Price Index of Private Rents (PIPR) data chain-linked to Index of Private Housing Rental Prices. This is a historical series from January 2005 to February 2025.

Graph and download economic data for Consumer Price Index for All Urban Consumers: Rent of Primary Residence in U.S. City Average (CUUR0000SEHA) from Dec 1914 to Sep 2025 about primary, rent, urban, consumer, CPI, inflation, price index, indexes, price, and USA.

Price to Rent Ratio in the United States increased to 134.04 in the fourth quarter of 2024 from 133.46 in the third quarter of 2024. This dataset includes a chart with historical data for the United States Price to Rent Ratio.

Rent Inflation in the United States remained unchanged at 3.60 percent in September. This dataset includes a chart with historical data for the United States Rent Inflation.

Graph and download economic data for Consumer Price Index for All Urban Consumers: Rent of Primary Residence in Seattle-Tacoma-Bellevue WA (CBSA) (CUURA423SEHA) from Dec 1914 to Sep 2025 about Seattle, primary, rent, WA, urban, consumer, CPI, inflation, price index, indexes, price, and USA.

This dataset contains Real Estate Rents listings in the Canada broken by Province and City. Data was collected via web scraping using python libraries.

You may use the dataset for Canada rents houses trend analysis (with respect to the location - province/city/longitude/latitude), regression analysis (price prediction), correlation analysis, etc.,

Content

The dataset has 1 CSV file with 18 columns -

rentfaster.csv (25k+ entries)

-**'rentfaster_id'** - id of property on https://www.rentfaster.com . Can be explore with www.rentfaster.ca/rentfaster_id -**'city'** - city of property like 'Toronto', 'Calgary', 'Vancuver' and etc. -**'province'** - province of property like 'Alberta', 'Ontario' and etc. -**'address'** - address of property like '333 Seymour St' and etc -**'latitude'** - latitude coordinate of rental property -**'longitude'** - longitude coordinate of rental property -**'lease_term'** - category of rental period like 'Long Term', 'Negotiable' and etc -**'type'** - category of type a rental property like 'House', 'Apartment', 'Basement' and etc -**'price'** - price in CAD -**'beds'** - count of bedrooms -**'baths'** - count of bathrooms -**'sq_feet'** - area of rental property in square feets -**'link'** - right side of url for getting full details of the property rentfaster.com+'link' -**'furnishing'** - Furnished or not -**'availability_date'** - Date of availability -**'smoking'** - is allow smoke -**'cats'** - is allow cats -**'dogs'** - is allow dogs

The Price Index of Private Rents (PIPR) has shown significant growth, reaching a value of 117.9 in January 2025. This marks an increase of approximately 17.9 percent since January 2023, reflecting a robust upward trend in rental prices. Notably, the index saw a steady rise throughout 2024, with an annual percentage change peaking at 9.2 percent in March 2024. Mainstream properties are forecast to see rents further increase until 2028.

Rental price statistics historical data time series (indices and annual percentage change). These are official statistics in development.

Price to Rent Ratio in Norway increased to 119.06 in the third quarter of 2025 from 118.62 in the second quarter of 2025. This dataset includes a chart with historical data for Norway Price to Rent Ratio.

VITAL SIGNS INDICATOR List Rents (EC9)

FULL MEASURE NAME List Rents

LAST UPDATED October 2016

DESCRIPTION List rent refers to the advertised rents for available rental housing and serves as a measure of housing costs for new households moving into a neighborhood, city, county or region.

DATA SOURCE real Answers (1994 – 2015) no link

Zillow Metro Median Listing Price All Homes (2010-2016) http://www.zillow.com/research/data/

CONTACT INFORMATION vitalsigns.info@mtc.ca.gov

METHODOLOGY NOTES (across all datasets for this indicator) List rents data reflects median rent prices advertised for available apartments rather than median rent payments; more information is available in the indicator definition above. Regional and local geographies rely on data collected by real Answers, a research organization and database publisher specializing in the multifamily housing market. real Answers focuses on collecting longitudinal data for individual rental properties through quarterly surveys. For the Bay Area, their database is comprised of properties with 40 to 3,000+ housing units. Median list prices most likely have an upward bias due to the exclusion of smaller properties. The bias may be most extreme in geographies where large rental properties represent a small portion of the overall rental market. A map of the individual properties surveyed is included in the Local Focus section.

