Vacancy rates across the office real estate sector in the U.S. increased in the first quarter of 2025. This was in line with a general trend of rising vacancies that started in 2020 during the COVID-19 pandemic. In the *** quarter of 2025, about **** percent of office space across the country was vacant. In some major U.S. markets, vacancies exceeded ** percent. With a considerable part of the workforce working from home or following a hybrid working model, businesses are cautious when it comes to upscaling or renewing leases. Workplaces may never be the same again The COVID-19 pandemic has changed the way that companies operate, with working from home has becoming the new normal for many U.S. employees. The function of the office has evolved from the primary workplace to a space where employees collaborate, exchange ideas, and socialize. That has shifted occupiers’ attention toward spaces with modern designs that can accommodate the office of the future. Many businesses used the pandemic time to revisit their office guidelines, remodel or do a full or partial fit-out. With so much focus on quality, older buildings with poorer design or energy performance are likely to suffer lower demand, resulting in a two-speed market. What do higher vacancy rates mean for investors? Simply put, if landlords do not have tenants, their income stream is disrupted, and they cannot service their debts. April 2023 data shows that several U.S. metros had a significantly high share of distressed office real estate debt. In Charlotte-Gastonia-Concord, NC-SC, more than one-third of the commercial mortgage-backed securities for offices were delinquent, in special servicing, or a combination of both. As of March 2025. offices had the highest delinquency rate in the commercial property sector.

Graph and download economic data for Rental Vacancy Rate in the United States (RRVRUSQ156N) from Q1 1956 to Q1 2025 about vacancy, rent, rate, and USA.

The supply of new office space varied greatly among selected metropolitan areas in the United States in the second quarter of 2022. New York City was the leading metropolitan area with the most office space under construction at over 22 million square feet. Austin ranked second, and the San Francisco Bay Area was third, both of them had over 11 million square feet under construction. During the same period, the absorption rates for office space in some metropolitan areas were negative.

Graph and download economic data for Home Vacancy Rate for the United States (USHVAC) from 1986 to 2024 about vacancy, housing, rate, and USA.

Freestanding retail real estate in the United States had the highest occupancy rate in the fourth quarter of 2024, at **** percent. This was *** percent higher than the average for the retail real estate sector. Malls, life centers and outlet centers had the highest vacancy, with **** percent of space occupied.

Mission Bay district of San Francisco had over 300,000 square feet of office space under construction in the first quarter of 2023. This placed it as the district with the highest amount of new office space supply in San Francisco. Only three districts, out of twelve, reported construction of new office space in this period.

Graph and download economic data for Job Openings: Total Nonfarm (JTSJOR) from Dec 2000 to May 2025 about job openings, vacancy, nonfarm, and USA.

Rental vacancy rates across the United States showed significant regional differences in 2024, with the South experiencing the highest rate at 8.7 percent. This disparity reflects broader demographic shifts and economic factors influencing the rental market. The regional variations in vacancy rates have persisted despite an overall decline since 2014, highlighting the complex dynamics of the U.S. housing landscape. Rental demand and affordability challenges The rental market continues to face pressure from high demand, particularly among younger demographics. People under 30 comprise the largest share of American renters, with approximately 42 million in this age group. Despite softening rents in some areas, affordability remains a significant issue. In 2023, 42.5 percent of renters paid gross rent exceeding 35 percent of their income, indicating widespread financial strain among tenants. Regional disparities and market trends The Northeast and West regions, which include many large urban areas, have consistently lower vacancy rates compared to the Midwest and South. This trend aligns with population shifts towards these regions, fueling higher home prices growth. The rental market has shown signs of stabilization in 2023, with the number of vacant homes for rent slightly picking up after two years of record-low vacancy.

Graph and download economic data for Infra-Annual Registered Unemployment and Job Vacancies: Total Economy: Unfilled Vacancies for United States (LMJVTTUVUSM647S) from Dec 2000 to Jan 2024 about job openings, jobs, vacancy, and USA.

