In April 2020, the Sakha (Yakutiya) Republic recorded the most significant price drop in real estate prices in Russia with a roughly five percent price fall per square meter. In the Moscow and Leningrad Regions, the price of residential properties dropped by 3.2 and 3 percentage points per square meter over the given period, respectively.

La Rioja was the Spanish region where the pandemic impact on real estate prices was higher compared to the previous year, with a decrease of almost 16% in the last quarter of 2020. The only place in Spain where there was an increase in comparison with the pre-pandemic data was in the autonomous city of Melilla.

In a September 2020 survey among adults in the United States, many respondents said that the COVID-19 pandemic did not change their interest in buying a home. Millennials were most likely to have changed their homeownership plans: ** percent of Millennials were more interested in buying a home due to the COVID-19 pandemic compared with **** percent of Baby Boomers.In the United States, the 2020 homeownership rate reached **** percent.

Analysis of Spanish Apartment Pricing and Size Post-COVID-19

Investigating the Impact of the Pandemic

By [source]

About this dataset

This dataset provides an in-depth insight into Spanish apartment prices, locations and sizes, offering a comprehensive view of the effects of the Covid-19 crisis in this market. By exploring the data you can gain valuable knowledge on how different variables such as number of rooms, bathrooms, square meters and photos influence pricing, as well as key details such as description and whether or not they are recommended by reviews. Furthermore, by comparing average prices per square meter regionally between different areas you can get a better understanding of individual apartment value changes over time. Whether you are looking for your dream home or simply seeking to understand current trends within this sector this dataset is here to provide all the information necessary for both people either starting or already familiar with this industry

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How to use the dataset

This dataset includes a comprehensive collection of Spanish apartments that are currently up for sale. It provides valuable insight into the effects of the Covid-19 pandemic on pricing and size. With this guide, you can take advantage of all the data to explore how different factors like housing surface area, number of rooms and bathrooms, location, number of photos associated with an apartment, type and recommendations affect price.

• First off, you should start by taking a look at summary column which summarizes in one or two lines what each apartment is about. You can quickly search some patterns which could give important information about the market current situation during COVID-19 crisis.

• Explore more in depth each individual apartment by looking at its description section for example if it refers to particular services available like swimming pool or gymnasiums . Consequently those extra features usually bumps up the prices higher since buyers are keen to have such luxury items included in their purchase even if it’s not so affordable sometimes..

• Start studying locationwise since it might gives hint as to what kind preof city we have eirther active market in terms equity investment , home stay rental business activities that suggest opportunities for considerable return on investment (ROI). Even further detailed analysis such as comparing net change over time energy efficient ratings electrical or fuel efficiency , transport facilities , educational level may be conducted when choosing between several apartments located close one another ..

• Consider multiple column ranging from price value provided (price/m2 )to size sqm surface area measure and count number of rooms & bathrooms . Doing so will help allot better understanding whether purchasing an unit is worth expenditure once overall costs per advantages estimated –as previously acknowledged apps features could increase prices significantly- don’t forget security aspect major item critical home choice making process affording protection against Intruders ..

• An interesting but tricky part is Num Photos how many were included –possibly indicates quality build high end projects appreciate additional gallery mentioning quite informative panorama around property itself - while recomendation customarily assumes certain guarantees warranties unique promise provided providing aside prospective buyer safety issues impose trustworthiness matters shared among other future residents …

• Finally type & region column should be taken into account reason enough different categories identifies houses versus flats diversely built outside suburban villas contained inside specially designed mansion areas built upon special requests .. Therefore usage those two complementary field help finding right desired environment accompaniments beach lounge bar attract nature lovers adjacent mountainside

Research Ideas

• Creating an interactive mapping tool that showcases the average prices per square meter of different cities or regions in Spain, enabling potential buyers to identify the most affordable areas for their desired budget and size.
• Developing a comparison algorithm that recommends the best options available depending on various criteria such as cost, rooms/bathrooms, recommended status, etc., helping users make informed decisions when browsing for apartments online.
• Constructing a model that predicts sale prices based on existing data trends and analyses of photos and recommendations associated wit...

