexes calculate the impact of changing costs on different households. The relationship between wages and costs determines affordability and shifts in the cost of living. Mumbai tops the list Mumbai usually tops the list of most expensive cities in India. As the financial and entertainment hub of the country, Mumbai offers wide opportunities and attracts talent from all over the country. It is the second-largest city in India and has one of the most expensive real estates in the world.

Living Cost: Pensioners: Average per Month: CR: City of Sevastopol data was reported at 13,555.000 RUB in 2024. This records an increase from the previous number of 12,486.000 RUB for 2023. Living Cost: Pensioners: Average per Month: CR: City of Sevastopol data is updated yearly, averaging 12,228.000 RUB from Dec 2021 (Median) to 2024, with 4 observations. The data reached an all-time high of 13,555.000 RUB in 2024 and a record low of 9,862.000 RUB in 2021. Living Cost: Pensioners: Average per Month: CR: City of Sevastopol data remains active status in CEIC and is reported by Federal State Statistics Service. The data is categorized under Russia Premium Database’s Household Survey – Table RU.HF003: Living Cost: Pensioner.

Population with Income per Capita below Living Cost: % of Total: NW: Novgorod Region data was reported at 8.700 % in 2024. This records a decrease from the previous number of 10.800 % for 2023. Population with Income per Capita below Living Cost: % of Total: NW: Novgorod Region data is updated yearly, averaging 15.750 % from Dec 1995 (Median) to 2024, with 30 observations. The data reached an all-time high of 34.200 % in 2000 and a record low of 8.700 % in 2024. Population with Income per Capita below Living Cost: % of Total: NW: Novgorod Region data remains active status in CEIC and is reported by Federal State Statistics Service. The data is categorized under Russia Premium Database’s Demographic and Labour Market – Table RU.GA015: Population with Income per Capita below Living Cost.

Description

This comprehensive dataset provides a wealth of information about all countries worldwide, covering a wide range of indicators and attributes. It encompasses demographic statistics, economic indicators, environmental factors, healthcare metrics, education statistics, and much more. With every country represented, this dataset offers a complete global perspective on various aspects of nations, enabling in-depth analyses and cross-country comparisons.

Key Features

• Country: Name of the country.
• Density (P/Km2): Population density measured in persons per square kilometer.
• Abbreviation: Abbreviation or code representing the country.
• Agricultural Land (%): Percentage of land area used for agricultural purposes.
• Land Area (Km2): Total land area of the country in square kilometers.
• Armed Forces Size: Size of the armed forces in the country.
• Birth Rate: Number of births per 1,000 population per year.
• Calling Code: International calling code for the country.
• Capital/Major City: Name of the capital or major city.
• CO2 Emissions: Carbon dioxide emissions in tons.
• CPI: Consumer Price Index, a measure of inflation and purchasing power.
• CPI Change (%): Percentage change in the Consumer Price Index compared to the previous year.
• Currency_Code: Currency code used in the country.
• Fertility Rate: Average number of children born to a woman during her lifetime.
• Forested Area (%): Percentage of land area covered by forests.
• Gasoline_Price: Price of gasoline per liter in local currency.
• GDP: Gross Domestic Product, the total value of goods and services produced in the country.
• Gross Primary Education Enrollment (%): Gross enrollment ratio for primary education.
• Gross Tertiary Education Enrollment (%): Gross enrollment ratio for tertiary education.
• Infant Mortality: Number of deaths per 1,000 live births before reaching one year of age.
• Largest City: Name of the country's largest city.
• Life Expectancy: Average number of years a newborn is expected to live.
• Maternal Mortality Ratio: Number of maternal deaths per 100,000 live births.
• Minimum Wage: Minimum wage level in local currency.
• Official Language: Official language(s) spoken in the country.
• Out of Pocket Health Expenditure (%): Percentage of total health expenditure paid out-of-pocket by individuals.
• Physicians per Thousand: Number of physicians per thousand people.
• Population: Total population of the country.
• Population: Labor Force Participation (%): Percentage of the population that is part of the labor force.
• Tax Revenue (%): Tax revenue as a percentage of GDP.
• Total Tax Rate: Overall tax burden as a percentage of commercial profits.
• Unemployment Rate: Percentage of the labor force that is unemployed.
• Urban Population: Percentage of the population living in urban areas.
• Latitude: Latitude coordinate of the country's location.
• Longitude: Longitude coordinate of the country's location.

Potential Use Cases

• Analyze population density and land area to study spatial distribution patterns.
• Investigate the relationship between agricultural land and food security.
• Examine carbon dioxide emissions and their impact on climate change.
• Explore correlations between economic indicators such as GDP and various socio-economic factors.
• Investigate educational enrollment rates and their implications for human capital development.
• Analyze healthcare metrics such as infant mortality and life expectancy to assess overall well-being.
• Study labor market dynamics through indicators such as labor force participation and unemployment rates.
• Investigate the role of taxation and its impact on economic development.
• Explore urbanization trends and their social and environmental consequences.

