Graph and download economic data for Housing Inventory: Median Days on Market in Texas (MEDDAYONMARTX) from Jul 2016 to Oct 2025 about TX, median, and USA.

Context

Zillow's Economic Research Team collects, cleans and publishes housing and economic data from a variety of public and proprietary sources. Public property record data filed with local municipalities -- including deeds, property facts, parcel information and transactional histories -- forms the backbone of our data products, and is fleshed out with proprietary data derived from property listings and user behavior on Zillow.

The large majority of Zillow's aggregated housing market and economic data is made available for free download at zillow.com/data.

Content

Variable Availability:

Zillow Home Value Index (ZHVI): A smoothed seasonally adjusted measure of the median estimated home value across a given region and housing type. A dollar denominated alternative to repeat-sales indices. Find a more detailed methodology here: http://www.zillow.com/research/zhvi-methodology-6032/

Zillow Rent Index (ZRI): A smoothed seasonally adjusted measure of the median estimated market rate rent across a given region and housing type. A dollar denominated alternative to repeat-rent indices. Find a more detailed methodology here: http://www.zillow.com/research/zillow-rent-index-methodology-2393/

For-Sale Listing/Inventory Metrics: Zillow provides many variables capturing current and historical for-sale listings availability, generally from 2012 to current. These variables include median list prices and inventory counts, both by various property types. Variables capturing for-sale market competitiveness including share of listings with a price cut, median price cut size, age of inventory, and the days a listing spend on Zillow before the sale is final.

Home Sales Metrics: Zillow provides data on sold homes including median sale price by various housing types, sale counts (methodology here: http://www.zillow.com/research/home-sales-methodology-7733/), and a normalized view of sale volume referred to as turnover. The prevalence of foreclosures is also provided as ratio of the housing stock and the share of all sales in which the home was previously foreclosed upon.

For-Rent Listing Metrics: Zillow provides median rents prices and median rent price per square foot by property type and bedroom count.

Housing type definitions:

All Homes: Zillow defines all homes as single-family, condominium and co-operative homes with a county record. Unless specified, all series cover this segment of the housing stock.

Condo/Co-op: Condominium and co-operative homes.

Multifamily 5+ units: Units in buildings with 5 or more housing units, that are not a condominiums or co-ops.

Duplex/Triplex: Housing units in buildings with 2 or 3 housing units.

Tiers: By metro, we determine price tier cutoffs that divide the all homes housing stock into thirds using the full distribution of estimated home values. We then estimate real estate metrics within the property sets, Bottom, Middle, and Top, defined by these cutoffs. When reported at the national level, all Bottom Tier homes defined at the metro level are pooled together to form the national bottom tier. The same holds for Middle and Top Tier homes.

Regional Availability:

Zillow metrics are reported for common US geographies including Nation, State, Metro (2013 Census Defined CBSAs), County, City, ZIP code, and Neighborhood.

We provide a crosswalk between colloquial Zillow region names and federally defined region names and linking variables such as County FIPS codes and CBSA codes. Cities and Neighborhoods do not match standard jurisdictional boundaries. Zillow city boundaries reflect mailing address conventions and so are often visually similar to collections of ZIP codes. Zillow neighborhood boundaries can be found here.

Suppression Rules: To ensure reliability of reported values the Zillow Economic Research team applies suppression rules triggered by low sample sizes and excessive volatility. These rules are customized to the metric and region type and explain most missingness found in the provided datasets.

Additional Data Products

The following data products and more are available for free download exclusively at [Zillow.com/Data][1]:

• Zillow Home Value Forecast
• Zillow Rent Forecast
• Negative Equity (the share of mortgaged properties worth less than mortgage balance)
• Zillow Home Price Expectations Survey
• Zillow Housing Aspirations Report
• Zillow Rising Sea Levels Research
• Cash Buyers Time Series
• Buy vs. Rent Breakeven Horizon
• Mortgage Affordability, Rental Affordability, Price-to-Income Ratio
• Conventional 30-year Fixed Mortgage Rate, Weekly Time Series
• Jumbo 30-year Fixed Mortgage Rates, Weekly Time Series

Acknowledgements

The mission of the Zillow Economic Research Team is to be the most open, authoritative source for timely and accurate housing data and unbiased insight. We...

