This dataset is no longer being updated due to redevelopment of private rental prices statistics, impact analysis, UK, please see more information here: Redevelopment of private rental prices statistics, impact analysis, UK - Office for National Statistics (ons.gov.uk). The Index of Private Housing Rental Prices (IPHRP) is a quarterly experimental price index. It tracks the prices paid for renting property from private landlords in Great Britain. IPHRP is produced from a number of administrative sources and is classified as experimental by ONS. The index compares trends (rather than levels) in average private sector rents across English regions, Wales and Scotland. It uses a complex mix-adjustment and weighting process to produce a single index for each area. This index uses data on actual new and ongoing rents. The sample ensures that the index is representative of the stock at regional level and that it isn't distorted by units dropping out of the sample because they switch to LHA or for other reasons. This is an advantage over the VOA dataset where the sample is changing over time and may not be representative. Tables show monthly data. Data is updated once a quarter. Index level (January 2011 = 100). Not seasonally adjusted. See more on the ONS Website

Median monthly rental prices for the private rental market in England by bedroom category, region and administrative area, calculated using data from the Valuation Office Agency and Office for National Statistics.

This dataset is no longer being updated due to redevelopment of private rental prices statistics, impact analysis, UK, please see more information here: Redevelopment of private rental prices statistics, impact analysis, UK - Office for National Statistics (ons.gov.uk).

The Index of Private Housing Rental Prices (IPHRP) is a quarterly experimental price index. It tracks the prices paid for renting property from private landlords in Great Britain.

IPHRP is produced from a number of administrative sources and is classified as experimental by ONS.

The index compares trends (rather than levels) in average private sector rents across English regions, Wales and Scotland. It uses a complex mix-adjustment and weighting process to produce a single index for each area. This index uses data on actual new and ongoing rents.

The sample ensures that the index is representative of the stock at regional level and that it isn't distorted by units dropping out of the sample because they switch to LHA or for other reasons. This is an advantage over the VOA dataset where the sample is changing over time and may not be representative.

Tables show monthly data. Data is updated once a quarter.

Index level (January 2011 = 100). Not seasonally adjusted.

See more on the ONS Website

An experimental price index tracking the prices paid for renting property from private landlords in the United Kingdom

The data was scraped from the Magicbricks website. The following are the details of the dataset:

• Title: The title of the property listing.
• Price: The monthly rent of the property.
• Area: The total area of the property in square feet.
• BHK: The number of bedrooms in the property.
• Bathrooms: The number of bathrooms on the property.
• Furnished: Whether the property is furnished or not.
• Balconies: The number of balconies in the property.
• Floor: The floor number of the property.
• Ownership: The type of ownership of the property (i.e., freehold, leasehold, etc.).
• Facing: The direction the property faces.
• Amenities: The amenities that are available in the property or the surrounding area.
• Transaction Type: Whether the property is for sale or rent.
• Property Type: The type of property (i.e., apartment, house, villa, etc.).
• Location: The location of the property.
• Year of Construction: The year the property was built.
• Is Luxury: Whether the property is considered to be a luxury property.
• Description: A brief description of the property.
• Property Image: A link to the property image.

Key points in the dataset are :

1) This dataset can be used to gain insights into the rental market in Mumbai. For example, you could use the data to analyze the average rent for different types of properties, the most popular neighborhoods for renters, or the factors that affect the price of rent. You could also use the data to identify trends in the rental market, such as the increasing popularity of furnished apartments or the rising prices of luxury properties.

2) The dataset could also be used by real estate agents to help their clients find rental properties that meet their needs and budget. Additionally, the data could be used by developers to make informed decisions about the types of properties to build in Mumbai.

3) Overall, this dataset is a valuable resource for anyone who is interested in the rental market in Mumbai. It can be used to gain insights into the market, identify trends, and make informed decisions.

(Disclaimer: The data in this dataset has been gathered from publicly available sources. While the data is believed to be reliable and all privacy policies have been observed, No personal information such as email addresses, mobile numbers, or physical addresses hasn't been collected. I scrape data from the website Magicbricks to study the real estate market of Mumbai. ) Thank you !!!