The residential vacancy rate is the percentage of residential units that are unoccupied, or vacant, in a given year. The U.S. Census Bureau defines occupied housing units as “owner-occupied” or “renter-occupied.” Vacant housing units are not classified by tenure in this way, as they are not occupied by an owner or renter.

The residential vacancy rate serves as an indicator of the condition of the area’s housing market. Low residential vacancy rates indicate that demand for housing is high compared to the housing supply. However, the aggregate residential vacancy rate is lacking in granularity. For example, the housing market for rental units in the area and the market for buying a unit in the same area may be very different, and the aggregate rate will not show those distinct conditions. Furthermore, the vacancy rate may be high, or low, for a variety of reasons. A high vacancy rate may result from a falling population, but it may also result from a recent construction spree that added many units to the total stock.

The residential vacancy rate in Champaign County appears to have fluctuated between 8% and 14% from 2005 through 2022, reaching a peak near 14% in 2019. In 2023, this rate dropped to about 7%, its lowest value since 2005. However, this rate was calculated using the American Community Survey’s (ACS) estimated number of vacant houses per year, which has year-to-year fluctuations that are largely not statistically significant. Thus, we cannot establish a trend for this data.

The residential vacancy rate data shown here was calculated using the estimated total housing units and estimated vacant housing units from the U.S. Census Bureau’s American Community Survey 1-Year Estimates, which are released annually.

As with any datasets that are estimates rather than exact counts, it is important to take into account the margins of error (listed in the column beside each figure) when drawing conclusions from the data.

Due to the impact of the COVID-19 pandemic, instead of providing the standard 1-year data products, the Census Bureau released experimental estimates from the 1-year data in 2020. This includes a limited number of data tables for the nation, states, and the District of Columbia. The Census Bureau states that the 2020 ACS 1-year experimental tables use an experimental estimation methodology and should not be compared with other ACS data. For these reasons, and because data is not available for Champaign County, no data for 2020 is included in this Indicator.

For interested data users, the 2020 ACS 1-Year Experimental data release includes a dataset on Occupancy Status.

Sources: U.S. Census Bureau; American Community Survey, 2023 American Community Survey 1-Year Estimates, Table B25002, generated by CCRPC staff; using data.census.gov; (17 October 2024).; U.S. Census Bureau; American Community Survey, 2022 American Community Survey 1-Year Estimates, Table B25002, generated by CCRPC staff; using data.census.gov; (25 September 2023).; U.S. Census Bureau; American Community Survey, 2021 American Community Survey 1-Year Estimates, Table B25002, generated by CCRPC staff; using data.census.gov; (4 October 2022).; U.S. Census Bureau; American Community Survey, 2019 American Community Survey 1-Year Estimates, Table B25002, generated by CCRPC staff; using data.census.gov; (8 June 2021).; U.S. Census Bureau; American Community Survey, 2018 American Community Survey 1-Year Estimates, Table B25002, generated by CCRPC staff; using data.census.gov; (8 June 2021).; U.S. Census Bureau; American Community Survey, 2017 American Community Survey 1-Year Estimates, Table B25002, generated by CCRPC staff; using American FactFinder; (13 September 2018).; U.S. Census Bureau; American Community Survey, 2016 American Community Survey 1-Year Estimates, Table B25002, generated by CCRPC staff; using American FactFinder; (14 September 2017).; U.S. Census Bureau; American Community Survey, 2015 American Community Survey 1-Year Estimates, Table B25002, generated by CCRPC staff; using American FactFinder; (19 September 2016).; U.S. Census Bureau; American Community Survey, 2014 American Community Survey 1-Year Estimates, Table B25002; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2013 American Community Survey 1-Year Estimates, Table SB25002; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2012 American Community Survey 1-Year Estimates, Table B25002; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2011 American Community Survey 1-Year Estimates, Table B25002; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2010 American Community Survey 1-Year Estimates, Table B25002; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2009 American Community Survey 1-Year Estimates, Table B25002; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2008 American Community Survey 1-Year Estimates, Table B25002; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2007 American Community Survey 1-Year Estimates, Table B25002; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2006 American Community Survey 1-Year Estimates, Table B25002; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2005 American Community Survey 1-Year Estimates, Table B25002; generated by CCRPC staff; using American FactFinder; (16 March 2016).

