Graph and download economic data for All-Transactions House Price Index for Boston, MA (MSAD) (ATNHPIUS14454Q) from Q3 1977 to Q2 2025 about Boston, MA, appraisers, HPI, housing, price index, indexes, price, and USA.

The S&P Case Shiller Boston Home Price Index has risen steadily since *************. The index measures changes in the prices of existing single-family homes. The index value was equal to 100 as of ************, so if the index value is equal to *** in a given month, for example, it means that the house prices have increased by ** percent since 2000. The value of the S&P Case Shiller Boston Home Price Index amounted to nearly ****** in ***********. That was above the national average.

Title: Boston Housing Price Prediction Dataset

Description:

This dataset contains information about housing prices in Boston and is often used for regression analysis and predictive modeling. The dataset is based on the classic Boston Housing dataset, which is frequently used as a benchmark in machine learning.

Attributes:

1. CRIM (Per Capita Crime Rate): The per capita crime rate in the neighborhood.
2. ZN (Proportion of Residential Land Zoned for Large Lots): The proportion of residential land zoned for lots over 25,000 sq. ft.
3. INDUS (Proportion of Non-Retail Business Acres): The proportion of non-retail business acres per town.
4. CHAS (Charles River Dummy Variable): A binary variable indicating whether the Charles River bounds the tract (1 if bounded, 0 otherwise).
5. NOX (Nitric Oxides Concentration): Nitric oxides concentration (parts per 10 million).
6. RM (Average Number of Rooms per Dwelling): The average number of rooms per dwelling.
7. AGE (Proportion of Owner-Occupied Units Built Prior to 1940): The proportion of owner-occupied units built prior to 1940.
8. DIS (Weighted Distances to Employment Centers): Weighted distances to five Boston employment centers.
9. RAD (Index of Accessibility to Radial Highways): An index representing accessibility to radial highways.
10. TAX (Full-Value Property Tax Rate per $10,000): The full-value property tax rate per $10,000.
11. PTRATIO (Pupil-Teacher Ratio): The pupil-teacher ratio by town.
12. B (1000(Bk - 0.63)^2 where Bk is the Proportion of Black Residents): A measure of the proportion of Black residents adjusted for an offset.
13. LSTAT (Percentage of Lower Status of the Population): The percentage of lower-status residents in the population.
14. MEDV (Median Value of Owner-Occupied Homes): The median value of owner-occupied homes in $1000s (Target Variable).

Objective:

Predict the median value of owner-occupied homes (MEDV) based on various features to gain insights into factors influencing housing prices.

Usage:

This dataset is suitable for regression tasks, machine learning practice, and understanding the dynamics of housing markets.

Citation:

The dataset is derived from the UCI Machine Learning Repository and can be cited as follows:

Harrison Jr., D., & Rubinfeld, D. L. (1978). Hedonic prices and the demand for clean air. Journal of Environmental Economics and Management, 5(1), 81-102.

Graph and download economic data for Housing Inventory: Median Days on Market Month-Over-Month in Boston-Cambridge-Newton, MA-NH (CBSA) (MEDDAYONMARMM14460) from Jul 2017 to Aug 2025 about Boston, NH, MA, median, and USA.

The Boston Housing dataset contains information about housing prices in the suburbs of Boston, 1970.

Graph and download economic data for S&P CoreLogic Case-Shiller MA-Boston Home Price Index (BOXRSA) from Jan 1987 to Jun 2025 about Boston, NH, MA, HPI, housing, price index, indexes, price, and USA.

View monthly updates and historical trends for Case-Shiller Home Price Index: Boston, MA. Source: Standard and Poor's. Track economic data with YCharts an…

Graph and download economic data for Housing Inventory: Active Listing Count in Boston-Cambridge-Newton, MA-NH (CBSA) (ACTLISCOU14460) from Jul 2016 to Aug 2025 about Boston, NH, MA, active listing, listing, and USA.

(https://www.kaggle.com/c/house-prices-advanced-regression-techniques) About this Dataset Start here if... You have some experience with R or Python and machine learning basics. This is a perfect competition for data science students who have completed an online course in machine learning and are looking to expand their skill set before trying a featured competition.

Competition Description

Ask a home buyer to describe their dream house, and they probably won't begin with the height of the basement ceiling or the proximity to an east-west railroad. But this playground competition's dataset proves that much more influences price negotiations than the number of bedrooms or a white-picket fence.

With 79 explanatory variables describing (almost) every aspect of residential homes in Ames, Iowa, this competition challenges you to predict the final price of each home.

Practice Skills Creative feature engineering Advanced regression techniques like random forest and gradient boosting Acknowledgments The Ames Housing dataset was compiled by Dean De Cock for use in data science education. It's an incredible alternative for data scientists looking for a modernized and expanded version of the often cited Boston Housing dataset.

Context

There's a story behind every dataset and here's your opportunity to share yours.

