Of the most populous cities in the U.S., San Jose, California had the highest annual income requirement at ******* U.S. dollars annually for homeowners to have an affordable and comfortable life in 2024. This can be compared to Houston, Texas, where homeowners needed an annual income of ****** U.S. dollars in 2024.

In 2024, the CPI in U.S. cities averaged at 313.7. However, the CPI for the New York-Newark-Jersey City metropolitan area amounted to about 334.21. Prices in New York City were significantly higher than the U.S. average. Nonetheless, the San Diego-Carlsbad area ranked first with a CPI of 373.32.The monthly inflation rate for the United States can be found here.

The US Family Budget Dataset provides insights into the cost of living in different US counties based on the Family Budget Calculator by the Economic Policy Institute (EPI).

This dataset offers community-specific estimates for ten family types, including one or two adults with zero to four children, in all 1877 counties and metro areas across the United States.

Interesting Task Ideas:

1. See how family budgets compare to the federal poverty line and the Supplemental Poverty Measure in different counties.
2. Look into the money challenges faced by different types of families using the budgets provided.
3. Find out which counties have the most affordable places to live, food, transportation, healthcare, childcare, and other things people need.
4. Explore how the average income of families relates to the overall cost of living in different counties.
5. Investigate how family size affects the estimated budget and find counties where bigger families have higher costs.
6. Create visuals showing how the cost of living varies across different states and big cities.
7. Check whether specific counties are affordable for families of different sizes and types.
8. Use the dataset to compare living standards and economic security in different US counties.

If you find this dataset valuable, don't forget to hit the upvote button! 😊💝

Checkout my other datasets

Employment-to-Population Ratio for USA

Productivity and Hourly Compensation

130K Kindle Books

900K TMDb Movies

USA Unemployment Rates by Demographics & Race

Photo by Alev Takil on Unsplash

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.

A dataset comprising various variables around housing and demographics for the top 50 American cities by population.

Variables:

Zip Code: Zip code within which the listing is present.

Price: Listed price for the property.

Beds: Number of beds mentioned in the listing.

Baths: Number of baths mentioned in the listing.

Living Space: The total size of the living space, in square feet, mentioned in the listing.

Address: Street address of the listing.

City: City name where the listing is located.

State: State name where the listing is located.

Zip Code Population: The estimated number of individuals within the zip code. Data from Simplemaps.com.

Zip Code Density: The estimated number of individuals per square mile within the zip code. Data from Simplemaps.com.

County: County where the listing is located.

Median Household income: Estimated median household income. Data from the U.S. Census Bureau.

Latitude: Latitude of the zip code. ** Data from Simplemaps.com.**

Longitude: Longitude of the zip code. Data from Simplemaps.com.

The Consumer Sentiment Index in the United States stood at 51 in November 2025. This reflected a drop of 2.6 point from the previous survey. Furthermore, this was its lowest level measured since June 2022. The index is normalized to a value of 100 in December 1964 and based on a monthly survey of consumers, conducted in the continental United States. It consists of about 50 core questions which cover consumers' assessments of their personal financial situation, their buying attitudes and overall economic conditions.

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.

This table contains data on the percent of households paying more than 30% (or 50%) of monthly household income towards housing costs for California, its regions, counties, cities/towns, and census tracts. Data is from the U.S. Department of Housing and Urban Development (HUD), Consolidated Planning Comprehensive Housing Affordability Strategy (CHAS) and the U.S. Census Bureau, American Community Survey (ACS). The table is part of a series of indicators in the [Healthy Communities Data and Indicators Project of the Office of Health Equity] Affordable, quality housing is central to health, conferring protection from the environment and supporting family life. Housing costs—typically the largest, single expense in a family's budget—also impact decisions that affect health. As housing consumes larger proportions of household income, families have less income for nutrition, health care, transportation, education, etc. Severe cost burdens may induce poverty—which is associated with developmental and behavioral problems in children and accelerated cognitive and physical decline in adults. Low-income families and minority communities are disproportionately affected by the lack of affordable, quality housing. More information about the data table and a data dictionary can be found in the Attachments.