The website plans.fr, which lists more than 1,000 house plans online, has listed price increases in construction since 2020. These increases are due to several factors: — Re 2020 replacing the ROE 2012 — COVID with shortages of materials and craftsmen — High inflation of raw materials (+ 60 % on steel,...) The rises in the price of new housing since 2020 are delusional and have never been seen in recent history.

Residential Property Price Index: 18 Cities: Large data was reported at 107.304 2018=100 in Dec 2024. This records an increase from the previous number of 107.109 2018=100 for Sep 2024. Residential Property Price Index: 18 Cities: Large data is updated quarterly, averaging 102.588 2018=100 from Mar 2018 (Median) to Dec 2024, with 28 observations. The data reached an all-time high of 107.304 2018=100 in Dec 2024 and a record low of 99.532 2018=100 in Mar 2018. Residential Property Price Index: 18 Cities: Large data remains active status in CEIC and is reported by Bank Indonesia. The data is categorized under Global Database’s Indonesia – Table ID.EF010: Residential Property Price Index: by Cities. [COVID-19-IMPACT]

In a September 2020 survey among adults in the United States, over half of respondents said that their interest in buying a home had not changed due to the COVID-19 pandemic (** percent). However, Hispanic respondents were more likely to have changed their plans (** percent) compared to white respondents (** percent). In the United States, the 2020 homeownership rate reached **** percent.

The samples in this paper come from panel data of 35 large and medium-sized cities in China from 1999 to 2019(In order to avoid the impact of the COVID-19 Pandemic on the conclusions of this analysis, we use the data before the outbreak of the epidemic for empirical testing). Here, the variables adopted for assessing the housing bubble include price level, resident income, household population, the average wage of staff and land supply. Apart from the housing bubble index which is obtained via assessment, all the other basic data come from official statistics, including the Wind Economic Database, website of the People’s Bank of China, and National Bureau of Statistics website.

Key information about US Nominal Residential Property Price Index

• United States Nominal Residential Property Price Index was reported at 232.573 2010=100 in Sep 2024.
• This records an increase from the previous number of 230.393 2010=100 for Jun 2024.
• US Nominal Residential Property Price Index data is updated quarterly, averaging 61.010 2010=100 from Mar 1970 to Sep 2024, with 219 observations.
• The data reached an all-time high of 232.573 2010=100 in Sep 2024 and a record low of 10.610 2010=100 in Mar 1970.
• US Nominal Residential Property Price Index data remains active status in CEIC and is reported by Bank for International Settlements.
• The data is categorized under World Trend Plus’s Association: Property Sector – Table RK.BIS.RPPI: Selected Nominal Residential Property Price Index: 2010=100: Quarterly.

This study examines the spatial dynamics of urban vegetation and its impact on housing prices in Chicago, analyzing data from both pre- and post-COVID-19 periods. Employing Ordinary Least Squares (OLS) and Multiscale Geographically Weighted Regression (MGWR) models, we assess how the effects of green spaces on property values vary across different neighborhoods. The OLS model generally indicates a positive correlation between increased vegetation and housing prices. In contrast, the MGWR model reveals that the benefits of urban green spaces to property values are not uniformly distributed and exhibit significant variability. Notably, in some South Side areas of Chicago, increases in green space correlate with declines in property values, a sensitivity that intensified post-pandemic, leading to notable price declines. Conversely, the North Side, characterized as a higher-income area, shows greater resilience to the impacts of both increased green spaces and the COVID-19 pandemic, with less susceptibility to economic downturns. This research underscores the intricate interplay between urban green spaces and economic factors, highlighting how local socio-economic conditions and urban planning strategies can influence the economic benefits of vegetation. The findings provide essential insights for urban policymakers and planners striving to promote sustainable development and equitable economic growth in urban environments.