Summary of average monthly rents in private rental market, recorded per 12 month rolling period. Data updated bi-annually by local authority areas for England. These statistics used to be produced quarterly but since 2013 have been updated bi-annually in Q1 and Q3 only. VOA note on these statistics: "The sample used to produce these statistics is not statistical and may not be consistent over time as such these data should not be compared across time periods or between areas." This table only reflects the data available from the VOA and does not indicate level of statistical significance of the differences between areas or changes over time. The release presents the mean (average), median, lower quartile, and upper quartile gross monthly rent paid (ignoring any adjustment for services not eligible for housing benefit), for a number of bedroom/room categories for each Local Authority (LA) in England for the 12 month period stated. Full set of local authority tables available on the VOA website.

Quarterly summary of median private rent in South Australia by: suburb, postcode, State Government regions and Local Government Areas. The information relates to bonds lodged with Consumer and Business Services for private rental properties in South Australia.

Percentage of total monthly household income spent on private rent for England, Wales and Northern Ireland, and by regions of England, financial years ending 2016 to 2024.

Amount charged by Registered Social Landlord (Private Registered Provider (PRP)) Average Weekly Rents for social housing. Data is collected by the Housing Corporation via the annual Regulatory and Statistical Return (RSR) based on general needs stock only. Figures are based on only the larger Registered Social Landlords (RSLs) completing the long form. Upto 2006 the threshold for completing the long form was that the RSL owned/ managed at least 250 units/bedspaces. From 2007 this increased to 1,000 units/bedspaces. The districts, unitary authorities and counties listed above are based on 1 April 1998 boundaries. Figures for any 'new' re-organised areas have been estimated retrospectively applying the new boundaries back to 1997 and making appropriate assumptions. Note that the average RSL rents within a local authority area can move down from one year to the next. This is especially true if, during the latest year, most of the LA stock has been transferred through a large-scale voluntary transfer to the RSL sector. Larger housing associations report the rent they charge in the HCA’s Statistical Data Return. Data in spreadsheet includes average weekly rents for housing association general needs properties by number of bedrooms, in London by borough (stock owned by larger associations only).

Since passage of the U.S. Housing Act of 1937, the federal government has provided housing assistance to low-income renters. Most of these housing subsidies were provided under programs administered by the U.S. Department of Housing and Urban Development (HUD) or predecessor agencies. All programs covered in this report provide subsidies that reduce rents for low-income tenants who meet program eligibility requirements. Generally, households pay rent equal to 30 percent of their incomes, after deductions, while the federal government pays the remainder of rent or rental costs. To qualify for a subsidy, an applicant’s income must initially fall below a certain income limit. These income limits are HUD-determined, location specific, and vary by household size. Applicants for housing assistance are usually placed on a waiting list until a subsidized unit becomes available.Assistance provided under HUD programs falls into three categories: public housing, tenant-based, and privately owned, project-based.In public housing, local housing agencies receive allocations of HUD funding to build, operate or make improvements to housing. The housing is owned by the local agencies. Public housing is a form of project-based subsidy because households may receive assistance only if they agree to live at a particular public housing project.Currently, tenant based assistance is the most prevalent form of housing assistance provided. Historically, tenant based assistance began with the Section 8 certificate and voucher programs, which were created in 1974 and 1983, respectively. These programs were replaced by the Housing Choice Voucher program, under legislation enacted in 1998. Tenant based programs allow participants to find and lease housing in the private market. Local public housing agencies (PHAs) and some state agencies serving as PHAs enter into contracts with HUD to administer the programs. The PHAs then enter into contracts with private landlords. The housing must meet housing quality standards and other program requirements. The subsidies are used to supplement the rent paid by low-income households. Under tenant-based programs, assisted households may move and take their subsidy with them. The primary difference between certificates and vouchers is that under certificates, there was a maximum rent which the unit may not exceed. By contrast, vouchers have no specific maximum rent; the low-income household must pay any excess over the payment standard, an amount that is determined locally and that is based on the Fair Market Rent. HUD calculates the Fair Market Rent based on the 40th percentile of the gross rents paid by recent movers for non-luxury units meeting certain quality standards.The third major type of HUD rental assistance is a collection of programs generally referred to as multifamily assisted, or, privately-owned, project-based housing. These types of housing assistance fall under a collection of programs created during the last four decades. What these programs have in common is that they provide rental housing that is owned by private landlords who enter into contracts with HUD in order to receive housing subsidies. The subsidies pay the difference between tenant rent and total rental costs. The subsidy arrangement is termed project-based because the assisted household may not take the subsidy and move to another location. The single largest project-based program was the Section 8 program, which was created in 1974. This program allowed for new construction and substantial rehabilitation that was delivered through a wide variety of financing mechanisms. An important variant of project-based Section 8 was the Loan Management Set Aside (LMSA) program, which was provided in projects financed under Federal Housing Administration (FHA) programs that were not originally intended to provide deep subsidy rental assistance. Projects receiving these LMSA “piggyback” subsidies were developed under the Section 236 program, the Section 221(d)(3) Below Market Interest Rate (BMIR) program, and others that were unassisted when originally developed.Picture of Subsidized Households does not cover other housing

