Summary statistics for housing transactions by local authority in England and Wales, on an annual basis, updated quarterly using HM Land Registry Price Paid Data. Select values from the Year and Month dimensions for data for a 12-month period ending that month and year (e.g. selecting June and 2018 will return the twelve months to June 2018).

Description:

This dataset contains prices of New York houses, providing valuable insights into the real estate market in the region. It includes information such as broker titles, house types, prices, number of bedrooms and bathrooms, property square footage, addresses, state, administrative and local areas, street names, and geographical coordinates.

Key Features:

• BROKERTITLE: Title of the broker
• TYPE: Type of the house
• PRICE: Price of the house
• BEDS: Number of bedrooms
• BATH: Number of bathrooms
• PROPERTYSQFT: Square footage of the property
• ADDRESS: Full address of the house
• STATE: State of the house
• MAIN_ADDRESS: Main address information
• ADMINISTRATIVE_AREA_LEVEL_2: Administrative area level 2 information
• LOCALITY: Locality information
• SUBLOCALITY: Sublocality information
• STREET_NAME: Street name
• LONG_NAME: Long name
• FORMATTED_ADDRESS: Formatted address
• LATITUDE: Latitude coordinate of the house
• LONGITUDE: Longitude coordinate of the house

Potential Use Cases:

• Price analysis: Analyze the distribution of house prices to understand market trends and identify potential investment opportunities.
• Property size analysis: Explore the relationship between property square footage and prices to assess the value of different-sized houses.
• Location-based analysis: Investigate geographical patterns to identify areas with higher or lower property prices.
• Bedroom and bathroom trends: Analyze the impact of the number of bedrooms and bathrooms on house prices.
• Broker performance analysis: Evaluate the influence of different brokers on the pricing of houses.

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This data sets out levels of support with housing costs, known as the Local Housing Allowance (LHA) rate, for 2013-14, 2014-15, 2015-16, 2016-17, 2017-18, 2019-19, 2019-20, 2020-21 and 2021-22. The Allowance is set for different property sizes in each Broad Rental Market Area, or BRMA. These are not the same as county or district areas. You can find out more about BRMAs here. The Valuation Office Agency (VOA) completes a six-monthly survey of private rents across England which is used to set the LHA rates. However in 2016-17, many rates were frozen at 2015-16 levels due to national austerity measures. Since then, selected BRMAs have had their LHA rates adjusted, despite the general freeze. In 2020/21 rates were increased up to a set maximum to help mitigate the effects of the covid-19 pandemic, so LHAs would support a higher level rent than previously. For 2021-22 LHA rates have been held at the same level as 2020-21. The data comes from the Valuation Office Agency (VOA) and is available online at www.gov.uk. Individuals should seek advice about their individual claims from their local authority benefit team. The VOA provides a search facility to help applicants identify the relevant LHA for them. This search is based on postcode and property size and can be found at http://lha-direct.voa.gov.uk/search.aspx.

Graph and download economic data for All-Transactions House Price Index for Wisconsin (WISTHPI) from Q1 1975 to Q3 2025 about WI, appraisers, HPI, housing, price index, indexes, price, and USA.

New housing price index (NHPI). Monthly data are available from January 1981. The table presents data for the most recent reference period and the last four periods. The base period for the index is (201612=100).

Portugal, Canada, and the United States were the countries with the highest house price to income ratio in 2024. In all three countries, the index exceeded 130 index points, while the average for all OECD countries stood at 116.2 index points. The index measures the development of housing affordability and is calculated by dividing nominal house price by nominal disposable income per head, with 2015 set as a base year when the index amounted to 100. An index value of 120, for example, would mean that house price growth has outpaced income growth by 20 percent since 2015. How have house prices worldwide changed since the COVID-19 pandemic? House prices started to rise gradually after the global financial crisis (2007–2008), but this trend accelerated with the pandemic. The countries with advanced economies, which usually have mature housing markets, experienced stronger growth than countries with emerging economies. Real house price growth (accounting for inflation) peaked in 2022 and has since lost some of the gain. Although, many countries experienced a decline in house prices, the global house price index shows that property prices in 2023 were still substantially higher than before COVID-19. Renting vs. buying In the past, house prices have grown faster than rents. However, the home affordability has been declining notably, with a direct impact on rental prices. As people struggle to buy a property of their own, they often turn to rental accommodation. This has resulted in a growing demand for rental apartments and soaring rental prices.