United States Housing Vacancies & Homeownership: Number of Estimated Households data was reported at 121,940.000 Unit th in Sep 2018. This records an increase from the previous number of 121,307.000 Unit th for Aug 2018. United States Housing Vacancies & Homeownership: Number of Estimated Households data is updated monthly, averaging 90,091.500 Unit th from Apr 1955 (Median) to Sep 2018, with 756 observations. The data reached an all-time high of 121,940.000 Unit th in Sep 2018 and a record low of 47,788.000 Unit th in Apr 1955. United States Housing Vacancies & Homeownership: Number of Estimated Households data remains active status in CEIC and is reported by US Census Bureau. The data is categorized under Global Database’s USA – Table US.EB008: Housing Vacancy and Home Ownership Rate.

In 2023, it was estimated that over 161 million Americans were in some form of employment, while 3.64 percent of the total workforce was unemployed. This was the lowest unemployment rate since the 1950s, although these figures are expected to rise in 2023 and beyond. 1980s-2010s Since the 1980s, the total United States labor force has generally risen as the population has grown, however, the annual average unemployment rate has fluctuated significantly, usually increasing in times of crisis, before falling more slowly during periods of recovery and economic stability. For example, unemployment peaked at 9.7 percent during the early 1980s recession, which was largely caused by the ripple effects of the Iranian Revolution on global oil prices and inflation. Other notable spikes came during the early 1990s; again, largely due to inflation caused by another oil shock, and during the early 2000s recession. The Great Recession then saw the U.S. unemployment rate soar to 9.6 percent, following the collapse of the U.S. housing market and its impact on the banking sector, and it was not until 2016 that unemployment returned to pre-recession levels. 2020s 2019 had marked a decade-long low in unemployment, before the economic impact of the Covid-19 pandemic saw the sharpest year-on-year increase in unemployment since the Great Depression, and the total number of workers fell by almost 10 million people. Despite the continuation of the pandemic in the years that followed, alongside the associated supply-chain issues and onset of the inflation crisis, unemployment reached just 3.67 percent in 2022 - current projections are for this figure to rise in 2023 and the years that follow, although these forecasts are subject to change if recent years are anything to go by.

The Commercial Real Estate (CRE) industry is exhibiting significant variations across markets, with persistently high office vacancy rates juxtaposed against thriving prime office spaces. Hard hit by the widespread adoption of remote and hybrid work models, the overall office vacancy rate rose to 20.4% in Q4 2024 from the pre-pandemic rate of 16.8%. However, leasing volumes for prime office spaces are set to climb, providing opportunities for seasoned investors. On the other hand, the multifamily sector is gaining from a prominent move towards renting, primarily driven by housing affordability concerns and changing lifestyle preferences. This has increased demand for multifamily properties and opportunities to convert underutilized properties, such as offices, into residential rentals. The industrial real estate segment is also evolving, with the boom in e-commerce necessitating the development of strategically located warehouses for quick fulfillment and last-mile delivery. Industry revenue has gained at a CAGR of 0.8% to reach $1.4 trillion through the end of 2025, including a 0.4% climb in 2025 alone. The industry is grappling with multiple challenges, including high interest rates, wide buyer-seller expectation gaps and significant disparities in demand across different geographies and asset types. The Federal Reserve's persistent high-interest-rate environment creates refinancing hurdles for properties purchased during the low-rate period of 2020-2021. Because of remote working trends, office delinquency rates are predicted to climb from 11.0% in late 2024 to 14.0% by 2026, leading to a job market increasingly concentrated in certain urban centers. Through the end of 2030, the CRE industry is expected to stabilize as the construction pipeline shrinks, reducing new supply and, in turn, rebalancing supply and demand dynamics. With this adjustment, occupancy rates are likely to improve, and rents may observe gradual growth. The data center segment is set to witness accelerating demand propelled by the rapid expansion of artificial intelligence, cloud computing and the Internet of Things. Likewise, mixed-use properties are poised to gain popularity, driven by the growing appeal of flexible spaces that accommodate diverse businesses and residents. This new demand, coupled with the retiring baby boomer generation's preference for leisure-centric locales, is expected to push the transformation of traditional shopping plazas towards destination centers, offering continued opportunities for savvy CRE investors. Industry revenue will expand at a CAGR of 1.9% to reach $1.6 trillion in 2030.