The CORE datasets contained in the study cover annual official statistics on new lettings of the stock owned by local authorities and private registered providers of social housing in England, as well as sales of the social stock owned by private registered providers. For each year, data is structured into five datasets, four based on type of letting (social rent general needs and supported needs, and affordable rent general needs and supported needs) and one based on sales by private registered providers. All datasets are based on administrative data collected via the COntinuous REcording of Lettings and Sales (CORE) system. It is a regulatory requirement for providers registered with the Homes and Communities Agency to supply the data. For those who are not registered, submissions are voluntary. Local authorities have participated in CORE since 2004-5 on a voluntary basis. In the first year, only 24% of stock-holding local authorities participated, but the number of authorities participating has steadily increased, with all authorities submitting some data for 2013-14. Weighting is applied to adjust for non-response by local authorities for social rent datasets and imputation is also carried out to address item level non-response of key data on tenant characteristic, for both local authorities and private registered providers. The three datasets for affordable rent and sales are not weighted. The sales dataset has imputation which is outlined in the data dictionary

The collection of social housing lettings and sales data allows for a better understanding of the socio-economic and demographic make-up of affordable housing customers by tenure and of local housing markets and affordable housing products. These data are used by central government to inform national housing policy and by local government to inform their Strategic Housing Market Assessments. The data are also used by academics, researchers, charities and the wider public to understand social housing issues.

Further information may be found on the GOV.UK "https://www.gov.uk/government/collections/rents-lettings-and-tenancies" title="Social housing lettings"> Social housing lettings and "https://www.gov.uk/government/collections/social-housing-sales-including-right-to-buy-and-transfers" title="Social housing sales"> Social housing sales webpages.

End User Licence, Special Licence and Secure Access datasets
The CORE datasets are available at three access levels, depending on the level of detail in the data.

• For the standard End User Licence (EUL) version (SN 7603) the geographic level of the data is set at Government Office Region (GOR). Letting and voiding dates are provided at month and year only; age variables are top-coded at 90 years; income, benefits, earnings, charge and shortfall variables are banded to disguise unique values; landlords are grouped into coded categories.
• For the Special Licence access (SL) version (SN 7604), the geographic level is set at Local Authority. The SL data have more restrictive access conditions than those made available under the standard EUL. Prospective users of the SL version will need to complete an extra application form and demonstrate to the data owners exactly why they need access to the additional variables in order to get permission to use that version.
• For Secure Access (this study, SN 7686) the full CORE datasets are available, with some key variables recoded. Prospective users of the Secure Access version will need to fulfil additional requirements, including completion of face-to-face training and agreement to further stringent access conditions.

Latest edition
For the ninth edition (August 2023), data and documentation for CORE Lettings for 2018/19-2021/22 have been added to the study. Sales data and documentation for 2018/19-2020/21 have been replaced, and 2021/22 added.