This dataset was generated for analyzing the economic impacts of subway networks on housing prices in metropolitan areas. The provision of transit networks and accompanying improvement in accessibility induce various impacts and we focused on the economic impacts realized through housing prices. As a proxy of housing price, we consider the price of condominiums, the dominant housing type in South Korea. Although our focus is transit accessibility and housing prices, the presented dataset is applicable to other studies. In particular, it provides a wide range of variables closely related to housing price, including housing properties, local amenities, local demographic characteristics, and control variables for the seasonality. Many of these variables were scientifically generated by our research team. Various distance variables were constructed in a geographic information system environment based on public data and they are useful not only for exploring environmental impacts on housing prices, but also for other statistical analyses in regard to real estate and social science research. The four metropolitan areas covered by the data—Busan, Daegu, Daejeon, and Gwangju—are independent of the transit systems of Greater Seoul, providing accurate information on the metropolitan structure separate from the capital city.

The Typology will assist city government, local foundations and non-profits to understand local market strengths and to appropriately match neighborhood strategies to market conditions, for the best use of public and private resources. In addition, the typology will inform neighborhood level planning efforts and provide residents with an understanding of the local housing market conditions in their communities. Regional Choice: Competitive housing markets with high owner-occupancy rates and high property values in comparison to all other market types. Foreclosure, vacancy and abandonment rates are low. Middle Market Choice: Housing prices above the city’s average with strong ownership rates, and low vacancies, but with slightly increased foreclosure rates. Middle Market: Median sales values of $91,000 (above the City’s average of $65,000) as well as high homeownership rates. These markets experienced higher foreclosure rates when compared to higher value markets, with slight population loss. Middle Market Stressed: Slightly lower home sale values than the City’s average, and have not shown significant sales price appreciation. Vacancies and foreclosure rates are high, and the rate of population loss has increased in this market type, according to the 2010 Census data. Distressed Market: , Have experienced significant deterioration of the housing stock. This market category contains the highest vacancy rates and the lowest homeownership rates, compared to the other market types. It also has experienced some of the most substantial population losses in the City during the past decade.

There are a large number of Housing spreadsheets that provide the latest, most useful or most popular data, presented by type and other variables, including by geographical area or on a temporal basis. These spreadsheets are mostely produced from statistical returns completed by Local Authorities, although some are from survey data or external sources.

Median price paid for residential property in England and Wales, by property type and administrative geographies. Annual data.

Average house prices are derived from data supplied by the mortgage lending agencies on loans approved by them rather than loans paid. In comparing house prices figures from one period to another, account should be taken of the fact that changes in the mix of houses (incl apartments) will affect the average figures. The most current data is published on these sheets. Previously published data may be subject to revision. Any change from the originally published data will be highlighted by a comment on the cell in question. These comments will be maintained for at least a year after the date of the value change. Excluding apartments, measured in € Figure changed on the 27/6/16 as revised data received from the Local authority

The Typology will assist city government, local foundations and non-profits to understand local market strengths and to appropriately match neighborhood strategies to market conditions, for the best use of public and private resources. In addition, the typology will inform neighborhood level planning efforts and provide residents with an understanding of the local housing market conditions in their communities. Regional Choice: Competitive housing markets with high owner-occupancy rates and high property values in comparison to all other market types. Foreclosure, vacancy and abandonment rates are low. Middle Market Choice: Housing prices above the city��_��s average with strong ownership rates, and low vacancies, but with slightly increased foreclosure rates. Middle Market: Median sales values of $91,000 (above the City��_��s average of $65,000) as well as high homeownership rates. These markets experienced higher foreclosure rates when compared to higher value markets, with slight population loss. Middle Market Stressed: Slightly lower home sale values than the City��_��s average, and have not shown significant sales price appreciation. Vacancies and foreclosure rates are high, and the rate of population loss has increased in this market type, according to the 2010 Census data. Distressed Market: , Have experienced significant deterioration of the housing stock. This market category contains the highest vacancy rates and the lowest homeownership rates, compared to the other market types. It also has experienced some of the most substantial population losses in the City during the past decade.

