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.

The average for 2021 based on 41 countries was 107.05 index points. The highest value was in Switzerland: 211.98 index points and the lowest value was in Belarus: 40.99 index points. The indicator is available from 2017 to 2021. Below is a chart for all countries where data are available.

According to a recent study, Colombia had the lowest monthly cost of living in Latin America with 546 U.S. dollars needed for basic living. In contrast, four countries had a cost of living above one thousand dollars, Costa Rica, Chile, Panama and Uruguay. In 2022, the highest minimum wage in the region was recorded by Ecuador with 425 dollars per month.

Can Latin Americans survive on a minimum wage? Even if most countries in Latin America have instated laws to guarantee citizens a basic income, these minimum standards are often not enough to meet household needs. For instance, it was estimated that almost 22 million people in Mexico lacked basic housing services. Salary levels also vary greatly among Latin American economies. In 2022, the average net monthly salary in Brazil was lower than Ecuador's minimum wage.

What can a minimum wage afford in Latin America? Latin American real wages have generally risen in the past decade. However, consumers in this region still struggle to afford non-basic goods, such as tech products. Recent estimates reveal that, in order to buy an iPhone, Brazilian residents would have to work more than two months to be able to pay for it. A gaming console, on the other hand, could easily cost a Latin American worker several minimum wages.

Table showing the country rankings based in the different metrics analysed

Luxembourg stands out as the European leader in quality of life for 2025, achieving a score of 220 on the Quality of Life Index. The Netherlands follows closely behind with 211 points, while Albania and Ukraine rank at the bottom with scores of 104 and 115 respectively. This index provides a thorough assessment of living conditions across Europe, reflecting various factors that shape the overall well-being of populations and extending beyond purely economic metrics. Understanding the quality of life index The quality of life index is a multifaceted measure that incorporates factors such as purchasing power, pollution levels, housing affordability, cost of living, safety, healthcare quality, traffic conditions, and climate, to measure the overall quality of life of a Country. Higher overall index scores indicate better living conditions. However, in subindexes such as pollution, cost of living, and traffic commute time, lower values correspond to improved quality of life. Challenges affecting life satisfaction Despite the fact that European countries register high levels of life quality by for example leading the ranking of happiest countries in the world, life satisfaction across the European Union has been on a downward trend since 2018. The EU's overall life satisfaction score dropped from 7.3 out of 10 in 2018 to 7.1 in 2022. This decline can be attributed to various factors, including the COVID-19 pandemic and economic challenges such as high inflation. Rising housing costs, in particular, have emerged as a critical concern, significantly affecting quality of life. This issue has played a central role in shaping voter priorities for the European Parliamentary Elections in 2024 and becoming one of the most pressing challenges for Europeans, profoundly influencing both daily experiences and long-term well-being.

Comprehensive comparison of retirement destinations worldwide with cost of living, housing, healthcare, and lifestyle information.

Quality of Life Index (higher is better) is an estimation of overall quality of life by using an empirical formula which takes into account purchasing power index (higher is better), pollution index (lower is better), house price to income ratio (lower is better), cost of living index (lower is better), safety index (higher is better), health care index (higher is better), traffic commute time index (lower is better) and climate index (higher is better).

Current formula (written in Java programming language):

index.main = Math.max(0, 100 + purchasingPowerInclRentIndex / 2.5 - (housePriceToIncomeRatio * 1.0) - costOfLivingIndex / 10 + safetyIndex / 2.0 + healthIndex / 2.5 - trafficTimeIndex / 2.0 - pollutionIndex * 2.0 / 3.0 + climateIndex / 3.0);

For details how purchasing power (including rent) index, pollution index, property price to income ratios, cost of living index, safety index, climate index, health index and traffic index are calculated please look up their respective pages.

Formulas used in the past

Formula used between June 2017 and Decembar 2017

We decided to decrease weight from costOfLivingIndex in this formula:

index.main = Math.max(0, 100 + purchasingPowerInclRentIndex / 2.5 - (housePriceToIncomeRatio * 1.0) - costOfLivingIndex / 5 + safetyIndex / 2.0 + healthIndex / 2.5 - trafficTimeIndex / 2.0 - pollutionIndex * 2.0 / 3.0 + climateIndex / 3.0);

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.

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 2017 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.

Quality of life index, link: https://www.numbeo.com/quality-of-life/indices_explained.jsp

Happiness store, link: https://www.kaggle.com/unsdsn/world-happiness/home

Title: Top Cities Worldwide: Quality of Life Index 2024 Subtitle: Ranking the World's Best Cities for Living Based on Key Metrics

Source of Data: The dataset was collected from Numbeo.com, a publicly accessible database that provides data on various quality-of-life indicators across cities worldwide. Numbeo aggregates user-contributed data validated through statistical methods to ensure reliability.

Data Collection Method: Data was acquired through web scraping. Care was taken to follow ethical web scraping practices, adhering to Numbeo’s terms of service and respecting their robots.txt file.

Columns Description:

The dataset includes the following columns:

• Rank: City ranking based on the Quality of Life Index.
• City: Name of the city.
• Country: Country where the city is located.
• Quality of Life Index: Overall index measuring quality of life, calculated based on various sub-indices.
• Purchasing Power Index: Measures relative purchasing power in the city.
• Safety Index: Indicates how safe the city is based on crime rates.
• Health Care Index: Reflects the quality and accessibility of healthcare services.
• Cost of Living Index: Represents the cost of living, including housing, food, and transportation.
• Property Price to Income Ratio: A measure of housing affordability, calculated as the ratio of property prices to average incomes.
• Traffic Commute Time Index: Average time spent commuting within the city.