Live weekly charts for inventory, new listings, pending counts, Market Action Index, and median pending prices for the Albuquerque MSA.

This is a compilation of Python scripts used when developing the Collection of Dwellings to Represent the U.S. Housing Stock (2024 Update) NIST TN.

Graph and download economic data for Housing Inventory: Active Listing Count in Vermont (ACTLISCOUVT) from Jul 2016 to Oct 2025 about VT, active listing, listing, and USA.

Weekly Altos Research metrics: Market Action Index, inventory, pendings, prices, DOM, reductions. 7-day and 90-day readings.

Content

More details about each file are in the individual file descriptions.

Context

This is a dataset from the U.S. Census Bureau hosted by the Federal Reserve Economic Database (FRED). FRED has a data platform found here and they update their information according the amount of data that is brought in. Explore the U.S. Census Bureau using Kaggle and all of the data sources available through the U.S. Census Bureau organization page!

• Update Frequency: This dataset is updated daily.

Acknowledgements

This dataset is maintained using FRED's API and Kaggle's API.

Cover photo by Kelly Sikkema on Unsplash
Unsplash Images are distributed under a unique Unsplash License.

The online residential home sale listings industry is experiencing significant changes in its dynamics because of the increased number of homes for sale. The growth in listings is because of various factors, including a climb in the number of homeowners choosing to sell, the easing of the mortgage rate lock-in effect, and economic concerns driving the sale of investment properties. These conditions and the shift from a seller's market towards a more balanced, or even a buyer's market, translate into increased traffic and engagement on home sale platforms. This presents an opportunity for these online platforms to enhance their user experience, refine search tools and offer data analytics to help buyers navigate the increased options. By the end of 2025, industry revenue has climbed at a CAGR of 3.0% and is expected to total $2.2 billion in 2025. In 2025, revenue is expected to strengthen by an estimated 4.2%. Despite enjoying growth, the industry faces challenges with the elevated mortgage rates reducing demand for home purchases, leading to a market freeze. Despite the gain in home listings, actual transaction volumes have remained subdued, creating a challenging environment for the online residential home sale listing platforms. To stay competitive, these platforms are pivoting to offer enhanced tools for price comparisons, real-time mortgage calculators and in-depth educational content to help buyers understand the increased cost of borrowing and also navigate the high inventory but low turnover market. Industry profit has climbed as revenue has outpaced wage growth through the end of 2025. Through the end of 2030, online platforms must position themselves for demographic shifts and changing consumer preferences. Gen Z and younger millennials, who are entering homebuying age, are demanding a more tech-driven, seamless and mobile-first experience. The industry will also continue to see online platforms transform into comprehensive, one-stop digital destinations offering integrated services for every stage of the housing journey. Embracing changes such as artificial intelligence and data analytics to enhance user experience, streamlining listings uploads and offering real-time communication between buyers, sellers, and agents will be crucial for future success. Platforms that offer user-friendly, one-stop experiences and are equipped to provide advanced, feature-rich mobile experiences are set to capture greater market share. Overall, industry revenue will gain at a CAGR of 3.3% through 2030 to total $2.6 billion.

Overview

This residential real estate data set was created by Redfin, an online real estate brokerage. Published on January 9th, 2022, this data summarize the monthly housing market for every State, Metro, and Zip code in the US from 2012 to 2021. Redfin aggregated this data across multiple listing services and has been gracious enough to include property type in their reporting. Please properly cite and link to RedFin if you end up using this data for your research or project.

Source: RedFin Data Center

Property Type

Property type defined by RedFin

• All Residential: All properties defined as single-family, condominium, co-operative, townhouses, and multi-family (2-4 units) homes with a county record.
• Single Family Home (SFH): are homes built on a single lot, with no shared walls. Sometimes there’s a garage, attached or detached.
• Condominium (Condo): Usually a single unit within a larger building or community. Generally come with homeowners’ associations (HOAs), which require the residents to pay monthly or yearly dues.
• Cooperatives (Co-op): Usually a single unit within a larger building or community, but with a different way of holding a title to a shared building. You join a community and everyone in the community owns the building together.
• Townhouse: a hybrid between a condo and a single-family home. They are often multiple floors, with one or two shared walls, and some have a small yard space or rooftop deck. They’re generally larger than a condo, but smaller than a single-family home.
• Multifamily (2-4 units): They are essentially a home that has been turned into two or more units but the units cannot be purchased individually. There is one owner for the whole building.
• Land: Just land, no home of any type for sale.