U.S. Software Developer Salaries

Analyzing Regional Variations

By [source]

About this dataset

This dataset provides an extensive look into the financial health of software developers in major cities and metropolitan areas around the United States. We explore disparities between states and cities in terms of mean software developer salaries, median home prices, cost of living avgs, rent avgs, cost of living plus rent avgs and local purchasing power averages. Through this data set we can gain insights on how to better understand which areas are more financially viable than others when seeking employment within the software development field. Our data allow us to uncover patterns among certain geographic locations in order to identify other compelling financial opportunities that software developers may benefit from

More Datasets

For more datasets, click here.

Featured Notebooks

• 🚨 Your notebook can be here! 🚨!

How to use the dataset

This dataset contains valuable information about software developer salaries across states and cities in the United States. It is important for recruiters and professionals alike to understand what kind of compensation software developers are likely to receive, as it may be beneficial when considering job opportunities or applying for a promotion. This guide will provide an overview of what you can learn from this dataset.

The data is organized by metropolitan areas, which encompass multiple cities within the same geographical region (e.g., “New York-Northern New Jersey” covers both New York City and Newark). From there, each metro can be broken down further into a number of different factors that may affect software developer salaries in the area:

• Mean Software Developer Salary (adjusted): The average salary of software developers in that particular metro area after accounting for cost of living differences within the region.
• Mean Software Developer Salary (unadjusted): The average salary of software developers in that particular metro area before adjusting for cost-of-living discrepancies between locales.
• Number of Software Developer Jobs: This column lists how many total jobs are available to software developers in this particular metropolitan area.
• Median Home Price: A metric which shows median value of all homes currently on the market within this partcular city or state. It helps gauge how expensive housing costs might be to potential residents who already have an idea about their income/salary range expectations when considering a move/relocation into another location or potentially looking at mortgage/rental options etc.. 5) Cost Of Living Avg: A metric designed to measure affordability using local prices paid on common consumer goods like food , transportation , health care , housing & other services etc.. Also prominent here along with rent avg ,cost od living plus rent avg helping compare relative cost structures between different locations while assessing potential remunerations & risk associated with them . 6)Local Purchasing Power Avg : A measure reflecting expected difference in discretionary spending ability among households regardless their income level upon relocation due to price discrepancies across locations allows individual assessment critical during job search particularly regarding relocation as well as comparison based decision making across prospective candidates during any hiring process . 7 ) Rent Avg : Average rental costs for homes / apartments dealbreakers even among prime job prospects particularly medium income earners.(basis family size & other constraints ) 8 ) Cost Of Living Plus Rent Avg : Used here as one sized fits perspective towards measuring overall cost structure including items

Research Ideas

• Comparing salaries of software developers in different cities to determine which city provides the best compensation package.
• Estimating the cost of relocating to a new city by looking at average costs such as rent and cost of living.
• Predicting job growth for software developers by analyzing factors like local purchasing power, median home price and number of jobs available

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 perm...

D.C.'s median rent for a one bedroom apartment stands at $2,495, significantly higher than the national median rent of approximately $1,567. Click on different U.S. cities to see the median rent for a one bedroom apartment2.The map on the left side shows the percentage of people by census tract that are considered "cost burdened" by housing costs, by paying 30% or more of their household income on rent and utilities3. The map on the right side shows the median household income by census tract4. You can click on the "list" icon in the lower left corner to see the map legend, and meanings of map symbology. Areas that are cost burdened are often areas with the lowest median household incomes. There are also areas in wards where median incomes are high, but the cost of living is also high, leading to a greater cost burden.

