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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 May 2025 about primary, rent, urban, consumer, CPI, inflation, price index, indexes, price, and USA.
Mexico was one of the economies where house prices increased the most between 2016 and 2024, rising by nearly ** percent during that period. The growth rate of housing prices from 2015 to 2023 in Russia was even higher, but the 2024 data for that country was not yet available. Meanwhile, Poland and the U.S. were among the countries where rents increased the most from 2016 to 2024.
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.
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South Korea Rent Price Index: sa data was reported at 108.443 2015=100 in 2024. This records an increase from the previous number of 108.179 2015=100 for 2023. South Korea Rent Price Index: sa data is updated yearly, averaging 79.293 2015=100 from Dec 1985 (Median) to 2024, with 40 observations. The data reached an all-time high of 108.443 2015=100 in 2024 and a record low of 36.533 2015=100 in 1985. South Korea Rent Price Index: sa data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s South Korea – Table KR.OECD.AHPI: House Price Index: Seasonally Adjusted: OECD Member: Annual.
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Germany DE: Rent Price Index: sa data was reported at 115.012 2015=100 in 2024. This records an increase from the previous number of 112.600 2015=100 for 2023. Germany DE: Rent Price Index: sa data is updated yearly, averaging 63.513 2015=100 from Dec 1960 (Median) to 2024, with 65 observations. The data reached an all-time high of 115.012 2015=100 in 2024 and a record low of 13.547 2015=100 in 1960. Germany DE: Rent Price Index: sa data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Germany – Table DE.OECD.AHPI: House Price Index: Seasonally Adjusted: OECD Member: Annual.
In 2024, the rental index in Germany reached 107.5 index points. The index was set to 100 in 2020, which means that compared to then, rent in Germany increased by 7.5 percent. Munich saw the highest average rent price among the larger German cities.
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Rent Inflation in the United States decreased to 3.90 percent in May from 4 percent in April of 2025. This dataset includes a chart with historical data for the United States Rent Inflation.
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Austria AT: Rent Price Index: sa data was reported at 144.877 2015=100 in Mar 2025. This records an increase from the previous number of 143.430 2015=100 for Dec 2024. Austria AT: Rent Price Index: sa data is updated quarterly, averaging 52.859 2015=100 from Mar 1966 (Median) to Mar 2025, with 237 observations. The data reached an all-time high of 144.877 2015=100 in Mar 2025 and a record low of 6.464 2015=100 in Mar 1966. Austria AT: Rent Price Index: sa data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Austria – Table AT.OECD.AHPI: House Price Index: Seasonally Adjusted: OECD Member: Quarterly.
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Graph and download economic data for Consumer Price Index: OECD Groups: Services Less Housing: Housing Excluding Imputed Rentals for Housing for Estonia (ESTCPGRLH02GPQ) from Q2 1998 to Q4 2023 about imputed, Estonia, rent, services, CPI, price index, indexes, and price.
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Sweden SE: Rent Price Index: sa data was reported at 119.105 2015=100 in 2024. This records an increase from the previous number of 113.178 2015=100 for 2023. Sweden SE: Rent Price Index: sa data is updated yearly, averaging 63.966 2015=100 from Dec 1963 (Median) to 2024, with 62 observations. The data reached an all-time high of 119.105 2015=100 in 2024 and a record low of 4.616 2015=100 in 1963. Sweden SE: Rent Price Index: sa data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Sweden – Table SE.OECD.AHPI: House Price Index: Seasonally Adjusted: OECD Member: Annual.
According to our latest research, the global AI-Powered Rental Price Index market size reached USD 1.84 billion in 2024, with a robust compound annual growth rate (CAGR) of 17.2% projected through the forecast period. By 2033, the market is anticipated to achieve a value of USD 8.19 billion, driven by increasing demand for data-driven pricing strategies, rapid digital transformation in real estate, and the growing adoption of artificial intelligence across property valuation and management. As per our comprehensive analysis, the market is witnessing exponential growth due to the need for accurate, real-time rental price insights, supporting both property owners and tenants in making informed decisions.