Content

What's inside is more than just rows and columns. Make it easy for others to get started by describing how you acquired the data and what time period it represents, too.

Acknowledgements

We wouldn't be here without the help of others. If you owe any attributions or thanks, include them here along with any citations of past research.

Inspiration

Your data will be in front of the world's largest data science community. What questions do you want to see answered?

The U.S. housing market has slowed, after ** consecutive years of rising home prices. In 2021, house prices surged by an unprecedented ** percent, marking the highest increase on record. However, the market has since cooled, with the Freddie Mac House Price Index showing more modest growth between 2022 and 2024. In 2024, home prices increased by *** percent. That was lower than the long-term average of *** percent since 1990. Impact of mortgage rates on homebuying The recent cooling in the housing market can be partly attributed to rising mortgage rates. After reaching a record low of **** percent in 2021, the average annual rate on a 30-year fixed-rate mortgage more than doubled in 2023. This significant increase has made homeownership less affordable for many potential buyers, contributing to a substantial decline in home sales. Despite these challenges, forecasts suggest a potential recovery in the coming years. How much does it cost to buy a house in the U.S.? In 2023, the median sales price of an existing single-family home reached a record high of over ******* U.S. dollars. Newly built homes were even pricier, despite a slight decline in the median sales price in 2023. Naturally, home prices continue to vary significantly across the country, with West Virginia being the most affordable state for homebuyers.

Explore Boston, MA rental market 2025. The average long-term prices $3,342 and short-term $4,567, with trends shaping housing in a city of 663,972 residents.

View yearly updates and historical trends for Boston-Cambridge-Newton, MA-NH Housing Affordability Index. Source: National Association of Realtors. Track …

This statistic shows the housing markets with the largest year-on-year change in house flips in the United States in 2018. The house flipping rate in Boston, Massachusetts was 33 percent higher in 2018 than in 2017. House flipping is a real estate term which refers to the practice of an investor buying property with the aim of reselling them for a profit. The investor either invests capital into each respective property in the form of renovations or simply resells the properties if home prices are on the rise.

Property managers are hired to oversee operations for apartment complexes and other rental sites. In recent years, the property management industry has seen an oversupply of high-end apartments, leading to heightened competition among property managers and slower lease-ups. This has resulted in downward pressure on rent growth and flattened or declining rents in certain regions. In the office space sector, elevated interest rates have significantly decreased new office construction. Limited new stock increases the appeal of prime buildings and gives owners a strong negotiating position, leading to rent gains for Class A buildings. Demand for apartments has remained robust, as climbing home prices and elevated mortgage rates have made home ownership unaffordable for many households. Through the end of 2025, industry revenue has climbed at a CAGR of 1.9% to $134.2 billion, including a boost of 1.9% in 2025 alone. The gain of short-term rental platforms like Airbnb and VRBO has revolutionized the rental market, with property management firms adapting their services to accommodate these changes. However, persistent inflation and high interest rates present operational challenges for the industry and may strengthen costs. Property managers adopt various strategies to offset these expenses, such as adjusting rents, optimizing costs, streamlining operations through software and technology and renegotiating contracts for fixed-rate agreements. Through the end of 2030, housing affordability issues and slow construction activity will continue to boost the residential property management sector. E-commerce growth will stimulate demand in retail property management, with property managers needing to offer more flexible lease agreements adapted to omnichannel retail strategies. Technological advancements will be pivotal in the industry: AI, predictive tools and digital lease management platforms can streamline operations, improve efficiency and offer valuable insights through data analysis. While adopting these technologies may involve upfront costs, they will likely lead to long-term savings and positive transformations within the industry. Altogether, revenue will climb at a CAGR of 1.8% to reach $146.9 billion in 2030.

Housing Inventory: Median Days on Market Year-Over-Year in Boston-Cambridge-Newton, MA-NH (CBSA) was 4.05% in July of 2025, according to the United States Federal Reserve. Historically, Housing Inventory: Median Days on Market Year-Over-Year in Boston-Cambridge-Newton, MA-NH (CBSA) reached a record high of 66.67 in April of 2023 and a record low of -62.00 in May of 2021. Trading Economics provides the current actual value, an historical data chart and related indicators for Housing Inventory: Median Days on Market Year-Over-Year in Boston-Cambridge-Newton, MA-NH (CBSA) - last updated from the United States Federal Reserve on September of 2025.

The median rent for one- and two-bedroom apartments in Boston, Massachusetts, amounted to about ***** U.S. dollars by the end of 2023. Rents decreased slightly after the beginning of the coronavirus pandemic,this trend reversed in 2021 and as of December 2023, the annual rental growth stood at **** percent. Among the different states in the U.S., Massachusetts ranks as one of the most expensive rental markets.

