Graph and download economic data for Housing Inventory: Active Listing Count in Washington-Arlington-Alexandria, DC-VA-MD-WV (CBSA) (ACTLISCOU47900) from Jul 2016 to Jun 2025 about DC, Washington, MD, WV, active listing, VA, listing, and USA.

United States Months of Supply: sa: All Residential: Washington, DC data was reported at 1.499 Month in Jul 2020. This records a decrease from the previous number of 1.927 Month for Jun 2020. United States Months of Supply: sa: All Residential: Washington, DC data is updated monthly, averaging 2.588 Month from Feb 2012 (Median) to Jul 2020, with 102 observations. The data reached an all-time high of 3.904 Month in Mar 2012 and a record low of 1.499 Month in Jul 2020. United States Months of Supply: sa: All Residential: Washington, DC data remains active status in CEIC and is reported by Redfin. The data is categorized under Global Database’s United States – Table US.EB030: Months of Supply: by Metropolitan Areas: Seasonally Adjusted.

DATA SOURCES:

1. ONLY state sources (city/county/state administration, federal agencies, ministries, etc.). We DO NOT use unverified databases
2. Over 2300 sources. We use even the smallest sources, because they contain valuable data. This allows us to provide our users with the most complete data

DATA RELEVANCE:

1. Our data is updated daily, weekly, monthly depending on the sources
2. We collect, process and store all data, regardless of their relevance. Historical data is also valuable

DATA TYPES:

1. Specifications
2. Owners
3. Permits
4. Sales
5. Inspections
6. Violations
7. Assessed values
8. Taxes
9. Risks
10. Foreclosures
11. Property Tax Liens
12. Deed Restrictions

NUMBERS:

1. 2300 data sources in total
2. 217 data sources in Washington, D.C.
3. 315,000+ properties in Washington, D.C.
4. 4 billion records (listed in the "data types" block above) in total
5. 2 million new records every day

DATA USAGE:

1. Property check, investigation (even the smallest events are stored in our database)
2. Prospecting (more than 100 parameters to find the required records)
3. Tracking (our data allows us to track any changes)

The US luxury residential market, encompassing apartments, condominiums, villas, and landed houses, is a dynamic sector exhibiting robust growth. Driven by factors such as increasing high-net-worth individuals, a preference for upscale amenities and locations in prime cities like New York, Los Angeles, and San Francisco, and a sustained demand for second homes and investment properties, the market is projected to maintain a compound annual growth rate (CAGR) exceeding 3% from 2025 to 2033. While rising construction costs and interest rates pose challenges, the inherent resilience of the luxury segment, fueled by a limited supply of high-end properties and consistent demand from affluent buyers, mitigates these constraints. The segment's performance is geographically concentrated, with major metropolitan areas capturing the lion's share of market activity. Prominent developers like Toll Brothers Inc. and D.R. Horton are major players, contributing significantly to the market's supply. However, the market also faces challenges such as regulatory changes affecting construction and zoning, which could influence future growth. Furthermore, fluctuating global economic conditions and shifts in investor sentiment can impact demand in the luxury sector. The market segmentation highlights a strong preference for apartments and condominiums in urban centers, reflecting the lifestyle choices of many high-net-worth individuals. Villas and landed houses remain popular in suburban and rural areas, catering to a different segment of buyers prioritizing privacy and space. The regional analysis indicates that North America, particularly the US, dominates the luxury residential market, although international investment continues to play a significant role. The robust pipeline of luxury projects underway suggests continued growth, driven by sophisticated design, advanced technology integration in homes, and an increasing focus on sustainability. The market's performance will depend on the interplay of economic indicators, evolving consumer preferences, and the effective management of regulatory and infrastructural challenges. Understanding these dynamics is crucial for investors and developers aiming to navigate this lucrative yet complex market segment. Recent developments include: October 2021: Toll Brothers Inc. - the country's leading builder of luxury homes, through its Toll Brothers Campus Living Division and CanAm Capital Partners - the private equity affiliate of CanAm enterprises and a leading provider of project-level structured debt and equity solutions, announced the formation of a new joint venture. This joint venture will develop Lapis, a 1086-bed 293-unit luxury student housing community at Florida International University (FIU) in Miami, Florida. The community will offer luxury amenities, multiple study lounges, high-speed internet throughout the community, a resort-style pool, fitness center, bike storage, club room, outdoor kitchens, business center, and secured garage., November 2021: Toll Brothers Inc. - the nation's leading builder of luxury homes, through its Toll Brothers Apartment Living rental division and Sundance Bay - a leading private real estate investment and operating firm, announced the formation of a new joint venture to develop Broad & Noble. It is a 344-unit mixed-use rental apartment community in Philadelphia, Pa. This 18-story high-rise building will feature high-end luxury finishes, a fitness center, music, media, and podcast rooms; a conservatory and private dining rooms; a yoga and cycling studio, sky lounge with an outdoor deck area. Additionally, it will consist landscaped plaza, private storage areas, an access-controlled garage with bike storage, and a pet spa.. Notable trends are: Home Automation Becoming a Pre-requisite for Luxury Real Estate.