Limitations and Considerations:

• User-Generated Data: Since data on Numbeo is user-contributed, it may be subject to biases.
• Data Update Frequency: As Numbeo updates its data regularly, the dataset represents a snapshot in time and may require periodic updates.

Usage Note: The dataset is intended for research and analytical purposes. Users should verify the data's applicability for their specific use cases, considering the limitations mentioned above.

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.

In 2025, the Consumer Price Index (CPI) for medical professional services in the United States was at 432.46, compared to the period from 1982 to 1984 (=100). The CPI for hospital services was at 1,102.12.

The average for 2021 based on 165 countries was 105.854 index points. The highest value was in South Korea: 208.84 index points and the lowest value was in India: 58.17 index points. The indicator is available from 2017 to 2021. Below is a chart for all countries where data are available.

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

Cost comparison table showing community type costs by location

Global Best Countries to Retire Market is segmented by Application (Retirees_Digital Nomads_Expat Investors_Pensioners_Healthcare-Conscious Seniors), Type (Low-Cost Living Destinations_Healthcare Access Countries_Tax-Friendly Nations_Expat-Friendly Communities_Warm Climate Locations), and Geography (North America_ LATAM_ West Europe_Central & Eastern Europe_ Northern Europe_ Southern Europe_ East Asia_ Southeast Asia_ South Asia_ Central Asia_ Oceania_ MEA)

Quality of life varies significantly worldwide, influenced by factors like cost of living, healthcare, safety, and infrastructure. This case study analyzes Quality of Life Index rankings from 2022 and 2023 to identify trends, regional shifts, and key factors affecting global well-being.

🔍 What’s inside?

The 10 best and 10 worst ranked countries for both 2022 & 2023 Comparative analysis of ranking changes Visualizations: Bar charts, heatmaps, and Tableau maps for better insights Regional breakdowns to see if certain areas consistently rank high or low Key takeaways on what makes a country livable This project is designed to help analysts, travelers, and policymakers understand global quality-of-life trends.

📊 Tools Used: Excel, Google Sheets, Tableau, Python (optional for deeper analysis)

💡 Key Questions Explored:

Which countries improved or declined the most? Are there patterns in the best/worst-ranked regions? How do economic and social factors correlate with rankings?

According to a mid-2024 index, *********** was the most expensive country to live in Europe, with an index score of ****.******** followed in the second place with around ** points less.

Hungary, Czechia, Poland, and Portugal were the countries in Europe where house prices increased the most between 2015 and 2024. The EMF house price index for all four countries measured more than 200 index points, indicating that home prices more than doubled since 2015 — the base year. Property prices are tightly connected with the supply of new homes. France, Poland, and Denmark are some of the countries with the most dwellings completed per 1,000 citizens in Europe.

Annual ranking of countries for digital nomads based on internet speed, cost of living, safety, visa policies, and tax benefits

Domestic Food Prices After COVID-19

Analyzing Impact on Developing Countries' Food Security

By [source]

About this dataset

This dataset looks at the effect of the COVID-19 pandemic on food prices in both domestic and international markets, particularly in developing countries. It contains data on monthly changes in food prices, categorised by country, market, price type (domestic or international) and commodities. In particular, this dataset provides insight into how the pandemic has impacted food security for those living in poorer countries where price increases may be more acutely felt. This dataset gives us a greater understanding of these changing dynamics of global food systems to enable more efficient interventions and support for those who are most vulnerable

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How to use the dataset

This dataset is an excellent resource for anyone looking to analyze the impact of COVID-19 on domestic food prices in developing countries. With this dataset, you can get an up-to-date overview of changes in the costs of various commodities in a given market and by a given price type. Additionally, you can filter data by commodity, country and price type.

In order to use this dataset effectively, here are some steps: - Identify your research question(s) - Filter the dataset by selecting specific columns that best answer your research question (ex: month, country, commodity) - Analyze the data accordingly (for example: Sorting the results then calculating averages). - Interpret results into actionable insights or visualizations

Research Ideas

• Analyzing trends in the cost of food items across different countries to understand regional disparities in food insecurity.
• Comparing pre- and post-COVID international food prices to study how nations altered their trade policies in response to the pandemic, indicating a shift towards or away from trading with other nations for food procurement.
• Using sentiment analysis to study consumer sentiment towards purchasing certain items based on their market prices, allowing businesses and governments alike to better target interventions aimed at improving access and availability of food supplies

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

License: CC0 1.0 Universal (CC0 1.0) - Public Domain Dedication No Copyright - You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission. See Other Information.

Columns

File: dom_clean_data.csv | Column name | Description | |:---------------|:---------------------------------------------------------------------------| | month | The month in which the data was collected. (Date) | | country | The country in which the data was collected. (String) | | price_type | The type of price (domestic or international) that was collected. (String) | | market | The market in which the data was collected. (String) | | commodity | The type of commodity that was collected. (String) |

File: int_clean_data.csv | Column name | Description | |:---------------|:---------------------------------------------------------------------------| | country | The country in which the data was collected. (String) | | commodity | The type of commodity that was collected. (String) | | price_type | The type of price (domestic or international) that was collected. (String) | | time | The month in which the data was collected. (String) |

Acknowledgements

If you use this dataset in your research, please credit the original authors. If you use this dataset in your research, please credit .

Most Promising Supplying Countries 2007-2018: Top Countries To Source Your Product, Top Exporting Countries, Low-cost Exporting Countries