This Cost of International Education dataset compiles detailed financial information for students pursuing higher education abroad. It covers multiple countries, cities, and universities around the world, capturing the full tuition and living expenses spectrum alongside key ancillary costs. With standardized fields such as tuition in USD, living-cost indices, rent, visa fees, insurance, and up-to-date exchange rates, it enables comparative analysis across programs, degree levels, and geographies. Whether you’re a prospective international student mapping out budgets, an educational consultant advising on affordability, or a researcher studying global education economics, this dataset offers a comprehensive foundation for data-driven insights.

Description

Potential Uses

• Budget Planning Prospective students can filter by country, program level, or university to forecast total expenses and compare across destinations.
• Policy Analysis Educational policymakers and NGOs can assess the affordability of international education and design support programs.
• Economic Research Economists can correlate living-cost indices and tuition levels with enrollment rates or student demographics.
• University Benchmarking Institutions can benchmark their fees and ancillary costs against peer universities worldwide.

Notes on Data Collection & Quality

• Currency Conversions All monetary values are unified to USD using contemporaneous exchange rates to facilitate direct comparison.
• Living Cost Index Derived from reputable city-index publications (e.g., Numbeo, Mercer) to standardize disparate cost-of-living metrics.
• Data Currency Exchange rates and fee schedules should be periodically updated to reflect market fluctuations and policy changes.

Feel free to explore, visualize, and extend this dataset for deeper insights into the true cost of studying abroad!

As of mid-2025, Port of Spain ranked as the second Latin American and Caribbean city with the highest cost of living. The capital of ******************* obtained an index score of ****, followed by the ********* capital, with **** points.

Co-Living Space Market Outlook

According to our latest research, the Global Co-Living Space market size was valued at $21.4 billion in 2024 and is projected to reach $72.6 billion by 2033, expanding at a robust CAGR of 14.2% during the forecast period of 2024–2033. The primary driver fueling this substantial growth is the rising demand for affordable and flexible housing solutions among urban millennials and young professionals worldwide. As urbanization accelerates and the cost of living in major cities continues to soar, co-living spaces offer a compelling alternative by combining affordability, convenience, and a sense of community. This evolving lifestyle preference, coupled with technological advancements in property management and digital platforms, is reshaping the residential real estate landscape and positioning co-living as a mainstream solution for the future of urban living.

Regional Outlook

North America currently commands the largest share of the global co-living space market, accounting for nearly 35% of total market revenue in 2024. This dominance is attributed to the region’s mature real estate infrastructure, high urbanization rates, and a robust ecosystem of tech-enabled property management companies. Cities such as New York, San Francisco, and Toronto have witnessed a surge in co-living developments, driven by a growing population of young professionals and students seeking cost-effective and socially engaging living arrangements. Furthermore, favorable regulatory frameworks and the proliferation of venture-backed startups have accelerated the adoption of co-living models, making North America a benchmark for operational excellence and innovation in the sector.

The Asia Pacific region is emerging as the fastest-growing market, projected to register a remarkable CAGR of 17.8% from 2024 to 2033. This growth trajectory is propelled by rapid urban migration, a burgeoning middle class, and escalating property prices in metropolitan hubs like Beijing, Mumbai, Singapore, and Sydney. Governments in the region are increasingly supportive of alternative housing formats to address urban housing shortages, while real estate developers and institutional investors are ramping up investments in co-living projects. The region’s youthful demographic profile and cultural openness to shared living further catalyze market expansion, positioning Asia Pacific as a critical engine for future growth in the global co-living space market.

In emerging economies across Latin America, the Middle East, and Africa, the adoption of co-living spaces is gaining momentum but faces unique challenges. Limited awareness, regulatory ambiguities, and varying cultural perceptions of shared living can hinder rapid adoption. However, as urbanization intensifies and the demand for affordable housing rises, these markets present significant untapped potential. Localized demand is being addressed through partnerships with universities, corporations, and local governments, while regulatory reforms and pilot projects are gradually paving the way for broader acceptance. Despite infrastructural and policy hurdles, the long-term outlook for co-living in these regions remains optimistic, especially as global operators and investors begin to explore these nascent markets.