Source: Building Types

Property Type

For more definitions, please visit RedFin Data Center Metrics

• Average sale to list: The mean ratio of each home's sale price divided by their list price covering all homes with a sale date during a given time period. Excludes properties with a sale price of 50%.
• Home sales: Total number of homes with a sale date during a given time period.
• Inventory: Total number of active listings on the last day of a given time period.
• Median active list ppsf: The median list price per square foot of all active listings.
• Median active list price: The median list price of all active listings.
• Median active listings: The median of how many listings were active on each day within a given time period.
• Median days on market: The number of days between the date the home was listed for sale and when the home went off-market/pending sale covering all homes with an off-market date during a given time period where 50% of the off-market homes sat longer on the market and 50% went off the market faster. Excludes homes that sat on the market for more than 1 year.
• Median days to close: The median number of days a home takes to go from pending to sold.
• Median list price: The most recent listing price covering all homes with a listing date during a given time period where 50% of the active listings were above this price and 50% were below this price.
• Median list price per square foot: The most recent listing price divided by the total square feet of the property (not the lot) covering all homes with a listing date during a given time period where 50% of the active listings were above this price per sqft and 50% were below this price per sqft.
• Median listing with price drops: The median of how many listings were active on each day and whose current list price is less than the original list price within a given time period.
• Median sale price: The final home sale price covering all homes with a sale date during a given time period where 50% of the sales were above this price and 50% were below this price.
• Median sale price per square foot: The final home sale price divided by the total square feet of the property (not the lot) covering all homes with a sale date during a given time period where 50% of the sales were above this price per sqft and 50% were below this price per sqft.
• Months of supply: When data are monthly, it is inventory divided by home sales. This tells you how long it would take supply to be bought up if no new homes came on the market.
• New listings: Total number of homes with a listing added date during a given time period.
• Off market in two weeks: The total number of homes that went under contract within two weeks of their listing date.
• Pending home sales: Total homes that went under contract during the period. Excludes homes that were on the market longer than 90 ...

This data collection provides information on the characteristics of the housing inventory in 15 Standard Metropolitan Statistical Areas (SMSAs). Data include year the structure was built, type and number of living quarters, occupancy status, presence of commercial establishments on the property, presence of a garage, and property value. Additional data focus on kitchen and plumbing facilities, type of heating fuel used, source of water, sewage disposal, and heating and air conditioning equipment. Information about housing expenses includes mortgage or rent payments, utility costs, garbage collection fees, property insurance, and real estate taxes as well as repairs, additions, or alterations to the property. Similar data are provided for housing units previously occupied by respondents who had recently moved. Indicators of housing and neighborhood quality are also supplied. Housing quality variables include privacy of bedrooms, condition of kitchen facilities, basement or roof leakage, presence of cracks or holes in walls, ceilings, or floor, reliability of plumbing and heating equipment, and concealed electrical wiring. The presence of storm doors and windows and insulation was also noted. Neighborhood quality variables indicate presence of and objection to street noise, odors, crime, litter, and rundown and abandoned structures, as well as the adequacy of street lighting, public transportation, public parks, schools, shopping facilities, and police and fire protection. Extensive information on the ability of handicapped persons to move around their homes is also provided. Respondents were asked if they needed special equipment, or the help of another person to move around. They were also asked about the presence or need for housing features to aid their movement, such as ramps, braille lettering, elevators, and extra wide doors. In addition to housing characteristics, demographic data for household members are provided, including sex, age, race, income, marital status, and household relationship. Additional data are available for the household head, including Hispanic origin, length of residence, and travel-to-work information.

This database includes data used in the Project Connect Anti-Displacement Dashboard. The file includes 2020 decennial population and housing unit counts at the Block level, combined with 2020 ACS data at the Census Tract level that was used in the 2020 Displacement Risk map. To determine displacement risk, researchers at the University of Texas conducted a three-part analysis: the presence of vulnerable populations, residential market appreciation, and demographic change. To determine vulnerable populations, the authors used indicators to identify residents who, according to academic research, are least able to absorb housing costs, which includes: communities of color, low-income households, heads of households without a bachelor's degree or higher, families with children in poverty, and renters. In 2020, the City of Austin Housing and Planning staff updated the data and simplified the categories. The data sources include the 2020 Census, 2016-2020 ACS 5-year Estimates, and City of Austin Affordable Housing Inventory. This file also includes the total income restricted units from the Comprehensive Affordable Housing Directory (CAHD) and City of Austin Affordable Housing Inventory (AHI) as of 8.22.2022.

