This dataset provides insights into the global housing market, covering various economic factors from 2015 to 2024. It includes details about property prices, rental yields, interest rates, and household income across multiple countries. This dataset is ideal for real estate analysis, financial forecasting, and market trend visualization.

📑 Column Descriptions

Key information about House Prices Growth

• US house prices grew 5.2% YoY in Dec 2024, following an increase of 5.4% YoY in the previous quarter.
• YoY growth data is updated quarterly, available from Mar 1992 to Dec 2024, with an average growth rate of 5.4%.
• House price data reached an all-time high of 17.7% in Sep 2021 and a record low of -12.4% in Dec 2008.

Graph and download economic data for Median Sales Price of Houses Sold for the United States (MSPUS) from Q1 1963 to Q1 2025 about sales, median, housing, and USA.

Nahb Housing Market Index in the United States decreased to 32 points in June from 34 points in May of 2025. This dataset provides the latest reported value for - United States Nahb Housing Market Index - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

The number of U.S. home sales in the United States declined in 2024, after soaring in 2021. A total of four million transactions of existing homes, including single-family, condo, and co-ops, were completed in 2024, down from 6.12 million in 2021. According to the forecast, the housing market is forecast to head for recovery in 2025, despite transaction volumes expected to remain below the long-term average. Why have home sales declined? The housing boom during the coronavirus pandemic has demonstrated that being a homeowner is still an integral part of the American dream. Nevertheless, sentiment declined in the second half of 2022 and Americans across all generations agreed that the time was not right to buy a home. A combination of factors has led to house prices rocketing and making homeownership unaffordable for the average buyer. A survey among owners and renters found that the high home prices and unfavorable economic conditions were the two main barriers to making a home purchase. People who would like to purchase their own home need to save up a deposit, have a good credit score, and a steady and sufficient income to be approved for a mortgage. In 2022, mortgage rates experienced the most aggressive increase in history, making the total cost of homeownership substantially higher. Are U.S. home prices expected to fall? The median sales price of existing homes stood at 413,000 U.S. dollars in 2024 and was forecast to increase slightly until 2026. The development of the S&P/Case Shiller U.S. National Home Price Index shows that home prices experienced seven consecutive months of decline between June 2022 and January 2023, but this trend reversed in the following months. Despite mild fluctuations throughout the year, home prices in many metros are forecast to continue to grow, albeit at a much slower rate.

The Utrecht Housing Dataset is a synthetic dataset designed for students and practitioners to learn about data science and machine learning. Derived from the Dutch housing market, it is high-quality and noise-free, making it suitable for multiple algorithms such as decision trees, linear regression, logistic regression, and neural networks. This dataset was specifically created for educational purposes and emphasises responsible AI by being accessible to learners with diverse academic backgrounds.

Dataset Features:

• id: Unique identifier for each house, ranging from 0 to 100,000 (not used in algorithms).
• zipcode: Zip code of the house's location, indicating its area. Possible values: 3520, 3525, 3800.
• lot-len: Length of the house plot in meters, ranging from 5.0 to 100.0.
• lot-width: Width of the house plot in meters, ranging from 5.0 to 100.0.
• lot-area: Total area of the house plot in square meters, derived from lot-len * lot-width.
• house-area: The living area of the house in square meters (e.g., 30.0 for small houses, 200.0 for mansions).
• garden-size: The size of the garden in square meters, with larger gardens being desirable.
• balcony: Number of balconies (common values: 0, 1, 3). x-coor: X-coordinate of the house's location (range: 2000 to 3000).
• y-coor: Y-coordinate of the house's location (range: 5000 to 6000).
• buildyear: The year the house was built (from as early as 1100 to modern times).
• bathrooms: Number of bathrooms (common values: 1, 2, or 3). Output/Target Features
• tax value: Estimated value of the house for taxation, ranging from 50,000 to 1,000,000 euros.
• Retail value: The market value of the house, also ranges from 50,000 to 1,000,000 euros.
• energy-eff: Binary indicator (0 or 1) of whether the house is energy-efficient.
• monument: Binary indicator (0 or 1) of whether the house has architectural or historical monumental value.