Residential real estate transactions saw both a decline as well as an increase during the coronavirus pandemic in 2020, depending on the country. In Denmark, for example, property sales increased by over ***** percent year-on-year in the second quarter of 2020. This was in stark contrast to the United Kingdom, where provisional and non-seasonal data suggested the country saw one of its largest drops in housing transactions since 2009. Some countries, on the other hand, already witnessed a decrease in their transactions before COVID-19 hit Europe. The housing trade inFrance, for example, suffered a large decrease in the first quarter of 2020, right before quarantine measures were enforced. Data for Germany, on the other hand, suggested that its housing market was still growing before the lockdown. Whether this was still the case in 2020 remains to be seen.

Key information about China Gold Production

• China Real Residential Property Price Index was reported at 90.676 2010=100 in Jun 2025.
• This records a decrease from the previous number of 91.615 2010=100 for Mar 2025.
• China Real Residential Property Price Index data is updated quarterly, averaging 93.824 2010=100 from Jun 2005 to Jun 2025, with 81 observations.
• The data reached an all-time high of 112.991 2010=100 in Sep 2021 and a record low of 87.950 2010=100 in Jun 2005.
• China Real Residential Property Price Index data remains active status in CEIC and is reported by Bank for International Settlements.
• The data is categorized under World Trend Plus’s Association: Property Sector – Table RK.BIS.RPPI: Selected Real Residential Property Price Index: 2010=100: Quarterly. [COVID-19-IMPACT]

According to Cognitive Market Research, the global Residential Real Estate market size was USD 32651.6 million in 2024. It will expand at a compound annual growth rate (CAGR) of 5.50% from 2024 to 2031.

North America held the major market share for more than 40% of the global revenue with a market size of USD 13060.64 million in 2024 and will grow at a compound annual growth rate (CAGR) of 3.7% from 2024 to 2031.
Europe accounted for a market share of over 30% of the global revenue with a market size of USD 9795.48 million.
Asia Pacific held a market share of around 23% of the global revenue with a market size of USD 7509.87 million in 2024 and will grow at a compound annual growth rate (CAGR) of 7.5% from 2024 to 2031.
Latin America had a market share of more than 5% of the global revenue with a market size of USD 1632.58 million in 2024 and will grow at a compound annual growth rate (CAGR) of 4.9% from 2024 to 2031.
Middle East and Africa had a market share of around 2% of the global revenue and was estimated at a market size of USD 653.03 million in 2024 and will grow at a compound annual growth rate (CAGR) of 5.2% from 2024 to 2031.
The single-family homes category is the fastest growing segment of the Residential Real Estate industry

Market Dynamics of Residential Real Estate Market

Key Drivers for Residential Real Estate Market

Increasing population drives housing demand to Boost Market Growth

Increasing population drives housing demand by creating a need for more residential spaces to accommodate growing numbers of people. As population rises, particularly in urban and suburban areas, demand for housing expands, fueling the residential real estate market. This is especially evident in countries experiencing rapid urbanization, where people move to cities seeking better job opportunities, education, and lifestyle options, further increasing housing needs. Additionally, population growth often correlates with the formation of new households, such as young families or individuals moving out on their own, intensifying the demand for housing units. In response, developers and investors are motivated to build more residential properties, ranging from single-family homes to multifamily units, contributing to market growth and driving real estate values upward. For instance, The Ashwin Sheth Group aims to broaden its residential and commercial offerings in the Mumbai Metropolitan Region (MMR) of India.

Rising incomes and economic stability to Drive Market Growth

Rising incomes and economic stability drive the residential real estate market by boosting consumers’ purchasing power and confidence in long-term investments like homeownership. As incomes increase, people can afford larger down payments, qualify for higher loan amounts, and manage mortgage payments more comfortably, making home buying a more viable option. Economic stability, characterized by low unemployment rates and steady GDP growth, reinforces this confidence, as individuals feel secure in their financial situations. With greater disposable income, many consumers seek to upgrade to larger homes, buy second properties, or invest in luxury real estate, further fueling demand. This economic backdrop attracts both local and foreign investors, leading to more housing developments, increased property values, and a flourishing residential real estate market.