HouseTS is a large-scale multimodal dataset for long-term U.S. house-price forecasting and socioeconomic analysis. It contains monthly observations from 2012 – 2023 for ≈ 6 000 ZIP codes spanning 30 major metropolitan areas. Each record (one ZIP × one month) provides 33 engineered features sourced from four complementary modalities:

• Housing-market metrics — Zillow Research & Redfin Data Center: median sale/list prices, inventory, new listings, days on market, transaction volumes, and more.
• Socioeconomic indicators — U.S. Census Bureau ACS 5-Year: income, population, labor-force size, poverty rate, rent burden, median commute time, etc.
• Points of Interest (POIs) — OpenStreetMap via ohsome API: monthly counts of amenities such as restaurants, schools, supermarkets, parks, and transit stations.
• Aerial imagery — USDA NAIP (1 m RGB): annual snapshots for a subset of ZIP codes in the Washington D.C.–Maryland–Virginia (DMV) region, enabling vision-based analyses.

Typical use-cases

• Spatio-temporal house-price prediction
• Socioeconomic modeling that blends census and amenity data
• Multimodal learning with tabular + satellite inputs
• Urban-change detection through remote sensing and vision–language models

Getting started & baselines

Starter notebooks, data-loading utilities, and a full suite of statistical, machine-learning, and foundation-model baselines are available on GitHub:

→ GitHub repository:

Sweden had the largest residential stock within the Nordic countries, as of 2018. It amounted to nearly five million units in total, whereas the Finnish stock followed with over three million housings that year.

Temporary Housing Placement Platforms Market Outlook

According to our latest research, the global Temporary Housing Placement Platforms market size reached USD 18.7 billion in 2024, driven by robust demand across diverse sectors and rapid digitalization of accommodation services. The market is expected to grow at a CAGR of 10.3% from 2025 to 2033, reaching an estimated value of USD 49.3 billion by 2033. This surge is primarily attributed to increasing mobility of the global workforce, rising frequency of business travel, and the growing need for flexible, short-term housing solutions in response to emergencies and relocations.

The growth trajectory of the Temporary Housing Placement Platforms market is being significantly influenced by the evolving dynamics of the modern workforce. As remote work and project-based assignments become more prevalent, both individuals and organizations are seeking adaptable accommodation solutions that can cater to short-term and long-term needs. The proliferation of digital platforms has made it easier for users to access, compare, and book temporary housing options globally, further stimulating demand. Additionally, the integration of advanced technologies such as artificial intelligence, big data analytics, and real-time booking systems has enhanced the user experience, making these platforms more efficient, transparent, and accessible. The market also benefits from the increasing trend of global mobility, where professionals, students, and families are frequently relocating for work, education, or personal reasons, thereby fueling the need for reliable and flexible temporary housing options.

Another significant growth factor is the expanding role of temporary housing placement platforms in disaster and emergency response scenarios. Governments, NGOs, and relief organizations are increasingly leveraging these platforms to provide immediate accommodation solutions for displaced populations due to natural disasters, conflicts, or other emergencies. The ability of these platforms to quickly match available housing inventory with urgent demand has proven invaluable in crisis situations, driving adoption across the humanitarian sector. Furthermore, the COVID-19 pandemic underscored the importance of agile housing solutions, as quarantine requirements and travel restrictions necessitated rapid adjustments to traditional accommodation models. This has led to the development of specialized emergency housing platforms and partnerships with local authorities, further broadening the market’s scope and impact.

The market is also experiencing growth from the rising popularity of vacation and leisure travel, with consumers increasingly seeking unique and personalized accommodation experiences. Short-term rental platforms have capitalized on this trend by offering a wide range of properties, from urban apartments to countryside retreats, catering to diverse traveler preferences. The integration of user reviews, secure payment systems, and value-added services such as concierge support or local experiences has enhanced customer trust and satisfaction. Additionally, educational institutions are utilizing temporary housing placement platforms to facilitate student accommodations, particularly for international students and participants in exchange programs. This diversification of application areas ensures sustained growth and resilience for the market, even in the face of fluctuating economic conditions.