Report Scope

When the COVID-19 pandemic forced tens of millions of people to work remotely, some chose to relocate out of high-cost, large metro areas. Did people move to cheaper metros or give up in city living altogether? How many will follow in their footsteps, and what could their relocating mean for the places they choose?

Context:

The Bureau of Labor Statistics defines the Consumer Price Index (CPI) as “a statistical measure of change, over time, of the prices of goods and services in major expenditure groups--such as food, housing, apparel, transportation, and medical care--typically purchased by urban consumers. Essentially, it compares the cost of a sample of goods and services in a specific month relative to the cost of the same "market basket" in an earlier reference period.

Make sure to read the cu.txt for more descriptive summaries on each data file and how to use the unique identifiers.

Content:

This dataset was collected June 27th, 2017 and may not be up-to-date.

The revised CPI introduced by the BLS in 1998 includes indexes for two populations; urban wage earners and clerical workers (CW), and all urban consumers (CU). This dataset covers all urban consumers (CU).

The Consumer Price Index (CPI) is a statistical measure of change, over time, of the prices of goods and services in major expenditure groups--such as food, housing, apparel, transportation, and medical care--typically purchased by urban consumers. Essentially, it compares the cost of a sample "market basket" of goods and services in a specific month relative to the cost of the same "market basket" in an earlier reference period. This reference period is designated as the base period.

As a result of the 1998 revision, both the CW and the CU utilize updated expenditure weights based upon data tabulated from three years (1982, 1983, and 1984) of the Consumer Expenditure Survey and incorporate a number of technical improvements, including an updated and revised item structure.

To construct the two indexes, prices for about 100,000 items and data on about 8,300 housing units are collected in a sample of 91 urban places. Comparison of indexes for individual CMSA's or cities show only the relative change over time in prices between locations. These indexes cannot be used to measure interarea differences in price levels or living costs.

Summary Data Available: U.S. average indexes for both populations are available for about 305 consumer items and groups of items. In addition, over 100 of the indexes have been adjusted for seasonality. The indexes are monthly with some beginning in 1913. Semi-annual indexes have been calculated for about 100 items for comparison with semi-annual areas mentioned below. Semi-annual indexes are available from 1984 forward.

Area indexes for both populations are available for 26 urban places. For each area, indexes are published for about 42 items and groups. The indexes are published monthly for three areas, bimonthly for eleven areas, and semi-annually for 12 urban areas.

Regional indexes for both populations are available for four regions with about 55 items and groups per region. Beginning with January 1987, indexes are monthly, with some beginning as early as 1966. Semi-annual indexes have been calculated for about 42 items for comparison with semi-annual areas mentioned above. Semi-annual indexes have been calculated for about 42 items in the 27 urban places for comparison with semi-annual areas.

City-size indexes for both populations are available for three size classes with about 55 items and groups per class. Beginning with January 1987, indexes are monthly and most begin in 1977. Semi-annual indexes have been calculated for about 42 items for comparison with semi-annual areas mentioned below.

Region/city-size indexes for both populations are available cross classified by region and city-size class. For each of 13 cross calculations, about 42 items and groups are available. Beginning with January 1987, indexes are monthly and most begin in 1977. Semi-annual indexes have been calculated for about 42 items in the 26 urban places for comparison with semi-annual areas.

Frequency of Observations: U.S. city average indexes, some area indexes, and regional indexes, city-size indexes, and region/city-size indexes for both populations are monthly. Other area indexes for both populations are bimonthly or semi-annual.

Annual Averages: Annual averages are available for all unadjusted series in the CW and CU.

Base Periods: Most indexes have a base period of 1982-1984 = 100. Other indexes, mainly those which have been added to the CPI program with the 1998 revision, are based more recently. The base period value is 100.0, except for the "Purchasing Power" values (AAOR and SAOR) where the base period value is 1.000.

Data Characteristics: Indexes are stored to one decimal place, except for the "Purchasing Power" values which are stored to three decimal places.

References: BLS Handbook of Methods, Chapter 17, "Consumer Price Index", BLS Bulletin 2285, April 1988.