Graph and download economic data for Housing Inventory Estimate: Vacant Housing Units in the United States (EVACANTUSQ176N) from Q2 2000 to Q1 2025 about vacancy, inventories, housing, and USA.

Commercial leasing providers serve as lessors of buildings for nonresidential purposes. Industry participants include owner-lessors of nonresidential buildings, establishments that rent real estate and then act as lessors in subleasing it and establishments that provide full-service office space. Through the end of 2025, lessors have experienced mixed demand from critical downstream market segments. Since the onset of COVID-19, demand for office space has been volatile amid work-from-home and hybrid work arrangements. However, demand for industrial and retail spaces has risen, bolstered by gaining e-commerce sales and resilient consumer spending, buoying industry revenue. Over the past five years, industry revenue has climbed at a CAGR of 0.6% to reach $257.5 billion, including an estimated 0.7% gain in 2025. From 2020 to 2022, commercial leasing companies benefited from low interest rates, stimulating business expansion. However, in response to surging inflation, the Federal Reserve began raising interest rates in 2022 and continued into 2023. Rising interest rates translated into higher borrowing costs for tenants seeking new leases for their business operations. This can make expanding or relocating to a larger space more expensive. The industry benefited from three interest rate cuts in 2024. Industry profit remains high, reaching 51.6% of industry revenue in 2025. Industry revenue will climb at a CAGR of 2.6% to $292.9 billion through the end of 2030. Demand for office space will remain subdued over the next five years. However, a shortage of prime office spaces will elevate rent for Class A office buildings, benefiting lessors with those in their portfolios. Per capita disposable income growth and a continuation of climbing consumer spending will bolster demand for retail spaces, especially in suburban and Sun Belt markets. E-commerce sales will continue to power demand for industrial space as the percentage of e-commerce sales to total retail sales will mount.

United States Housing Vacancy Rate: Rental data was reported at 6.800 % in Jun 2018. This records a decrease from the previous number of 7.000 % for Mar 2018. United States Housing Vacancy Rate: Rental data is updated quarterly, averaging 7.400 % from Mar 1956 (Median) to Jun 2018, with 250 observations. The data reached an all-time high of 11.100 % in Sep 2009 and a record low of 5.000 % in Dec 1981. United States Housing Vacancy Rate: Rental data remains active status in CEIC and is reported by US Census Bureau. The data is categorized under Global Database’s USA – Table US.EB008: Housing Vacancy and Home Ownership Rate.

Context

This data were collected and disseminated according to this publication: https://www.nature.com/articles/s41597-019-0273-5

All descriptors below are taken from this publication and are copyright of the authors.

Abstract

Adaptive interactions between building occupants and their surrounding environments affect both energy use and environmental quality, as demonstrated by a large body of modeling research that quantifies the impacts of occupant behavior on building operations. Yet, available occupant field data are insufficient to explore the mechanisms that drive this interaction. This paper introduces data from a one year study of 24 U.S. office occupants that recorded a comprehensive set of possible exogenous and endogenous drivers of personal comfort and behavior over time. The longitudinal data collection protocol merges individual thermal comfort, preference, and behavior information from online daily surveys with datalogger readings of occupants’ local thermal environments and control states, yielding 2503 survey responses alongside tens of thousands of concurrent behavior and environment measurements. These data have been used to uncover links between the built environment, personal variables, and adaptive actions, and the data contribute to international research collaborations focused on understanding the human-building interaction.