A more recent version of these indicators can be found on this page: https://www.data.gouv.fr/fr/datasets/carte-des-loyers-indicateurs-de-loyers-dannonce-par-commune-en-2022/ Due to the evolution of the methodology and the communal mesh size, successive versions of the indicators cannot be compared to provide information on the evolution of rents. ### Context of the project Knowledge of the level of rents is important to ensure the proper functioning of the rental market and the conduct of national and local housing policies. The Directorate-General for Planning, Housing and Nature (DGALN) launched in 2018 the “rent map” project by partnering on the one hand with a research team in economics of Agrosup Dijon and the National Institute of Research in Agronomics (INRAE), and on the other hand with SeLoger, leboncoin and PAP. This innovative partnership has rebuilt a database with more than 9 million rental ads. On the basis of these data, the research team developed a methodology for estimating indicators, at the communal scale, of rent (including charges) per m² for apartments and houses. These experimental indicators are put online in order to be usable by all: state services, local authorities, real estate professionals, private donors and tenants. In a second phase of the project, the methodology will need to be consolidated and sustained, in order to provide for a regular update of these indicators. This project provides additional information to that offered by the Local Land Observatorys (OLL), deployed since 2013 and reinforced since 2018 by the Elan law. Today, this associative network of 30 OLL publishes every year precise information on the rents practiced in 51 of the main French agglomerations. ### Presentation of the dataset The data disseminated are indicators of ad rents, at the level of the municipality. The field covered is the whole of France, outside of Mayotte. The geography of the municipalities is the one in force on 1 January 2017. Rent indicators are calculated using ad data published on leboncoin, SeLoger and PAP over the period 2015-2019. Rent indicators are provided including charges for standard properties leased in the 3 rd quarter of 2018 with the following reference characteristics: — For an apartment: 49 m² and average area per room of 22.1 m² — For a house: 92 m² area and average area per room of 22.5 m² ### Data terms and conditions These indicators can be freely used, provided that the source is indicated as follows: “UMR 1041 CESAER estimates (AgroSup Dijon-INRAE) from SeLoger, leboncoin, PAP”. ### Precautions for use Rent indicators are calculated including charges, on ad data, so measure flow rents only. The data were duplicated but could not rely on very discriminating photos and characteristics. For municipalities with no housing leased through an advertisement on at least one of the three sites during the period considered, the rent indicator is that estimated for a larger grid comprising neighbouring municipalities with similar characteristics. Moreover, since the data do not make it possible to distinguish with certainty furnished and tourist rentals, biases in the rent indicators can be observed locally. Users are advised to consider rent indicators with caution in municipalities where the coefficient of determination (R2) is less than 0.5, the number of observations in the municipality is less than 30 or the prediction interval is very wide.

Rent Affordability: Average monthly private rent as a percentage of median monthly salary - (2 bedroom properties) *This indicator has been discontinued

The dataset is a catalog of major residential development projects in Somerset County, NJ. This includes Affordable Housing, Senior housing options, and Market-rate rentalsAffordable Housing Options: With New Jersey having some of the highest housing costs in the county, the state government has implemented several initiatives and programs to provide housing options for low- and moderate-income eligible households. In addition, several municipalities have implemented inclusionary zoning laws, that require property developers to allocate a certain percentage of the units for affordable housing. Somerset county has several affordable housing programs to help low-and moderate-income eligible households and first-time homebuyers, including the Mt. Laurel Doctrine, New Jersey Balanced Housing Program, HUD Public Housing Program, HUD Housing Choice Voucher Program (Section 8). This dataset provides a comprehensive list of all affordable housing projects in the county. The dataset includes ‘inclusionary’ developments that are comprised of both market-rate units and affordable units. It also includes municipality-sponsored and other 100% affordable housing projects, as well as affordable housing created through the redevelopment process. The total number of market rate and affordable housing units in each project is provided. Some projects include a blend of both rental and for-purchase units. Senior Housing Options: There are several housing options in Somerset County for older adults seeking assistance with daily living or those who want to maintain their independence or those who seek to live in communities designed for older adults. These options include – Active Adult Communities: These are communities designed for older adults who can live independently but want to live in a community specifically for older adults. They typically offer amenities such as fitness centers, swimming pools, and social activities. Many independent living communities also offer additional services such as transportation, housekeeping, and meals. Assisted Living Communities: These communities aid with daily living activities such as bathing, dressing, and medication management. They offer a range of services, depending on the level of care needed. Some assisted living communities also offer memory care services for individuals with dementia or Alzheimer's disease. Continuing Care Retirement Communities: These communities offer a continuum of care that includes independent living, assisted living, and skilled nursing care. This allows residents to "age in place" and receive additional care as needed without having to move to a different community. Senior Residence: These communities are restricted to residents who are 55 years of age or older. They typically offer amenities like active adult communities and may have additional features such as golf courses, community centers, and events. Market Rate Rentals: These properties are typically owned/operated by private landlords and are not considered affordable housing and are not subject to government subsidies. These include apartments, condominiums, town homes, single-family homes. The information included in this dataset represents a point-in-time (November 2023) and is subject to change. Furthermore, new, or alternative housing projects may be proposed in future years, which will be incorporated into subsequent dataset updates. Updates to this dataset will take place on an as-needed basis.