Individual properties surveyed provided lower- and upper-bound ranges for the various types of housing available (studio, 1 bedroom, 2 bedroom, etc.). Median lower- and upper-bound prices are determined across all housing types for the regional and county geographies. The median list price represented in Vital Signs is the average of the median lower- and upper-bound prices for the region and counties. Median upper-bound prices are determined across all housing types for the city geographies. The median list price represented in Vital Signs is the median upper-bound price for cities. For simplicity, only the mean list rent is displayed for the individual properties. The metro areas geography rely upon Zillow data, which is the median price for rentals listed through www.zillow.com during the month. Like the real Answers data, Zillow's median list prices most likely have an upward bias since small properties are underrepresented in Zillow's listings. The metro area data for the Bay Area cannot be compared to the regional Bay Area data. Due to afore mentioned data limitations, this data is suitable for analyzing the change in list rents over time but not necessarily comparisons of absolute list rents. Metro area boundaries reflects today’s metro area definitions by county for consistency, rather than historical metro area boundaries.

Due to the limited number of rental properties surveyed, city-level data is unavailable for Atherton, Belvedere, Brisbane, Calistoga, Clayton, Cloverdale, Cotati, Fairfax, Half Moon Bay, Healdsburg, Hillsborough, Los Altos Hills, Monte Sereno, Moranga, Oakley, Orinda, Portola Valley, Rio Vista, Ross, San Anselmo, San Carlos, Saratoga, Sebastopol, Windsor, Woodside, and Yountville.

Inflation-adjusted data are presented to illustrate how rents have grown relative to overall price increases; that said, the use of the Consumer Price Index does create some challenges given the fact that housing represents a major chunk of consumer goods bundle used to calculate CPI. This reflects a methodological tradeoff between precision and accuracy and is a common concern when working with any commodity that is a major component of CPI itself. Percent change in inflation-adjusted median is calculated with respect to the median price from the fourth quarter or December of the base year.

Price to Rent Ratio in Switzerland increased to 128.02 in the second quarter of 2025 from 126.84 in the first quarter of 2025. This dataset includes a chart with historical data for Switzerland Price to Rent Ratio.

The median monthly rent for all apartment types in the U.S. has stabilized since 2022, despite some seasonal fluctuations. In August 2025, the monthly rent for a two-bedroom apartment amounted to ***** U.S. dollars. That was an increase from ***** U.S. dollars in January 2021, but a decline from the peak value of ***** U.S. dollars in August 2022. Where are the most expensive apartments in the U.S.? Apartment rents vary widely from state to state. To afford a two-bedroom apartment in California, for example, a renter needed to earn an average hourly wage of nearly ** U.S. dollars. This was approximately double the average wage in North Carolina and three times as much as the average wage in Arkansas. In fact, rental costs were considerably higher than the hourly minimum wage in all U.S. states. How did rents change in different states in the U.S.? In 2025, some of the most expensive states to rent an apartment only saw a moderate increase in rental prices. Nevertheless, rents increased in most states as of August 2025. In West Virginia, the annual rental growth was the highest, at ***** percent.