Regionally, North America continues to dominate the Temporary Housing Placement Platforms market, accounting for the largest share in 2024 due to its advanced digital infrastructure, high corporate mobility, and established presence of leading platform providers. Europe follows closely, driven by cross-border mobility within the European Union and a strong culture of business and leisure travel. The Asia Pacific region is witnessing the fastest growth, propelled by rapid urbanization, increasing expatriate populations, and government initiatives to support disaster resilience and student mobility. Latin America and the Middle East & Africa are emerging as promising markets, supported by improving internet penetration and growing awareness of temporary housing solutions. The regional outlook remains positive, with each geography presenting unique opportunities and challenges for market players.

The Real Estate Sales and Brokerage industry has faced headwinds recently, mainly because of high mortgage rates. Between 2022 and 2023, the Federal Reserve raised its benchmark interest rate 11 times to manage inflation. Although reduced several times since, the aftermath remains prevalent, with mortgage rates still significantly higher than the levels of 2019-2021. This has stifled homebuyer demand, resulting in reduced home sales and pressure on related sectors. Agents and brokers are adjusting to this new reality, with many would-be homeowners delaying or reconsidering their purchasing plans. The office market has also been impacted, facing high vacancy rates. Despite the challenges, there are indicators of resilience in the industry. Housing inventory has increased, alleviating some buying pressures and providing more options for buyers. Brokers and agents are shifting their strategies, focusing more on marketing and price negotiations. Home prices have continued to climb, benefiting agents and brokerages whose commission relies on selling prices. In the office market, despite an increase in vacancies, sales of buildings have been on the rise; brokers have found opportunities by focusing on high-quality assets, such as Class A office spaces. Nonetheless, because of the industry's robust performance from 2020 to 2021, revenue has climbed at a CAGR of 0.7% over the past five years, reaching $240.0 billion in 2025. 2025 revenue will climb an estimated 0.6% as home price appreciation and a rebound in commercial sales volume will fuel tepid growth. The 'higher for longer' mortgage rate environment will persist, but reductions in interest rates will make new building constructions less expensive, leading to a gain in apartment complex constructions and benefiting real estate professionals. Supply constraints will gradually ease as housing starts are projected to strengthen, resulting in a more balanced and sustainable market. The industry will also see technological advancements with a greater reliance on AI-driven lead generation, virtual staging and automated transaction tools. Federal efforts to alleviate housing shortages through regulatory reforms and the use of federal lands for housing construction may boost the industry. Overall, industry revenue will gain at a CAGR of 1.8% to reach $262.6 billion in 2030.

A. SUMMARY

This dataset reports the number of new residential units made available for occupancy in San Francisco since January 2018. Each row in this dataset shows the change in the number of new units associated with a building permit application. Each row also includes the date those units were approved for occupancy, the type of document approving them, and their address.

Values in the column [Number of Units Certified] can be added together to produce a count of new units approved for occupancy since January 2018.

These records provide a preliminary count of new residential units. The San Francisco Planning Department issues a Housing Inventory Report each year that provides a more complete account of new residential units, and those results may vary slightly from records in this dataset. The Housing Inventory Report is an in-depth annual research project requiring extensive work to validate information about projects. By comparison, this dataset is meant to provide more timely updates about housing production based on available administrative data. The Department of Building Inspection and Planning Department will reconcile these records with future Housing Inventory Reports.

B. METHODOLOGY

At the end of each month, DBI staff manually calculate how many new units are available for occupancy for each building permit application and enters that information into this dataset. These records reflect counts for all types of residential units, including authorized accessory dwelling units. These records do not reflect units demolished or removed from the city’s available housing stock.

Multiple records may be associated with the same building permit application number, which means that new certifications or amendments were issued. Only changes to the net number of units associated with that permit application are recorded in subsequent records.

For example, Building Permit Application Number [201601010001] located at [123 1st Avenue] was issued an [Initial TCO] Temporary Certificate of Occupancy on [January 1, 2018] approving 10 units for occupancy. Then, an [Amended TCO] was issued on [June 1, 2018] approving [5] additional units for occupancy, for a total of 15 new units associated with that Building Permit Application Number. The building will appear as twice in the dataset, each row representing when new units were approved.