The global New Energy Vehicle (NEV) motor housing market is experiencing robust growth, driven by the accelerating adoption of electric vehicles (EVs) and hybrid electric vehicles (HEVs) worldwide. The market's expansion is fueled by stringent government regulations aimed at reducing carbon emissions, coupled with increasing consumer demand for eco-friendly transportation solutions. Technological advancements in motor design, leading to higher efficiency and power density, further contribute to market growth. The market is segmented by application (passenger vehicles and commercial vehicles) and type (DC motor housings and AC asynchronous motor housings). Passenger vehicles currently dominate the market, but the commercial vehicle segment is projected to witness significant growth in the coming years due to the electrification of buses, trucks, and other commercial fleets. Key players in the market are continuously investing in research and development to improve the performance, durability, and cost-effectiveness of NEV motor housings. Competition is intense, with both established players and new entrants vying for market share. Regional growth varies, with Asia Pacific, particularly China, expected to remain the largest market due to its substantial EV manufacturing base and government support for the NEV industry. While the North American and European markets are also experiencing substantial growth, they lag behind Asia Pacific in terms of market size. Challenges remain, including the high cost of raw materials and the need for continuous innovation to meet the evolving demands of the NEV industry. However, the overall outlook for the NEV motor housing market remains positive, with substantial growth expected throughout the forecast period. The forecast period (2025-2033) anticipates a sustained high CAGR, reflecting ongoing advancements in battery technology, improving charging infrastructure, and the increasing affordability of EVs. This positive trend is further supported by government incentives and subsidies designed to accelerate the transition to electric mobility. While supply chain disruptions and fluctuations in raw material prices may pose temporary challenges, the long-term growth trajectory remains strong. The market's competitive landscape is characterized by both large multinational corporations and specialized component manufacturers. Strategic alliances, mergers, and acquisitions are anticipated to reshape the competitive landscape further. Focus on lightweighting technologies, improved thermal management solutions, and the development of more sustainable manufacturing processes will be critical for companies seeking to maintain a competitive edge. The market segmentation by type (DC and AC motor housings) will likely see a shift in market share over time, influenced by advancements in motor technology and the evolving requirements of different EV applications.

The New Energy Vehicle (NEV) Motor Housing market is experiencing robust growth, driven by the burgeoning adoption of electric vehicles (EVs) and hybrid electric vehicles (HEVs) globally. The market, currently valued at approximately $5 billion in 2025, is projected to witness a Compound Annual Growth Rate (CAGR) of 15% from 2025 to 2033. This significant expansion is fueled by several key factors: increasing government incentives promoting NEV adoption, stringent emission regulations leading to the phase-out of internal combustion engine vehicles, and continuous advancements in battery technology, enhancing EV range and performance. The market segmentation reveals a strong demand for both passenger vehicle and commercial vehicle motor housings, with DC motor housings currently holding a larger market share due to their prevalence in smaller EVs. However, AC asynchronous motor housings are anticipated to gain traction in the coming years as higher-power EVs become more prevalent. Competitive landscape analysis reveals a mix of established players like Hitachi Metals and emerging regional manufacturers in China. This competitive environment fosters innovation and cost optimization, benefiting consumers. The market's growth trajectory is expected to remain positive throughout the forecast period, fueled by sustained investment in charging infrastructure, ongoing improvements in NEV technology, and the expanding global middle class with increasing purchasing power. However, challenges such as the high initial cost of EVs, uneven distribution of charging infrastructure in certain regions, and potential supply chain disruptions related to raw materials may pose some restraints on market growth. Nevertheless, the long-term outlook remains optimistic, with the NEV sector poised for significant expansion, translating into substantial growth for the NEV Motor Housing market. The market's geographical distribution indicates significant growth opportunities in Asia Pacific, particularly in China and India, owing to their large automotive markets and supportive government policies. This comprehensive report provides an in-depth analysis of the burgeoning New Energy Vehicle (NEV) Motor Housing market, projected to reach $15 billion by 2030. It delves into market segmentation, key players, growth drivers, challenges, and emerging trends, offering valuable insights for stakeholders across the automotive and manufacturing industries. The report leverages extensive primary and secondary research to deliver actionable intelligence for strategic decision-making.