Data Source: This dataset was compiled from multiple data sources

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Portugal, Canada, and the United States were the countries with the highest house price to income ratio in 2024. In all three countries, the index exceeded 130 index points, while the average for all OECD countries stood at 116.2 index points. The index measures the development of housing affordability and is calculated by dividing nominal house price by nominal disposable income per head, with 2015 set as a base year when the index amounted to 100. An index value of 120, for example, would mean that house price growth has outpaced income growth by 20 percent since 2015. How have house prices worldwide changed since the COVID-19 pandemic? House prices started to rise gradually after the global financial crisis (2007–2008), but this trend accelerated with the pandemic. The countries with advanced economies, which usually have mature housing markets, experienced stronger growth than countries with emerging economies. Real house price growth (accounting for inflation) peaked in 2022 and has since lost some of the gain. Although, many countries experienced a decline in house prices, the global house price index shows that property prices in 2023 were still substantially higher than before COVID-19. Renting vs. buying In the past, house prices have grown faster than rents. However, the home affordability has been declining notably, with a direct impact on rental prices. As people struggle to buy a property of their own, they often turn to rental accommodation. This has resulted in a growing demand for rental apartments and soaring rental prices.

European Study Costs 2023: Unveiling Affordability Insights

Introduction:

Welcome to the "European Study Costs 2023" dataset, a treasure trove of information for anyone intrigued by the dynamics of international education expenses across Europe. In this dataset, we delve into the nuanced details of the total yearly living costs, average tuition fees, and yearly student living costs in various European countries.

Key Highlights:

International Student Perspectives: Gain valuable insights into the costs associated with pursuing education as an international student in Europe.

*Regional Contrasts: Explore the distinct variations in study expenses between Eastern and Western European countries, uncovering intriguing trends that could shape future academic landscapes.

Affordability Factors: Understand the factors contributing to the affordability of education, from governmental support to cultural influences and economic conditions.

Outliers and Anomalies: Identify outliers like Luxembourg, offering a unique perspective and prompting further analysis into what sets certain countries apart.

Correlations and Trends: Investigate potential correlations between tuition fees and living costs, unraveling patterns that could influence student decision-making.*

Opportunities for Analysis:

Delve into comparative analyses, ranking countries based on overall affordability. Explore opportunities for feature engineering to enhance predictive models. Consider machine learning tasks such as predicting living costs or clustering countries based on affordability profiles.

Impactful Insights for Students and Analysts:

This dataset goes beyond numbers; it provides a roadmap for prospective international students to make informed decisions about where to pursue their education. Join the exploration, contribute your analyses, and uncover the intricacies of educational affordability in Europe for 2023.

Population with Income per Capita below Living Cost: % of Total: CF: Moscow Region data was reported at 4.900 % in 2024. This records a decrease from the previous number of 5.500 % for 2023. Population with Income per Capita below Living Cost: % of Total: CF: Moscow Region data is updated yearly, averaging 9.850 % from Dec 1995 (Median) to 2024, with 30 observations. The data reached an all-time high of 35.200 % in 2000 and a record low of 4.900 % in 2024. Population with Income per Capita below Living Cost: % of Total: CF: Moscow Region data remains active status in CEIC and is reported by Federal State Statistics Service. The data is categorized under Russia Premium Database’s Demographic and Labour Market – Table RU.GA015: Population with Income per Capita below Living Cost.

Population with Income per Capita below Living Cost: % of Total: VR: Republic of Marii El data was reported at 12.600 % in 2024. This records a decrease from the previous number of 15.100 % for 2023. Population with Income per Capita below Living Cost: % of Total: VR: Republic of Marii El data is updated yearly, averaging 24.150 % from Dec 1995 (Median) to 2024, with 30 observations. The data reached an all-time high of 60.200 % in 2000 and a record low of 12.600 % in 2024. Population with Income per Capita below Living Cost: % of Total: VR: Republic of Marii El data remains active status in CEIC and is reported by Federal State Statistics Service. The data is categorized under Russia Premium Database’s Demographic and Labour Market – Table RU.GA015: Population with Income per Capita below Living Cost.

According to a consumer demand survey conducted by Capgemini Research Institute in late 2023, just under ** percent of shoppers around the world said they would become more loyal towards companies that helped them during the challenging cost-of-living crisis. About ** percent of respondents said they would purchase more products from them in the future as a result. For more Capgemini insights, click here.

Population with Income per Capita below Living Cost: % of Total: CF: Kursk Region data was reported at 6.300 % in 2024. This records a decrease from the previous number of 7.600 % for 2023. Population with Income per Capita below Living Cost: % of Total: CF: Kursk Region data is updated yearly, averaging 10.950 % from Dec 1995 (Median) to 2024, with 30 observations. The data reached an all-time high of 42.200 % in 2000 and a record low of 6.300 % in 2024. Population with Income per Capita below Living Cost: % of Total: CF: Kursk Region data remains active status in CEIC and is reported by Federal State Statistics Service. The data is categorized under Russia Premium Database’s Demographic and Labour Market – Table RU.GA015: Population with Income per Capita below Living Cost.

According to the 2023 Global Consumer Insights Survey China report, only *** percent of respondents in mainland China and Hong Kong were found to be extremely concerned about the rising cost of living in relation to their personal financial situation. Those who were somewhat concerned accounted for ** percent of the total respondents. Seven percent of respondents were not at all concerned about the rising cost.