Usage:

The dataset is ideal for: - Machine Learning Applications: Training and testing predictive models for tax valuation, market value, and energy efficiency. - Feature Analysis: Exploring the relationships between housing attributes and target values. - Educational Purposes: Teaching students about regression, classification, and feature engineering. - Visualisation: Creating plots and graphs due to the well-structured and interpretable data.

Coverage:

The dataset provides a comprehensive representation of housing features relevant to the Dutch market, ensuring high usability for educational and experimental projects.

License:

CC0 (Public Domain)

Who Can Use It:

This dataset is designed for students, researchers, data scientists, and machine learning practitioners seeking to explore real-world applications of AI in housing markets.

How to Use It:

• Develop predictive models for tax and retail value estimation.
• Evaluate housing energy efficiency or monumental status using classification techniques.
• Explore feature importance to understand what drives housing value.
• Benchmark machine learning algorithms on a synthetic, high-quality dataset.

The municipality’s assessment of the housing market situation in particular housing for the elderly in the municipality. Balance, surplus or deficit of housing. Housing deficits do not always mean that there are housing social problems such as overcrowding or extensive subletting as a widespread phenomenon. Housing deficits can mean that there is a dynamic economy in the municipality, where increased income leads to increased demand for housing. The fact that a municipality reports a deficit on housing means in many cases that it is difficult to move to, or within the municipality. surplus of housing means that there are constantly more vacant dwellings, or homes for sale, than is demanded. The existence of unleashed apartments in a single residential area does not necessarily mean that the local housing market is characterised by a surplus. A surplus of housing does not necessarily mean that there are suitable housing in relation to the demand and/or need in the municipality. Special forms of housing for the elderly refer to housing in accordance with Chapter 5, Section 5 of the Social Services Act. In order to be able to live in special housing, you need an aid assessment and a decision from the municipality.

House prices in the UK rose dramatically during the coronavirus pandemic, with growth slowing down in 2022 and turning negative in 2023. The year-on-year annual house price change peaked at 14 percent in July 2022. In February 2025, house prices increased by 5.4 percent. As of late 2024, the average house price was close to 290,000 British pounds. Correction in housing prices: a European phenomenon The trend of a growing residential real estate market was not exclusive to the UK during the pandemic. Likewise, many European countries experienced falling prices in 2023. When comparing residential property RHPI (price index in real terms, e.g. corrected for inflation), countries such as Germany, France, Italy, and Spain also saw prices decline. Sweden, one of the countries with the fastest growing residential markets, saw one of the largest declines in prices. How has demand for UK housing changed since the outbreak of the coronavirus? The easing of the lockdown was followed by a dramatic increase in home sales. In November 2020, the number of mortgage approvals reached an all-time high of over 107,000. One of the reasons for the housing boom were the low mortgage rates, allowing home buyers to take out a loan with an interest rate as low as 2.5 percent. That changed as the Bank of England started to raise the base lending rate, resulting in higher borrowing costs and a decline in homebuyer sentiment.

The municipality’s assessment of the housing market situation for young people, aged 19-25, in the municipality. Balance, surplus or deficit of housing. Housing deficits do not always mean that there are housing social problems such as overcrowding or extensive subletting as a widespread phenomenon. Housing deficits can mean that there is a dynamic economy in the municipality, where increased income leads to increased demand for housing. The fact that a municipality reports a deficit on housing means in many cases that it is difficult to move to, or within the municipality. surplus of housing means that there are constantly more vacant dwellings, or homes for sale, than is demanded. The existence of unleashed apartments in a single residential area does not necessarily mean that the local housing market is characterised by a surplus. A surplus of housing does not necessarily mean that there are suitable housing in relation to the demand and/or need in the municipality.

The municipality’s assessment of the housing market situation in the municipality as a whole. Balance, surplus or deficit of housing. Housing deficits do not always mean that there are housing social problems such as overcrowding or extensive subletting as a widespread phenomenon. Housing deficits can mean that there is a dynamic economy in the municipality, where increased income leads to increased demand for housing. The fact that a municipality reports a housing deficit means in many cases that it is difficult to move to, or within the municipality. Surplus housing means that there are constantly more vacant dwellings, or homes for sale, than is demanded. The existence of unleashed apartments in a single residential area does not necessarily mean that the local housing market is characterised by a surplus. A surplus of housing does not necessarily mean that there are suitable housing in relation to the demand and/or need in the municipality. In 2013, the answer option “Almost balance on bost. land” was used instead of “balance”.