Acknowledgements:

This dataset was taken directly from the U.S. Bureau of Labor Statistics web...

The Consumer Price Index (CPI) is a statistical measure of change, over time, of the prices of goods and services in major expenditure groups--such as food, housing, apparel, transportation, and medical care--typically purchased by urban consumers. Essentially, it compares the cost of a sample "market basket" of goods and services in a specific month relative to the cost of the same "market basket" in an earlier reference period. This reference period is designated as the base period.

The CPI publishes indexes for two populations; all urban consumers (CU) and urban wage earners and clerical workers (CW).

To construct the two indexes, thousands of prices for commodities and services purchased by consumers are collected in a sample of 75 urban places. Rent data is collected in a separate sample of thousands of rental units. Comparison of indexes for individual CMSA's or cities show only the relative change over time in prices between locations. These indexes cannot be used to measure interarea differences in price levels or living costs.

Summary Data Available: U.S. average indexes for both populations are available for several hundred consumer items and groups of items. In addition, many of the indexes have been adjusted for seasonality. The indexes are monthly. Different indexes go back to different years, with the earliest, including all items, dating to 1913. Semi-annual indexes have been calculated for many items for comparison with semi-annual areas mentioned below. Semi-annual indexes are available from 1984 forward.

Area indexes for both populations are available for 23 urban places. For each area, indexes are published for a subset of items and groups. The indexes are published monthly for three areas and bimonthly for twenty areas. Regional and division level indexes for both populations are available for a subset of items and groups published. Indexes are published for four regions and nine divisions. Regional indexes date to 1966; divisional indexes are newer, dating to 2018. Indexes are monthly, with Semi-annual indexes also calculated for selected items.

City-size class indexes for both populations are available for two size classes with a similar subset of groups and items. Region/city-size indexes (for example, Midwest size class B/C)for both populations are also available monthly.

Frequency of Observations: U.S. city average indexes, regional indexes, division indexes, size class indexes, and three metro area indexes are monthly. 20 metro area indexes are bimonthly.

Annual Averages: Annual averages are available for all unadjusted series in the CW and CU.

Base Periods: Most indexes have a base period of 1982-1984 = 100. Other indexes, mainly newer indexes, are based more recently. The base period value is generally 100.0, with rare exceptions where the base is set to 1000 to avoid loss of precision. The index for the "Purchasing Power" values (AAOR and SAOR) have a base period value of 1.000.

Data Characteristics: Indexes are published to three decimal places.

Updating Schedule: Updates become available with the release of new data, typically between the 10th and 14th of the month following the reference month.

The Consumer Price Index (CPI) measures over time the prices of goods and services in major expenditure categories typically purchased by urban consumers. The expenditure categories include food, housing, apparel, transportation, and medical care. Essentially, the Index measures consumer purchasing power by comparing the cost of a fixed set of goods and services (called a market basket) in a specific month relative to the cost of the same market basket in an earlier reference period, designated as the base period. The CPI is calculated for two population groups: urban wage earners and clerical workers (CPI-W) and all urban consumers (CPI-U). The CPI-W population includes those urban families with clerical workers, sales workers, craft workers, operatives, service workers, or laborers in the family unit and is representative of the prices paid by about 40 percent of the United States population. The CPI-U population consists of all urban households (including professional and salaried workers, part-time workers, the self-employed, the unemployed, and retired persons) and is representative of the prices paid by about 80 percent of the United States population. Both populations specifically exclude persons in the military, in institutions, and all persons living outside of urban areas (such as farm families). National indexes for both populations are available for about 350 consumer items and groups of items. In addition, over 100 of the indexes have been adjusted for seasonality. The indexes are monthly with some beginning in 1913. Area indexes are available for 27 urban places. For each area, indexes are presented for about 65 items and groups. The area indexes are produced monthly for 5 areas, bimonthly for 10 areas, and semiannually for 12 urban areas. Regional indexes are available for four regions with about 95 items and groups per region. Beginning with January 1987, regional indexes are monthly, with some beginning as early as 1966. City-size indexes are available for four size classes with about 95 items and groups per class. Beginning with January 1987, these indexes are monthly and most begin in 1977. Regional and city-size indexes are available cross-classified by region and city-size class. For each of the 13 cross-classifications, about 60 items and groups are available. Beginning with January 1987, these indexes are monthly and most begin in 1977. Each index record includes a series identification code that specifies the sample (either all urban consumers or urban wage earners and clerical workers), seasonality (either seasonally adjusted or unadjusted), periodicity (either semiannual or regular), geographic area, index base period, and item number of the index.