This data package includes the underlying data files to replicate the data and charts presented in Why China's housing policies have failed, PIIE Working Paper 23-5.

If you use the data, please cite as: Huang, Tianlei. 2023. Why China's housing policies have failed. PIIE Working Paper 23-5. Washington, DC: Peterson Institute for International Economics.

United Kingdom (DC)GDP: sa: HCE: Domestic: Housing: Water Supply & Misc (WS) data was reported at 2,254.000 GBP mn in Mar 2011. This records an increase from the previous number of 2,228.000 GBP mn for Dec 2010. United Kingdom (DC)GDP: sa: HCE: Domestic: Housing: Water Supply & Misc (WS) data is updated quarterly, averaging 456.000 GBP mn from Mar 1963 (Median) to Mar 2011, with 193 observations. The data reached an all-time high of 2,254.000 GBP mn in Mar 2011 and a record low of 27.000 GBP mn in Mar 1963. United Kingdom (DC)GDP: sa: HCE: Domestic: Housing: Water Supply & Misc (WS) data remains active status in CEIC and is reported by Office for National Statistics. The data is categorized under Global Database’s United Kingdom – Table UK.A067: ESA 1995: GDP: Household Consumption Expenditure: Current Prices: Seasonally Adjusted (Discontinued).

Abstract

Over the past decade, Albania has been seeking to develop the framework for a market economy and more open society. It has faced severe internal and external challenges in the interim – extremely low income levels and a lack of basic infrastructure, the rapid collapse of output and inflation rise after the shift in regime in 1991, the turmoil during the 1997 pyramid crisis, and the social and economic shocks accompanying the 1999 Kosovo crisis. In the face of these challenges, Albania has made notable progress in creating conditions conducive to growth and poverty reduction.

In the process leading to its first Poverty Reduction Strategy (that is the National Strategy for Socioeconomic Development, now renamed the National Strategy for Development and Integration), the Government of Albania reinforced its commitment to strengthening its own capacity to collect and analyze on a regular basis the information it needs to inform policy-making.

Multi-purpose household surveys are one of the main sources of information to determine living conditions and measure the poverty situation of a country. They provide an indispensable tool to assist policy-makers in monitoring and targeting social programs. In its first phase (2001-2006), this monitoring system included the following data collection instruments: (i) Population and Housing Census; (ii) Living Standards Measurement Surveys every 3 years, and (iii) annual panel surveys.

The Population and Housing Census (PHC) conducted in April 2001, provided the country with a much needed updated sampling frame which is one of the building blocks for the household survey structure. The focus during this first phase of the monitoring system is on a periodic LSMS (in 2002 and 2005), followed by panel surveys on a subsample of LSMS households (in 2003, and 2004), drawing heavily on the 2001 census information.

A poverty profile based on 2002 data showed that some 25 percent of the population are poor, with many others vulnerable to poverty due to their incomes being close to the poverty threshold. Income related poverty is compounded by poor access to basic infrastructure (regular supply of electricity, clean water), education and health services, housing, etc.

The 2005 LSMS was in the field between May and early July, with an additional visit to agricultural households in October, 2005. The survey work was undertaken by the Living Standards unit of INSTAT, with the technical assistance of the World Bank.

Geographic coverage

National coverage. Domains: Tirana, other urban, rural; Agro-ecological areas (coastal, central, mountain)

Analysis unit

• Households
• Individuals

Kind of data

Sample survey data [ssd]

Sampling procedure

The Republic of Albania is divided geographically into 12 Prefectures (Prefekturat). The latter are divided into Districts (Rrethet) which are, in turn, divided into Cities (Qyteti) and Communes (Komunat). The Communes contain all the rural villages and the very small cities. For census purposes, the cities and the villages have been divided into enumeration areas (EAs).