One of the primary growth factors fueling the AI-Powered Rental Price Index market is the escalating need for transparency and precision in rental pricing, especially in highly dynamic urban real estate environments. Traditional pricing methodologies often fall short in accounting for rapidly shifting market variables, such as sudden changes in demand, local economic trends, or emerging neighborhood developments. AI-powered solutions leverage advanced algorithms and machine learning models to process vast datasets, including historical rental prices, property attributes, neighborhood analytics, and even social sentiment. This enables real estate stakeholders to arrive at more accurate and competitive rental prices, minimizing vacancies and maximizing returns. Further, the integration of AI with Internet of Things (IoT) and smart city initiatives is enhancing the granularity and timeliness of rental data, solidifying the value proposition of AI-powered rental indices.
Another significant growth driver is the increasing adoption of digital platforms by real estate agencies, property managers, and institutional investors. The transformation from manual, spreadsheet-based assessments to automated, AI-driven platforms is streamlining operations, reducing human error, and enabling scalable portfolio management. Financial institutions are also leveraging AI-powered rental indices for risk assessment, loan underwriting, and investment analysis, further expanding the addressable market. Additionally, the proliferation of proptech startups and increased venture capital investments in real estate technology are accelerating the innovation cycle, resulting in more sophisticated and customizable AI-powered pricing solutions. The rising consumer expectation for transparency and fairness in rental pricing, particularly among younger, tech-savvy renters, is further catalyzing market growth.
Furthermore, regulatory developments and government initiatives aimed at improving housing affordability and market efficiency are positively impacting the AI-Powered Rental Price Index market. In many regions, public sector agencies are collaborating with technology providers to develop standardized rental indices, which support policy-making, rent control measures, and urban planning. These collaborations are fostering an environment where AI-powered analytics are not only a competitive advantage for private enterprises but also a tool for public good. However, market expansion is somewhat tempered by challenges related to data privacy, algorithmic transparency, and the need for standardized data formats across jurisdictions. Addressing these issues will be crucial for sustained growth and broader adoption in the coming years.
Regionally, North America continues to dominate the AI-Powered Rental Price Index market, accounting for the largest share in 2024, owing to its mature real estate sector, high digital adoption, and strong presence of leading proptech firms. Europe is experiencing rapid growth, particularly in countries with high urbanization rates and regulatory support for digital transformation in real estate. Asia Pacific is emerging as a high-growth region, driven by urban expansion, smart city projects, and a burgeoning middle class seeking reliable rental information. While Latin America and Middle East & Africa are currently smaller markets, they present significant long-term potential as digital infrastructure and real estate investment accelerate. Overall, regional dynamics are shaped by varying levels of technological maturity, regulatory frameworks, and the pace of urbanization.
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Graph and download economic data for Consumer Price Index: OECD Groups: Services less housing: Housing excluding imputed rentals for housing for Greece (GRCCPGRLH02GYQ) from Q1 2010 to Q4 2021 about imputed, Greece, rent, services, CPI, price index, indexes, and price.
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Graph and download economic data for Consumer Price Index: OECD Groups: Services Less Housing: Housing Excluding Imputed Rentals for Housing for France (FRACPGRLH02GPQ) from Q2 1990 to Q3 2023 about imputed, France, rent, services, CPI, price index, indexes, and price.
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Estonia EE: Rent Price Index: sa data was reported at 166.033 2015=100 in Mar 2025. This records an increase from the previous number of 160.880 2015=100 for Dec 2024. Estonia EE: Rent Price Index: sa data is updated quarterly, averaging 82.552 2015=100 from Mar 1998 (Median) to Mar 2025, with 109 observations. The data reached an all-time high of 166.033 2015=100 in Mar 2025 and a record low of 38.664 2015=100 in Mar 1998. Estonia EE: Rent Price Index: sa data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Estonia – Table EE.OECD.AHPI: House Price Index: Seasonally Adjusted: OECD Member: Quarterly.
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Rental price statistics historical data time series (indices and annual percentage change). These are official statistics in development.
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According to our latest research, the AI-Powered Rental Price Index market size reached USD 1.7 billion in 2024, reflecting the rapid adoption of artificial intelligence technologies in the real estate sector. The market is projected to grow at a robust CAGR of 18.9% from 2025 to 2033, with the forecasted market size anticipated to reach USD 8.5 billion by 2033. This impressive growth trajectory is driven by the increasing demand for data-driven rental pricing solutions, the proliferation of smart property management systems, and the need for real-time market intelligence among property stakeholders.