Snapshot img

US Residential Construction Market Size 2025-2029

The us residential construction market size is valued to increase USD 242.9 million, at a CAGR of 4.5% from 2024 to 2029. Increasing household formation rates will drive the us residential construction market.

Major Market Trends & Insights

By Product - Apartments and condominiums segment was valued at USD 509.50 million in 2022
By Type - New construction segment accounted for the largest market revenue share in 2022

Market Size & Forecast

Market Opportunities: USD 39.65 million
Market Future Opportunities: USD 242.90 million
CAGR from 2024 to 2029 : 4.5%

Market Summary

The Residential Construction Market in the US is a dynamic and evolving industry, shaped by various factors and trends. Core technologies and applications, such as Building Information Modeling (BIM) and energy-efficient systems, are increasingly adopted to enhance project efficiency and sustainability. In fact, the use of BIM in residential construction is projected to reach 50% penetration by 2025, according to industry reports. Service types and product categories, including general contracting, design-build, and modular housing, cater to diverse residential construction needs. However, challenges persist, including rising material costs and skilled labor shortages for large-scale residential real estate projects. Regulations, such as the International Energy Conservation Code, drive the focus on sustainability in residential construction projects. The regional landscape is diverse, with the South and West regions leading in residential construction activity due to population growth and favorable economic conditions. These evolving market dynamics offer significant opportunities for industry players to innovate and adapt to the changing landscape.

What will be the Size of the US Residential Construction Market during the forecast period?

Get Key Insights on Market Forecast (PDF) Request Free Sample

How is the Residential Construction in US Market Segmented and what are the key trends of market segmentation?

The residential construction in us industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments. ProductApartments and condominiumsLuxury HomesOther typesTypeNew constructionRenovationApplicationSingle familyMulti-familyConstruction MaterialWood-framed ConcreteSteel Modular/PrefabricatedGeographyNorth AmericaUS

By Product Insights

The apartments and condominiums segment is estimated to witness significant growth during the forecast period.

The residential construction market in the US continues to evolve, with apartments and condominiums being key contributors to its growth. Urbanization is a significant driver, as more Americans opt for the convenience and amenities of city living. In response, developers are constructing modern, sustainable, and community-focused high-rise buildings and condominium complexes. Smart home technology and energy efficiency standards are becoming increasingly important in these projects, with Building Information Modeling (BIM) software guiding the design process. Modular construction, geotechnical engineering, and quality control measures ensure structural integrity and safety. Building codes and permitting processes are strictly adhered to, with green building certifications such as LEED and Energy Star driving the adoption of sustainable building practices. Masonry techniques, foundation design, and exterior cladding are essential elements of the construction process, with insulation materials and HVAC systems ensuring energy efficiency. Safety regulations govern electrical wiring, roofing systems, and plumbing fixtures. Construction scheduling is facilitated by project management software, with prefabricated components and 3D building modeling streamlining the process. Construction automation and waste management are also crucial considerations, with cost estimation models helping developers stay within budget. Environmental impact assessments and structural engineering studies are essential to minimize the environmental footprint and ensure safety. Framing techniques and foundation design are optimized for durability and cost-effectiveness. Safety regulations and quality control measures are strictly enforced to ensure the safety and satisfaction of residents. Overall, the residential construction market in the US is dynamic and forward-thinking, with a focus on sustainability, safety, and community.