Context

To Explore more on Regression Algorithm

Content

Each record in the database describes a Boston suburb or town. The data was drawn from the Boston Standard Metropolitan Statistical Area (SMSA) in 1970. The attributes are defined as follows (taken from the UCI Machine Learning Repository1): CRIM: per capita crime rate by town 2. ZN: proportion of residential land zoned for lots over 25,000 sq.ft. 3. INDUS: proportion of non-retail business acres per town 4. CHAS: Charles River dummy variable (= 1 if tract bounds river; 0 otherwise) 5. NOX: nitric oxides concentration (parts per 10 million) 1https://archive.ics.uci.edu/ml/datasets/Housing 123 20.2. Load the Dataset 124 6. RM: average number of rooms per dwelling 7. AGE: proportion of owner-occupied units built prior to 1940 8. DIS: weighted distances to five Boston employment centers 9. RAD: index of accessibility to radial highways 10. TAX: full-value property-tax rate per $10,000 11. PTRATIO: pupil-teacher ratio by town 12. B: 1000(Bk−0.63)2 where Bk is the proportion of blacks by town 13. LSTAT: % lower status of the population 14. MEDV: Median value of owner-occupied homes in $1000s We can see that the input attributes have a mixture of units.

Acknowledgements

Thanks to Dr.Jason

Graph and download economic data for All-Transactions House Price Index for Massachusetts (MASTHPI) from Q1 1975 to Q2 2025 about MA, appraisers, HPI, housing, price index, indexes, price, and USA.

The median house prices in the most expensive zip codes in New England, United States ranged from *** to *** million U.S. dollars. Boston (zip code 02199) was the most expensive in New England with a median house price of *** million U.S. dollars. Nevertheless, that was more affordable than in the ten zip codes with the highest median house price in the entire United States.

The United States home construction market, valued at approximately $700 billion in 2025, is experiencing robust growth, projected to maintain a compound annual growth rate (CAGR) exceeding 3% through 2033. This expansion is fueled by several key factors. Firstly, a persistent housing shortage, particularly in desirable urban areas like New York City, Los Angeles, and San Francisco, continues to drive demand. Secondly, favorable demographic trends, including millennial household formation and an increasing preference for homeownership, are bolstering the sector. Furthermore, low interest rates (though this is subject to change depending on economic conditions) have historically made mortgages more accessible, stimulating construction activity. However, the market isn't without its challenges. Rising material costs, labor shortages, and supply chain disruptions continue to exert upward pressure on construction prices, potentially impacting affordability and slowing growth in certain segments. The market is segmented by dwelling type (apartments & condominiums, villas, other), construction type (new construction, renovation), and geographic location, with significant activity concentrated in major metropolitan areas. The dominance of large national builders like D.R. Horton, Lennar Corp, and PulteGroup highlights the industry's consolidation trend, while the growth of multi-family construction reflects shifting urban preferences. Looking ahead, the market's trajectory will depend on macroeconomic factors, interest rate fluctuations, government policies impacting housing affordability, and the ability of the industry to address supply-chain and labor challenges. Innovation in construction technologies, sustainable building practices, and prefabricated homes are also emerging trends expected to significantly influence market dynamics over the forecast period. The competitive landscape is characterized by a mix of large publicly traded companies and smaller regional builders. While established players dominate the market share, opportunities exist for smaller firms specializing in niche markets, such as sustainable or luxury home construction, or those focused on specific geographic areas. The ongoing expansion of the market signifies significant potential for investment and growth, despite the hurdles currently impacting the sector. Addressing supply chain disruptions and labor shortages will be crucial for sustained growth. Continued demand in key urban centers and evolving consumer preferences toward specific dwelling types will be critical factors determining the market's future trajectory. Recent developments include: June 2022 - Pulte Homes - a national brand of PulteGroup, Inc. - announced the opening of its newest Boston-area community, Woodland Hill. Offering 46 new construction single-family homes in the charming town of Grafton, the community is conveniently located near schools, dining, and entertainment, with the Massachusetts Bay Transportation Authority commuter rail less than a mile away. The collection of home designs at Woodland Hill includes three two-story floor plans, ranging in size from 3,013 to 4,019 sq. ft. with four to six bedrooms, 2.5-3.5 baths, and 2-3 car garages. These spacious home designs feature flexible living spaces, plenty of natural light, gas fireplaces, and the signature Pulte Planning Center®, a unique multi-use workstation perfect for homework or a family office., December 2022 - D.R. Horton, Inc. announced the acquisition of Riggins Custom Homes, one of the largest builders in Northwest Arkansas. The homebuilding assets of Riggins Custom Homes and related entities (Riggins) acquired include approximately 3,000 lots, 170 homes in inventory, and 173 homes in the sales order backlog. For the trailing twelve months ended November 30, 2022, Riggins closed 153 homes (USD 48 million in revenue) with an average home size of approximately 1,925 square feet and an average sales price of USD 313,600. D.R. Horton expects to pay approximately USD 107 million in cash for the purchase, and the Company plans to combine the Riggins operations with the current D.R. Horton platform in Northwest Arkansas.. Notable trends are: High-interest Rates are Negatively Impacting the Market.