1. Sampling frame

The Enumeration Areas (EA) that make up the sampling frame come from the April 2001 General Census of Population and Housing. The EAs in the frame are classified by Prefecture, District, City or Commune. The frame also contains, for every EA, the number of Housing Units (HU), the number of occupied HUs, the number of unoccupied HUs, the number of households, and the population. We are using occupied dwellings and not total number of dwellings since many EAs contain a large number of empty dwellings.

A detailed study of the list of census EAs shows that many have zero population. In order to obtain EAs with the minimum of 50 and the maximum of 120 occupied housing units, the EAs with zero population have been taken off the sampling frame. Since the sizes of the EAs varied from 0 to 395 HUs, the smaller EAs (with less than 50 HU) have been collapsed with geographically adjacent ones and the largest EAs (with more than 120 HU) have been split into two or more EAs. Subsequently, maps identifying the boundaries of every split and collapsed EA were prepared. Given that the 2002 LSMS has been conducted less than a year after the April 2001 census, a listing operation to update the sample EAs was not conducted in the field. However, since the level of construction is very high in the city of Tirana and its suburbs, a quick count of the 75 sample EAs selected in Tirana was carried out followed by a listing operation. The check of the listing based on the Census data revealed two types of discrepancies: - HUs had become invalid, i.e. vacant, nonresidential, demolished, seasonally occupied, etc. - Instead of one small building (with one or two HU), a new one with 15 HUs was identified.

During of the listing update process, HUs identified as invalid were taken off the frame. In the case of a new building, these new HUs were entered with a new sequential code. The listing sheets prepared during the listing operation in Tirana, become the sampling frame for the final stage of selection of 12 HU which has to be interviewed. The unit of analysis and the unit of observation is the household. The universe under study consists of all the households in the Republic of Albania. We have used the Housing Unit (defined as the space occupied by one household) as the sampling unit, instead of the household, because the HU is more permanent and easier to identify in the field.

1. Sample Size

In the LSMS the sample size is 450 EA and in each EA 8 households were selected. So the total sample size of the LSMS is 3600 households. In addition, since a certain level of nonresponse is expected, 4 reserve units were selected in each sample EA.

1. Stratification

The sampling frame has been divided in three regions (strata) 1. Coastal Area 2. Central Area 3. Mountain Area and Tirana (urban and other urban) is consider as a separate strata.

The first three strata were divided into major cities (the most important cities in the region), other urban (the rest of cities in the region), and rural. In each more importance was given to the major cities and rural areas. We have selected 10 EA for each major city and 65 EAs (75 EAs for Mountain Area) for each region. In the city of Tirana and its suburbs, implicit stratification was used to improve the efficiency of the sample design.

1. Procedure for the Selection of Housing Units

A fixed number of valid dwelling units (12) was selected systematically and with equal probability from the Listing Form pertaining to Tirana and from the Census forms for the other areas. Once the 12 HUs were selected, 4 of them were chosen at random and kept as reserve units. The selected HUs were numbered within the EA and identified with a circle around the number in the listing form, as well as a circle on the maps. The reserve sample (units 9 to 12) were identified from R1 to R4 during data collection to emphasize the fact that they were reserve units.

Two copies of the sample listing sheets and two copies of maps for each EA were printed. The first copy of the listing sheet and the map were given to the supervisor and included the 12 HU, the second copy was given to the enumerator. The enumerator only received the 8 dwelling units, not the reserve ones. Each time the enumerator needed a reserve HU, he/she had to ask the supervisor and explain the reason why a reserve unit was needed. This process helped determine the reason why reserve units were used and provided more control on their use.