The rent price index in Australia in the first quarter of 2025 was *****, marking an increase from the same quarter of the previous year. Rent prices had decreased in 2020; in Melbourne and Sydney, this was mainly attributed to the absence of international students during the coronavirus outbreak. The current state of the rental market in Australia The rental market in Australia has been marked by varying conditions across different regions. Among the capital cities, Sydney has long been recognized for having some of the highest average rents. As of March 2025, the average weekly rent for a house in Sydney was *** Australian dollars, which was the highest average rent across all major cities in Australia that year. Furthermore, due to factors like population growth and housing demand, regional areas have also seen noticeable increases in rental prices. For instance, households in the non-metropolitan area of New South Wales’ expenditure on rent was around ** percent of their household income in the year ending June 2024. Housing affordability in Australia Housing affordability remains a significant challenge in Australia, contributing to a trend where many individuals and families rent for prolonged periods. The underlying cause of this issue is the ongoing disparity between household wages and housing costs, especially in large cities. While renting offers several advantages, it is worth noting that the associated costs may not always align with the expectation of affordability. Approximately one-third of participants in a recent survey stated that they pay between ** and ** percent of their monthly income on rent. Recent government initiatives, such as the 2024 Help to Buy scheme, aim to make it easier for people across Australia to get onto the property ladder. Still, the multifaceted nature of Australia’s housing affordability problem requires continued efforts to strike a balance between market dynamics and the need for accessible housing options for Australians.

Rent prices per square meter in the largest Dutch cities have been on an upward trend after a slight decline in 2020. Amsterdam remained the most expensive city to live in, averaging a monthly rent of 27.6 euros per square meter for residential real estate in the private rental sector. Monthly rents in Utrecht were around six euros cheaper per square meter. Both cities were above the average rent price of residential property in the Netherlands overall, whereas Rotterdam and The Hague were slightly below that. Buying versus renting, what do the Dutch prefer? The Netherlands is one of Europe’s leading countries when it comes to homeownership, having funded this with a mortgage. In 2023, around 60 percent of people living in the Netherlands were homeowners with a mortgage. This is because Dutch homeowners were able to for many years to deduct interest paid from pre-tax income (a system known in the Netherlands as hypotheekrenteaftrek). This resulted in the Netherlands having one of the largest mortgage debts across the European continent. Total mortgage debt of Dutch households reached a value of approximately 803 billion euros in 2023. Is the Dutch housing market overheating? There are several indicators for the Netherlands that allow to investigate whether the housing market is overheating or not. House price indices corrected for inflation in the Netherlands suggest, for example, that prices have declined since 2022. The Netherlands’ house-price-to-rent-ratio, on the other hand, has exceeded the pre-crisis level in 2019. These figures, however, are believed to be significantly higher for cities like Amsterdam, as it was suggested for a long time that the prices of owner-occupied houses were increasing faster than rents in the private rental sector.

This dataset provides monthly rental price statistics for apartments across urban neighborhoods, including average, median, minimum, and maximum rents by apartment type and location. It enables detailed market trend analysis, investment strategy development, and urban planning by offering granular insights into rental dynamics over time. The dataset is ideal for real estate professionals, investors, and researchers seeking to understand rental market fluctuations.

Rent prices in Berlin increased much less than consumer prices between 2018 and 2025. Between 2020, when the value for both indices was set at 100, and June 2025, consumer prices rose by 21.3 percent. In contrast, net rents without heating costs rose by over nine percent during that period.

This table contains data described by the following dimensions (Not all combinations are available): Geography (247 items: Carbonear; Newfoundland and Labrador; Corner Brook; Newfoundland and Labrador; Grand Falls-Windsor; Newfoundland and Labrador; Gander; Newfoundland and Labrador ...), Type of structure (4 items: Apartment structures of three units and over; Apartment structures of six units and over; Row and apartment structures of three units and over; Row structures of three units and over ...), Type of unit (4 items: Two bedroom units; Three bedroom units; One bedroom units; Bachelor units ...).