One of the key growth factors fueling the expansion of the AI-Powered Rental Price Index market is the escalating complexity and dynamism of global rental markets. Traditional pricing models often fail to capture the nuanced shifts in demand and supply, especially in urban and high-growth regions. AI-powered solutions leverage vast datasets, including historical rental data, economic indicators, neighborhood trends, and even social sentiment, to provide highly accurate and adaptive rental price indices. This enables property managers, landlords, and real estate agencies to optimize pricing strategies, reduce vacancy rates, and maximize returns. The ability to harness predictive analytics and machine learning for rental price forecasting is increasingly seen as a competitive differentiator in the industry.
Another significant driver is the digital transformation sweeping through the real estate sector. The integration of AI-powered rental price indices with property management platforms, listing services, and financial analytics tools is streamlining operations and enhancing decision-making. Cloud-based deployment models are making these advanced analytics accessible to a broader range of users, from large real estate agencies to individual landlords. The automation of rental price assessments not only reduces human error but also accelerates the leasing process, providing a seamless experience for both property owners and tenants. Furthermore, the growing emphasis on transparency and fairness in rental pricing is prompting regulatory bodies and public sector organizations to adopt AI-driven solutions for market monitoring and policy formulation.
The surge in urbanization and the proliferation of rental properties, especially in emerging economies, are also contributing to market growth. As cities expand and rental housing becomes a primary option for a growing segment of the population, the need for accurate, real-time rental price indices becomes critical. AI-powered platforms are uniquely positioned to capture hyper-local trends, adjust for seasonality, and factor in external events such as economic shocks or policy changes. This level of granularity and agility is essential for navigating the increasingly competitive and fragmented rental market landscape. Additionally, the COVID-19 pandemic has accelerated the adoption of digital solutions in real estate, further boosting the demand for AI-powered rental price indices.
Regionally, North America currently dominates the AI-Powered Rental Price Index market, accounting for the largest share in 2024, followed closely by Europe and the Asia Pacific. The United States, in particular, has witnessed widespread adoption of AI-driven property management tools, supported by a mature real estate ecosystem and high digital literacy. Europe is rapidly catching up, driven by regulatory initiatives and a strong focus on data-driven urban planning. The Asia Pacific region is expected to exhibit the highest CAGR over the forecast period, fueled by rapid urbanization, rising investments in proptech startups, and the digitalization of real estate services in countries like China, India, and Australia. Latin America and the Middle East & Africa are also emerging as promising markets, albeit from a smaller base, as local governments and private players recognize the value of AI in addressing housing market inefficiencies.
The AI-Powered Rental Price Index market is segmented by component into Software and Services, each playing a pivotal role in the ecosystem. The software segment comprises AI algorithms, analytics engines, and user interfaces that enable stakeholders to access, interpret, and act on rental price data. These platforms are increasingly incorporating advanced features such as n
Rental rates in the United States increased steadily since 2008. In 2023, the producer price index for gross rent in office buildings reached ***** index points. This means that between 2008 when the index value was set to 100 and 2023, gross office rents grew by about ** percent. Manhattan, San Francisco, and Boston are among the biggest and most expensive markets for office space in the United States.
Commercial rents services price index (CRSPI) by North American Industry Classification System (NAICS). Monthly data are available from January 2006 for the total index and from January 2019 for all other indexes. The table presents data for the most recent reference period and the last five periods. The base period for the index is (2019=100).
The median rent for one- and two-bedroom apartments in Austin, Texas, amounted to ***** U.S. dollars by the end of April 2025. Prices increased slightly after the start of the coronavirus pandemic, but in November 2021, rents surged by almost ** percent. Finally, in April 2025, the rental growth rate experienced a decrease of **** percent. Among the different states in the U.S., Texas ranks as one of the mid-price range rental markets.
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Graph and download economic data for Consumer Price Index: Rent, Repairs, and Maintenance for Italy (CPSEHO05ITQ657N) from Q2 1960 to Q1 2018 about imputed, repair, maintenance, Italy, rent, services, CPI, price index, indexes, and price.
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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 May 2025 about primary, rent, urban, consumer, CPI, inflation, price index, indexes, price, and USA.