In the field the enumerator registered the occupancy status of every unit: - occupied as principal residence - vacant - under construction (not occupied) - demolished or abandoned (not occupied) - seasonally occupied

In the case that one HU was found to be invalid, the enumerator used the first reserve unit (identified with the code R1). In the case that in one EA more than 4 DU selected were invalid, other units from that EA chosen at random by headquarter (in Tirana) were selected as replacement units to keep the enumerator load constant and maintain a uniform sample size in each EA. Before identifying the invalid HUs, the interviewer had to note the interview status of each visit for all the units for which an interview was attempted, whether these are original units or reserve units. This was done to determine the interview status: interview completed, nonresponse, refusal, etc. In other words, this will allow identifying: the completed interviews (responses obtained), the incomplete but usable ones (responses obtained), the incomplete ones but not usable (nonresponse), the refusals (nonresponse) and the "not at home" (nonresponse). Subsequently, the invalid units identified were substituted with the available reserves, always maintaining the sample of 8 HUs.

Mode of data collection

Face-to-face [f2f]

Research instrument

Four survey instruments were used to collect information for the 2005 Albania LSMS: a household questionnaire, a diary for recording household food consumption, a community questionnaire, and a price questionnaire.

The household questionnaire included all the core LSMS modules as defined in Grosh and Glewwe (2000)1, plus additional modules on migration, fertility, subjective poverty, agriculture, non-farm enterprises, and social capital. Geographical referencing data on the longitude and latitude of each household were also recorded using portable GPS devices. Geo-referencing will enable a more efficient spatial link among the different surveys of the system, as well as between the survey households and other geo-referenced information.

The choice of the modules was aimed at matching as much as

In 2022, Venlo was the leading market in the Netherlands by warehouse leasing activity with ******* square meters of take-up. Unlike for example the United Kingdom (UK) or Germany, warehouses or distribution centers (DCs) in the Netherlands are less centered around major cities. This is probably due to the small size of the country and the comparatively high connectivity to the cities and ports of both Rotterdam as well as Antwerp in Belgium. The southern provinces of the Netherlands are also popular hotspots for logistics real estate because of the lower rent prices.

International brands: an important driver behind the Netherlands’ logistics market

The total size of the Dutch logistics market was approximately ** million square meters in 2020, the highest number in nine years. This is because many international brands opened distribution centers in the Netherlands. Venlo, for example, supplies European fashion brands Michael Kors, Tommy Hilfiger, Calvin Klein and Under Armour via Trade Port Venlo Noord. Spain’s Inditex (the company behind Zara, Pull&Bear and Berschka) are to open a logistics center in Lelystad in 2019, whilst Lidl opened its European e-commerce DC in the West-Brabant region (around the city of Roosendaal) in 2018.

Dutch warehouses are popular investment tools for foreign investors

The Netherlands’ growth as a logistics hub for retailers and e-commerce companies in Europe hasn’t gone unnoticed. In 2019, ** percent of all investments in logistics property in the country came from foreign investors. Most cross-border capital came from Germany and the UK, with **** percent coming from South Korean investors.

United Kingdom (DC)GDP: sa: HCE: Domestic: Housing: WS: Water Supply data was reported at 1,101.000 GBP mn in Mar 2011. This records an increase from the previous number of 1,079.000 GBP mn for Dec 2010. United Kingdom (DC)GDP: sa: HCE: Domestic: Housing: WS: Water Supply data is updated quarterly, averaging 222.000 GBP mn from Mar 1963 (Median) to Mar 2011, with 193 observations. The data reached an all-time high of 1,101.000 GBP mn in Mar 2011 and a record low of 14.000 GBP mn in Jun 1964. United Kingdom (DC)GDP: sa: HCE: Domestic: Housing: WS: Water Supply data remains active status in CEIC and is reported by Office for National Statistics. The data is categorized under Global Database’s UK – Table UK.A065: ESA 1995: GDP: Household Consumption Expenditure: Current Prices: Seasonally Adjusted (Discontinued).

Months of Supply：季节性调整后：All Residential：Washington, DC在07-01-2020达1.499月，相较于06-01-2020的1.927月有所下降。Months of Supply：季节性调整后：All Residential：Washington, DC数据按月更新，02-01-2012至07-01-2020期间平均值为2.588月，共102份观测结果。该数据的历史最高值出现于03-01-2012，达3.904月，而历史最低值则出现于07-01-2020，为1.499月。CEIC提供的Months of Supply：季节性调整后：All Residential：Washington, DC数据处于定期更新的状态，数据来源于Redfin，数据归类于全球数据库的美国 – Table US.EB030：Months of Supply：by Metropolitan Areas：季节性调整后。