If additional or amended certifications are issued for a building permit application, but they do not change the number of units associated with that building permit application, those certifications are not recorded in this dataset. For example, if all new units associated with a project are certified for occupancy under an Initial TCO, then the Certificate of Final Completion (CFC) would not appear in the dataset because the CFC would not add new units to the housing stock. See data definitions for more details.

C. UPDATE FREQUENCY

This dataset is updated monthly.

D. DOCUMENT TYPES

Several documents issued near or at project completion can certify units for occupation. They are: Initial Temporary Certificate of Occupancy (TCO), Amended TCO, and Certificate of Final Completion (CFC).

• Initial TCO is a document that allows for occupancy of a unit before final project completion is certified, conditional on if the unit can be occupied safely. The TCO is meant to be temporary and has an expiration date. This field represents the number of units certified for occupancy when the TCO is issued. • Amended TCO is a document that is issued when the conditions of the project are changed before final project completion is certified. These records show additional new units that have become habitable since the issuance of the Initial TCO. • Certificate of Final Completion (CFC) is a document that is issued when all work is completed according to approved plans, and the building is ready for complete occupancy. These records show additional new units that were not accounted for in the Initial or Amended TCOs.

This feature layer contains Median List Price data for the greater Bozeman, MT area sourced from Realtor.com and provided by FRED Economic Data hosted by the Economic Research Division of the Federal Reserve Bank of St. Louis. Median Listing Price refers to the median market inventory value of the suggested gross sale price of real estate property within the specified geography for the specified period of time. Geography may include listing prices outside of the City of Bozeman city limits.Processing Notes:Data is retrieved from the FRED API and imported into FME to create and AGOL Feature Service. Units: USD, not seasonally adjustedMonthly reporting frequencyDownload Median Listing Price data for the greater Bozeman, MT areaAdditional LinksFRED Economic DataRealtor.com Research Data

Property currently or historically owned and managed by the City of Chicago. Information provided in the database, or on the City’s website generally, should not be used as a substitute for title research, title evidence, title insurance, real estate tax exemption or payment status, environmental or geotechnical due diligence, or as a substitute for legal, accounting, real estate, business, tax or other professional advice. The City assumes no liability for any damages or loss of any kind that might arise from the reliance upon, use of, misuse of, or the inability to use the database or the City’s web site and the materials contained on the website. The City also assumes no liability for improper or incorrect use of materials or information contained on its website. All materials that appear in the database or on the City’s web site are distributed and transmitted "as is," without warranties of any kind, either express or implied as to the accuracy, reliability or completeness of any information, and subject to the terms and conditions stated in this disclaimer.

The following columns were added 4/14/2023:

• Sales Status
• Sale Offering Status
• Sale Offering Reason
• Square Footage - City Estimate
• Land Value (2022) -- Note: The year will change over time.

The following columns were added 3/19/2024:

• Application Use
• Grouped Parcels
• Application Deadline
• Offer Round
• Application URL

Common-Stock Time Series for Walker & Dunlop Inc. Walker & Dunlop, Inc., through its subsidiaries, originates, sells, and services a range of multifamily and other commercial real estate financing products and services for owners and developers of real estate in the United States. It operates through three segments: Capital Markets, Servicing & Asset Management, and Corporate. The company offers first mortgage, second trust, supplemental, construction, mezzanine, preferred equity, and small-balance loans. It also provides finance for multifamily, manufactured housing communities, student housing, affordable housing, and senior housing properties under the Fannie Mae's DUS program; and construction and permanent loans to developers and owners of multifamily housing, affordable housing, senior housing, and healthcare facilities. In addition, the company acts as a debt broker to work with life insurance companies, banks, and other institutional lenders to find debt and/or equity solution for the borrowers' needs; and offers property sales brokerage services to owners and developers of multifamily properties, and commercial real estate and multifamily property appraisals for various investors. Further, it provides multifamily appraisal and valuation services; and real estate-related investment banking and advisory services, including housing market research. Additionally, the company offers servicing and asset-managing the portfolio of loans; originates loans through its principal lending and investing activities; and manages third-party capital invested in tax credit equity funds focused on the LIHTC sector and other commercial real estate sectors. Walker & Dunlop, Inc. was founded in 1937 and is headquartered in Bethesda, Maryland.