Residential: CO: Unsold: Johor: Cluster: < MYR 50000 data was reported at 0.000 Unit in Mar 2018. This stayed constant from the previous number of 0.000 Unit for Dec 2017. Residential: CO: Unsold: Johor: Cluster: < MYR 50000 data is updated quarterly, averaging 0.000 Unit from Dec 2003 (Median) to Mar 2018, with 58 observations. Residential: CO: Unsold: Johor: Cluster: < MYR 50000 data remains active status in CEIC and is reported by Valuation and Property Services Department, Ministry of Finance. The data is categorized under Global Database’s Malaysia – Table MY.EB025: Residential Property Market Status: Unsold: Unit: Completed: by Type of Property & Price Range.

The municipality’s assessment of the housing market situation for self-employed new arrivals in the municipality. Newly arrived persons who are covered by the reception in municipalities are refugees, persons in need of protection or persons with permission due to exceptional or particularly distressing circumstances and their relatives. A person is considered to be newly arrived while he or she is covered by establishment initiatives, i.e. two to three years. Balance, surplus or deficit of housing. Housing deficits do not always mean that there are housing social problems such as overcrowding or extensive subletting as a widespread phenomenon. Housing deficits can mean that there is a dynamic economy in the municipality, where increased income leads to increased demand for housing. The fact that a municipality reports a deficit on housing means in many cases that it is difficult to move to, or within the municipality. surplus of housing means that there are constantly more vacant dwellings, or homes for sale, than is demanded. The existence of unleashed apartments in a single residential area does not necessarily mean that the local housing market is characterised by a surplus. A surplus of housing does not necessarily mean that there are suitable housing in relation to the demand and/or need in the municipality.

Malaysia Residential: CO: LA: Johor: Town House: MYR100001-150000 data was reported at 0.000 Unit in Mar 2018. This stayed constant from the previous number of 0.000 Unit for Dec 2017. Malaysia Residential: CO: LA: Johor: Town House: MYR100001-150000 data is updated quarterly, averaging 211.000 Unit from Dec 2003 (Median) to Mar 2018, with 58 observations. The data reached an all-time high of 623.000 Unit in Jun 2006 and a record low of 0.000 Unit in Mar 2018. Malaysia Residential: CO: LA: Johor: Town House: MYR100001-150000 data remains active status in CEIC and is reported by Valuation and Property Services Department, Ministry of Finance. The data is categorized under Global Database’s Malaysia – Table MY.EB035: Residential Property Market Status: Launched: Unit: Completed: by Type of Property & Price Range.

The municipality’s assessment of the housing market situation for special forms of housing for persons with disabilities in the municipality. Special forms of accommodation for persons with disabilities are housing under the Act on Support and Services for Persons with Certain Disabilities (LSS), or Chapter 5, Section 7 of the Social Services Act. Balance, surplus or deficit of housing. Housing deficits do not always mean that there are housing social problems such as overcrowding or extensive subletting as a widespread phenomenon. Housing deficits can mean that there is a dynamic economy in the municipality, where increased income leads to increased demand for housing. The fact that a municipality reports a deficit on housing means in many cases that it is difficult to move to, or within the municipality. surplus of housing means that there are constantly more vacant dwellings, or homes for sale, than is demanded. The existence of unleashed apartments in a single residential area does not necessarily mean that the local housing market is characterised by a surplus. A surplus of housing does not necessarily mean that there are suitable housing in relation to the demand and/or need in the municipality.

Residential: CO: LA: 2 to 3 Storey Terraced: MYR300001-400000 data was reported at 4,660.000 Unit in Jun 2018. This records an increase from the previous number of 4,497.000 Unit for Mar 2018. Residential: CO: LA: 2 to 3 Storey Terraced: MYR300001-400000 data is updated quarterly, averaging 1,586.000 Unit from Jun 2013 (Median) to Jun 2018, with 21 observations. The data reached an all-time high of 4,660.000 Unit in Jun 2018 and a record low of 576.000 Unit in Jun 2013. Residential: CO: LA: 2 to 3 Storey Terraced: MYR300001-400000 data remains active status in CEIC and is reported by Valuation and Property Services Department, Ministry of Finance. The data is categorized under Global Database’s Malaysia – Table MY.EB035: Residential Property Market Status: Launched: Unit: Completed: by Type of Property & Price Range.