Request Free Sample

The Apartments and condominiums segment was valued at USD 509.50 million in 2019 and showed a gradual increase during the forecast period.

Request Free Sample

Market Dynamics

Our researchers analyzed the data with 2024 as

Mid‑Term Rental Platforms Market Outlook

According to our latest research, the Global Mid‑Term Rental Platforms market size was valued at $6.2 billion in 2024 and is projected to reach $18.7 billion by 2033, expanding at a CAGR of 12.8% during the forecast period of 2024–2033. This remarkable growth trajectory is primarily driven by the rising demand for flexible housing solutions among digital nomads, expatriates, students, and corporations seeking alternatives to traditional long-term leases and short-term vacation rentals. The evolution of remote work, globalization of talent, and increasing mobility of the workforce have fundamentally altered living patterns, fueling demand for mid-term rental options that offer both convenience and cost-effectiveness. As urbanization accelerates and consumers seek adaptable, tech-enabled housing solutions, the mid-term rental platforms market is poised for robust expansion on a global scale.

Regional Outlook

The North American region currently commands the largest share of the global mid-term rental platforms market, accounting for approximately 38% of total market value in 2024. This dominance is underpinned by a mature digital infrastructure, high internet penetration, and a well-established ecosystem of property management and rental technology providers. The United States, in particular, has witnessed strong adoption among urban professionals, students, and corporate clients, driven by the proliferation of remote work and frequent corporate relocations. Regulatory clarity in key metropolitan areas, coupled with a robust supply of diverse property types, has further accelerated the market’s maturity. Additionally, the presence of leading platform innovators and strong venture capital backing has enabled rapid scaling and innovation, positioning North America as the bellwether for mid-term rental trends.

In contrast, the Asia Pacific region is emerging as the fastest-growing market, projected to register a CAGR of 15.2% from 2024 to 2033. Rapid urbanization, a burgeoning middle class, and the growing influx of international students and expatriates are fueling demand for flexible rental solutions in cities such as Singapore, Tokyo, Sydney, and Bangalore. Governments across the region are increasingly embracing digital transformation in real estate, while local and international investors are pouring capital into platform development and property acquisition. The rise of tech-savvy millennial and Gen Z populations, combined with escalating real estate prices and housing shortages in major urban centers, is accelerating the shift toward mid-term rentals as a viable, affordable alternative. Strategic partnerships between local developers and global platform providers are also fostering innovation and market penetration.

Meanwhile, emerging economies in Latin America and the Middle East & Africa present both significant opportunities and unique challenges for mid-term rental platforms. While demand is growing, especially in gateway cities and educational hubs, adoption is often hampered by fragmented regulatory environments, limited digital payment infrastructure, and a lack of standardized property listings. Localized demand is shaped by specific cultural factors, such as extended family living arrangements and varying attitudes toward rental versus ownership. However, government initiatives to promote smart cities, digital transformation, and international investment in real estate are gradually creating a more conducive environment for mid-term rental platforms. Overcoming these market entry barriers will require tailored strategies, robust localization, and close collaboration with regional stakeholders.

Report Scope

How many incorporated places are registered in the U.S.?

There were 19,502 incorporated places registered in the United States as of July 31, 2019. 16,410 had a population under 10,000 while, in contrast, only 10 cities had a population of one million or more.

Small-town America

Suffice it to say, almost nothing is more idealized in the American imagination than small-town America. When asked where they would prefer to live, 30 percent of Americans reported that they would prefer to live in a small town. Americans tend to prefer small-town living due to a perceived slower pace of life, close-knit communities, and a more affordable cost of living when compared to large cities.

An increasing population

Despite a preference for small-town life, metropolitan areas in the U.S. still see high population figures, with the New York, Los Angeles, and Chicago metro areas being the most populous in the country. Metro and state populations are projected to increase by 2040, so while some may move to small towns to escape city living, those small towns may become more crowded in the upcoming decades.