Context

This dataset contains information on rent pricing surrounding Kuala Lumpur and Selangor region, Malaysia. The information was scraped from mudah.my

Content

There are 13 features with one unique ids (ads_id) and one target feature (monthly_rent)

• ads_id: the listing ids (unique)
• prop_name: name of the building/ property
• completion_year: completion/ established year of the property
• monthly_rent: monthly rent in ringgit malaysia (RM)
• location: property location in Kuala Lumpur region
• property_type:property type such as apartment, condominium, flat, duplex, studio, etc
• rooms: number of rooms in the unit
• parking: number of parking space for the unit
• bathroom: number of bathrooms in the unit
• size: total area of the unit in square feet
• furnished: furnishing status of the unit (fully, partial, non-furnished)
• facilities: main facilities available
• additional_facilities: additional facilities (proximity to attraction area, mall, school, shopping, railways, etc)

Acknowledgements The data was scraped from mudah.my

Inspiration I have been living in Kuala Lumpur, Malaysia since 2017, and in the past there was no easy way to understand whether certain unit pricing is making sense or not. With this dataset, I wanted to be able to answer the following questions:

• What are the biggest factor affecting the unit/rent pricing?
• Which location in Kuala Lumpur/ Selangor region that has the highest rent price? etc?

View monthly updates and historical trends for US Consumer Price Index: Rent Of Primary Residence. from United States. Source: Bureau of Labor Statistics.…

Georeferenced Amsterdam Rental Values

Exploring Urban Housing Markets Through Historical Patterns

By [source]

About this dataset

This dataset provides insightful and comprehensive information on the spatial distribution of rental values in Amsterdam throughout a period of time. In order to generate this data, the Verponding registration from Amsterdam City Archives was consulted, which collected a tax known as the Verpondings-quohieren van den 8sten penning on the rental value of immovable property. This data was attained through transcribing and geo-referencing registration books from the archives; thereby incorporating both transcribed rental values of all real estate properties listed therein as well as geo-referenced tax records plotted onto an historical map of Amsterdam.

The compilation and analysis of historic rental values may offer further insights into underlying social, economic, and cultural developments within Amsterdam over time. Therefore, the potential applications for this dataset are enormous; offering investigators an opportunity to gather useful information with relation to urban renewal efforts or even supporting archaeological research studies. Moreover, with various columns such as order number, wijk district where applicable property is located within respective street name as well as details on whether said property is available for rent/own disposition - researchers may also utilize these collected metrics for meaningful planning/management decisions simultaneously unfolding hidden patterns concerning disparities or trends that might be discerned when compared to current trends employed by residents today

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How to use the dataset

This dataset provides insight into the spatial distribution of rental values in Amsterdam between 1647 and 1652. The data provided is a valuable resource for researchers looking to study the economic, social, and cultural history of Amsterdam over this period in time. With this data set, users can explore hidden patterns, disparities, and trends that may inform decision-making or help with urban renewal projects. Moreover, this dataset can also be used to assess archaeological and cultural heritage research.

In order to understand the georeferenced rental values better and draw meaningful conclusions from the data set it is important to keep few things in mind: - Check out handy columns such as ‘wijk’ (district) which offers information about where each property is located;
- The ‘rent/own’ indicates whether a property was rented (huur) or owned (koop);
- The ‘value’ column contains information regarding the rental value of each property; - The ‘tax’ column shows how much tax was paid on each listed property;
- In addition to this additional notes have been provided in some cases offering more insights into particular properties;

By seeing all these details together one will get an excellent overview of individual households renting or owning their real estate properties along with their tax payment throughout Amsterdam during this period 1647-1652. Additionally by graphing this data one could compare rental value against geographic location or even track consecutive years on how they vary year after year! This can help trace any historical changes taking place how they affect individual households within Amsterdam as well as socio-economic changes occurring throughout the city over the years!

Research Ideas

• Creating a predictive heat map by analyzing correlation between rental values and various other factors such as geographic location, proximity to public transportation, availability of amenities/services etc.
• Comparing and contrasting current maps of real estate prices in Amsterdam with the maps from this dataset to analyze shifts in property prices over time and understand the evolution of urban housing markets in the city.
• Studying socio-economic differences between different geographical areas based on rental values from this dataset, which could help provide a better understanding of the social, economic, and cultural history of the city

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

License: CC0 1.0 Universal (CC0 1.0) - Public Domain Dedication No Copyright - You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permi...