MY: Residential: MS: Unsold: Completed: P.Pinang: Low Cost House data was reported at 0.000 Unit in Jun 2018. This stayed constant from the previous number of 0.000 Unit for Mar 2018. MY: Residential: MS: Unsold: Completed: P.Pinang: Low Cost House data is updated quarterly, averaging 0.000 Unit from Mar 2003 (Median) to Jun 2018, with 62 observations. The data reached an all-time high of 58.000 Unit in Dec 2003 and a record low of 0.000 Unit in Jun 2018. MY: Residential: MS: Unsold: Completed: P.Pinang: Low Cost House data remains active status in CEIC and is reported by Valuation and Property Services Department, Ministry of Finance. The data is categorized under Global Database’s Malaysia – Table MY.EB024: Residential Property Market Status: Unsold: Unit: Completed.

Residential: CO: LA: Cluster: MYR50001-100000 data was reported at 0.000 Unit in Mar 2018. This stayed constant from the previous number of 0.000 Unit for Dec 2017. Residential: CO: LA: Cluster: MYR50001-100000 data is updated quarterly, averaging 0.000 Unit from Dec 2003 (Median) to Mar 2018, with 58 observations. The data reached an all-time high of 504.000 Unit in Sep 2007 and a record low of 0.000 Unit in Mar 2018. Residential: CO: LA: Cluster: MYR50001-100000 data remains active status in CEIC and is reported by Valuation and Property Services Department, Ministry of Finance. The data is categorized under Global Database’s Malaysia – Table MY.EB035: Residential Property Market Status: Launched: Unit: Completed: by Type of Property & Price Range.

Residential: CO: LA: Flat: < MYR 50000 data was reported at 64.000 Unit in Mar 2018. This stayed constant from the previous number of 64.000 Unit for Dec 2017. Residential: CO: LA: Flat: < MYR 50000 data is updated quarterly, averaging 2,308.500 Unit from Dec 2003 (Median) to Mar 2018, with 58 observations. The data reached an all-time high of 4,181.000 Unit in Dec 2009 and a record low of 64.000 Unit in Mar 2018. Residential: CO: LA: Flat: < MYR 50000 data remains active status in CEIC and is reported by Valuation and Property Services Department, Ministry of Finance. The data is categorized under Global Database’s Malaysia – Table MY.EB035: Residential Property Market Status: Launched: Unit: Completed: by Type of Property & Price Range.

Residential: CO: Unsold: Johor: Condominium: MYR150001-200000 data was reported at 0.000 Unit in Mar 2018. This stayed constant from the previous number of 0.000 Unit for Dec 2017. Residential: CO: Unsold: Johor: Condominium: MYR150001-200000 data is updated quarterly, averaging 62.500 Unit from Dec 2003 (Median) to Mar 2018, with 58 observations. The data reached an all-time high of 425.000 Unit in Jun 2007 and a record low of 0.000 Unit in Mar 2018. Residential: CO: Unsold: Johor: Condominium: MYR150001-200000 data remains active status in CEIC and is reported by Valuation and Property Services Department, Ministry of Finance. The data is categorized under Global Database’s Malaysia – Table MY.EB025: Residential Property Market Status: Unsold: Unit: Completed: by Type of Property & Price Range.

Residential: CO: LA: 2 to 3 Storey Semi Detached: MYR250001-300000 data was reported at 68.000 Unit in Jun 2018. This records a decrease from the previous number of 92.000 Unit for Mar 2018. Residential: CO: LA: 2 to 3 Storey Semi Detached: MYR250001-300000 data is updated quarterly, averaging 150.000 Unit from Jun 2013 (Median) to Jun 2018, with 21 observations. The data reached an all-time high of 182.000 Unit in Dec 2015 and a record low of 68.000 Unit in Jun 2018. Residential: CO: LA: 2 to 3 Storey Semi Detached: MYR250001-300000 data remains active status in CEIC and is reported by Valuation and Property Services Department, Ministry of Finance. The data is categorized under Global Database’s Malaysia – Table MY.EB035: Residential Property Market Status: Launched: Unit: Completed: by Type of Property & Price Range.