Prior to 1974 the data was based on surveys of existing house sales in Dublin carried out by the Valuation Office on behalf of the D. O. E. Since 1974 the data has been based on information supplied by all lending agencies on the average price of mortgage financed existing house transactions. Average house prices are derived from data supplied by the mortgage lending agencies on loans approved by them rather than loans paid. In comparing house prices figures from one period to another, account should be taken of the fact that changes in the mix of houses (incl apartments) will affect the average figures. Data for 1969/1970 is not available for Cork, Limerick, Galway, Waterford and Other areas The most current data is published on these sheets. Previously published data may be subject to revision. Any change from the originally published data will be highlighted by a comment on the cell in question. These comments will be maintained for at least a year after the date of the value change. National and Other Areas figure changed for 2015 on 27/6/15 as revised data received from Local Authorities Prices includes houses and apartments measured in € .hidden { display: none }

Monthly new housing price index at the Canada level. The index is released on a monthly basis. (Index 2007=100) Includes the index from a year ago, the index from last period, the index from the current period, period to period percentage change and year to year percentage change.

Affordability ratios calculated by dividing house prices by gross annual residence-based earnings. Based on the median and lower quartiles of both house prices and earnings in England and Wales.

Average house prices are derived from data supplied by the mortgage lending agencies on loans approved by them rather than loans paid. In comparing house prices figures from one period to another, account should be taken of the fact that changes in the mix of houses (incl apartments) will affect the average figures. The most current data is published on these sheets. Previously published data may be subject to revision. Any change from the originally published data will be highlighted by a comment on the cell in question. These comments will be maintained for at least a year after the date of the value change. National and Other Areas figure changed for 2015Q4 on 27/6/15 as revised data received from Local Authorities (includes houses and apartments measured in €) .hidden { display: none }

Cleaned House Prices Dataset

This dataset contains information on residential properties, focusing on various features that influence house prices. Each row represents a unique property, with the following columns:

Summary

This cleaned dataset is intended for use in various analyses related to housing prices, such as regression modeling and feature importance evaluation. The data provides a comprehensive overview of different attributes that may affect the pricing of houses in a given area. It can be utilized for predictive modeling in real estate price prediction tasks.

Average house prices are derived from data supplied by the mortgage lending agencies on loans approved by them rather than loans paid. In comparing house prices figures The most current data is published on these sheets. Previously published data may be subject to revision. Any change from the originally published data will be highlighted by a comment on the cell in question. These comments will be maintained for at least a year after the date of the value change. Figure changed on the 27/6/16 as revised data received from the Local authority Prices include houses and apartments measured in €

Prior to 1974 the data was based on surveys of existing house sales in Dublin carried out by the Valuation Office on behalf of the D. O. E. Since 1974 the data has been based on information supplied by all lending agencies on the average price of mortgage financed existing house transactions. Average house prices are derived from data supplied by the mortgage lending agencies on loans approved by them rather than loans paid. In comparing house prices figures from one period to another, account should be taken of the fact that changes in the mix of houses (incl apartments) will affect the average figures. Data for 1969/1970 is not available for Cork, Limerick, Galway, Waterford and Other areas The most current data is published on these sheets. Previously published data may be subject to revision. Any change from the originally published data will be highlighted by a comment on the cell in question. These comments will be maintained for at least a year after the date of the value change. National and Other Areas figure changed for 2015 on 27/6/15 as revised data received from Local Authorities Prices includes houses and apartments measured in EUR