Background

Humans interact with the built environment in a variety of ways that contribute to both building energy use and environmental quality and thus warrant significant attention in the building design, operation, and retrofit processes. Occupants’ thermally adaptive behaviours such as adjusting thermostats and clothing, opening and closing windows and doors, operating personal heating and cooling devices, are strongly tied to total site energy consumed in residential and commercial buildings in the United States (U.S.). This dataset introduces longitudinal data from a one-year study of occupant thermal comfort and several related behavioural adaptations in an air-conditioned office setting in U.S. Offices. The primary objective of the data collection approach was to record a comprehensive range of exogenous and endogenous factors that may drive personal comfort and behaviour outcomes over time.

Methods

Longitudinal data on building occupant behavior, comfort, and environmental conditions were collected between July 2012 and August 2013 at the Friends Center office building in Center City Philadelphia, Pennsylvania, United States. Data collection proceeded in three stages:

1. Semi-structured interviews Semi-structured interviews identify aspects of behavior that are not yet well known or understood and provide a rich qualitative context for developing and interpreting responses from structured survey instruments. 32 interviews about thermal comfort and related behaviours were first conducted with office occupants from 7 air-conditioned buildings, ranging from aging to recently renovated, around the Philadelphia region

2. Site selection and subject recruitment for the longitudinal study Subject recruitment was initiated through an e-mail message sent to all employees in the Friends Center by its Executive Director. The following question areas were included: (a) demographic information, (b) office characteristics, (c) thermal comfort and preferences, (d) control options, (e) personal values, and f) typical work schedule (arrival, lunch, departure times).

3. Longitudinal survey and datalogger measurements. The final occupant sample participated in a series of subjective and objective measurements of thermal comfort, adaptive behavior, and related items. These measurements were carried via longitudinal online surveys, as well as through parallel datalogger and BAS measurements of the local environment and behavioural actions.

Technical Validation

Several measures were taken to ensure the validity of the collected data, following data collection guidance included in the final report for International Energy Agency Annex 66: Definition and Simulation of Occupant Behavior in Buildings. These measures include survey preparation phase, encourage high response rates, pilot studies, quality control, redundancy and comparison against expected conditions. Details for these measures can be found in the paper.

Usage Notes

• NaNs for certain variables do not generally imply missing data; rather, they indicate that the variable was not being measured for a given occupant at a given time stamp
• The variable “Occupant Number” refers to an occupant ID (e.g., a value between 1 and the 24 occupants who participated in the study); it does not refer to an occupancy (presence/absence) measurement.
• The variable “Occupancy 1” is an expected occupancy (presence/absence) value calculated across all time steps in the study based on the occupant’s responses about typical periods of occupancy on the background survey conducted before the start of the longitudinal measurements. The variable “Occupancy 2” is an expected occupancy state calculated across all time steps that fall under the two week daily surveying window, based on the time of arrival reported in the daily morning survey and recent departures from the office reported in the daily mid-day and afternoon surveys, as well as periods of prolonged absence reported on the retrospective surveys conducted after each two week period.

Household is an occupied housing unit. Householder is a person in whose name the housing unit is rented or owned. This person must be at least 15 years old. Family household is a household in which there is at least 1 person present who is related to the householder by birth, marriage or adoption. Family is used to refer to a family household. In general, family consists of those related to each other by birth, marriage or adoption.

This data uses the householder's person weight to describe characteristics of people living in households. As a result, estimates of the number of households do not match estimates of housing units from the Housing Vacancy Survey (HVS). The HVS is weighted to housing units, rather than the population, in order to more accurately estimate the number of occupied and vacant housing units. For more information about the source and accuracy statement of the Annual Social and Economic Supplement (ASEC) of the Current Population Survey (CPS) see the technical documentation accessible at: http://www.census.gov/programs-surveys/cps/technical-documentation/complete.html

Part Time Employment in the United States decreased to 28190 Thousand in June from 28557 Thousand in May of 2025. This dataset provides - United States Part Time Employment- actual values, historical data, forecast, chart, statistics, economic calendar and news.

Job Offers in the United States increased to 7769 Thousand in May from 7395 Thousand in April of 2025. This dataset provides the latest reported value for - United States Job Openings - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.