The English Housing Survey (EHS) is a continuous national survey commissioned by the Ministry of Housing, Community and Local Government (MHCLG) that collects information about people's housing circumstances and the condition and energy efficiency of housing in England. The EHS brings together two previous survey series into a single fieldwork operation: the English House Condition Survey (EHCS) (available from the UK Data Archive under GN 33158) and the Survey of English Housing (SEH) (available under GN 33277). The EHS covers all housing tenures. The information obtained through the survey provides an accurate picture of people living in the dwelling, and their views on housing and their neighbourhoods. The survey is also used to inform the development and monitoring of the Ministry's housing policies. Results from the survey are also used by a wide range of other users including other government departments, local authorities, housing associations, landlords, academics, construction industry professionals, consultants, and the general public.

The EHS has a complex multi-stage methodology consisting of two main elements; an initial interview survey of around 12,000 households and a follow-up physical inspection. Some further elements are also periodically included in or derived from the EHS: for 2008 and 2009, a desk-based market valuation was conducted of a sub-sample of 8,000 dwellings (including vacant ones), but this was not carried out from 2010 onwards. A periodic follow-up survey of private landlords and agents (the Private Landlords Survey (PLS)) is conducted using information from the EHS interview survey. Fuel Poverty datasets are also available from 2003, created by the Department for Energy and Climate Change (DECC).

The EHS interview survey sample formed part of the Integrated Household Survey (IHS) (available from the Archive under GN 33420) from April 2008 to April 2011. During this period the core questions from the IHS formed part of the EHS questionnaire.

Safeguarded and Special Licence Versions:
From 2014 data onwards, the Safeguarded versions (previously known as End User Licence (EUL)) of the EHS will only include derived variables. In addition the number of variables on the new EUL datasets has been reduced and disclosure control increased on certain remaining variables. New Special Licence versions of the EHS will be deposited later in the year, which will be of a similar nature to previous EHS EUL datasets and will include derived and raw datasets.

Further information about the EHS and the latest news, reports and tables can be found on the GOV.UK English Housing Survey web pages.

The Private Landlords Survey, 2010 (PLS), commissioned by the DCLG and carried out by ONS, was a national survey of landlords and managing agents who own and/or manage privately rented properties in England. The aim of the survey was to provide a snapshot of the composition and experience of landlords and how they (together with any agent) acquire, let, manage and maintain privately rented accommodation. A similar survey of private landlords was carried out by the DCLG (or predecessors) in the years 2001, 2003 and 2006 (only the 2010 survey is currently held at the UK Data Archive). As with previous years, the 2010 survey was based on information collated on DCLG's main housing survey. Respondents taking part in the ECHS 2007-2008 (see under SN 6449) and the EHS 2008-2009 (see under SN 7040) who were recorded as private renters were asked to provide details of their landlord. These details formed the main sample for the 2010 PLS.

The Rental Report time series dataset provides detailed time-series statistics for some key Rental Report data from the June quarter of 1999 to the December quarter of 2017. This specific dataset presents the median rental costs of 2 bedroom flats by the 2016 Local Government Areas geographic level. The rent figures included in the Rental Report are weekly median rents. Median rents represent the midpoint in the distribution of all rents. Fifty per cent of rents are higher than the median and fifty per cent are below the median. The Rental Report provides the most accurate information on the private rental market in Victoria. The data come from records kept by the Residential Tenancies Bond Authority (RTBA). The RTBA is responsible for receiving, registering and refunding all bonds associated with private residential leases in Victoria. For more information please visit the Department of Health and Human Services.

LGA based data for Rent (Weekly) by Landlord Type, in General Community Profile (GCP), 2016 Census. Count of occupied private dwellings being rented. Includes dwellings being occupied rent-free. Excludes 'Visitors only' and 'Other non-classifiable' households. The data is by LGA 2016 boundaries. Periodicity: 5-Yearly. Note: There are small random adjustments made to all cell values to protect the confidentiality of data. These adjustments may cause the sum of rows or columns to differ by small amounts from table totals. For more information visit the data source: http://www.abs.gov.au/census.

LGA based data for Rent (Weekly) by Landlord Type, in Place of Enumeration Profile (PEP), 2016 Census. Count of occupied private dwellings being rented. Includes dwellings being occupied rent-free. The data is by LGA 2016 boundaries. Periodicity: 5-Yearly. Note: There are small random adjustments made to all cell values to protect the confidentiality of data. These adjustments may cause the sum of rows or columns to differ by small amounts from table totals. For more information visit the data source: http://www.abs.gov.au/census.