Restraint Factor for the Residential Real Estate Market

High Property Prices will Limit Market Growth

High property prices restrain the residential real estate market by making homeownership unaffordable for a significant portion of the population. As prices rise, potential buyers, particularly first-time homeowners and low- to middle-income families, may find it challenging to secure adequate financing or meet the necessary down payment requirements. This affordability crisis limits the pool of qualified buyers, leading to slower sales and potential stagnation in market growth. Additionally, high property prices can prompt increased demand for rental properties, shifting focus away from home purchases. In markets where prices escalate rapidly, even affluent buyers may hesitate, fearing potential market corrections. Consequently, elevated property values can create a barrier to entry, ultimately restricting the overall health and vibrancy of the residential real estate market.

Impact of Covid-19 on the Residential Real Estate Market

The COVI...

Key information about Indonesia Gold Production

• Indonesia Real Residential Property Price Index was reported at 94.958 2010=100 in Jun 2025.
• This records a decrease from the previous number of 96.606 2010=100 for Mar 2025.
• Indonesia Real Residential Property Price Index data is updated quarterly, averaging 104.158 2010=100 from Mar 2002 to Jun 2025, with 94 observations.
• The data reached an all-time high of 140.259 2010=100 in Jun 2002 and a record low of 94.958 2010=100 in Jun 2025.
• Indonesia Real Residential Property Price Index data remains active status in CEIC and is reported by Bank for International Settlements.
• The data is categorized under World Trend Plus’s Association: Property Sector – Table RK.BIS.RPPI: Selected Real Residential Property Price Index: 2010=100: Quarterly. [COVID-19-IMPACT]

Key information about Russia Gold Production

• Russia Real Residential Property Price Index was reported at 76.346 2010=100 in Jun 2025.
• This records a decrease from the previous number of 76.542 2010=100 for Mar 2025.
• Russia Real Residential Property Price Index data is updated quarterly, averaging 78.396 2010=100 from Mar 2001 to Jun 2025, with 98 observations.
• The data reached an all-time high of 113.140 2010=100 in Sep 2008 and a record low of 34.944 2010=100 in Mar 2001.
• Russia Real Residential Property Price Index data remains active status in CEIC and is reported by Bank for International Settlements.
• The data is categorized under World Trend Plus’s Association: Property Sector – Table RK.BIS.RPPI: Selected Real Residential Property Price Index: 2010=100: Quarterly. [COVID-19-IMPACT]

Dataset Description: Pakistan Real Estate Prices (2018-2019)

Context

This dataset provides real estate price listings across various cities in Pakistan, capturing property details, pricing, locations, and listing dates. The data is valuable for market analysis, price forecasting, and inflation studies, making it a key resource for investors, researchers, and data scientists.

Source & Inspiration

The dataset is sourced from Zameen.com, Pakistan's leading real estate platform, containing 168,447 property listings from 2018 and 2019. The dataset helps analyze:

Market trends before COVID-19 Price fluctuations due to inflation Impact of location and property type on prices Forecasting future price movements Features & Data Columns Property Details: property_id, property_type, bedrooms, baths, Total_Area Location Info: location, city, province_name, latitude, longitude Financials: price (target variable), purpose (For Sale / For Rent) Time Features: date_added (listing date in YYYY-MM-DD format) Agency & Agent: agency, agent Meta: page_url (property page link)

Why This Dataset Matters?

Helps predict house prices using ML models like ARIMA, Prophet, LSTM Enables inflation tracking by observing price changes over time Provides insights into real estate investments in Pakistan

Key information about Serbia Gold Production

• Serbia Real Residential Property Price Index was reported at 115.200 2010=100 in Jun 2025.
• This records an increase from the previous number of 114.750 2010=100 for Mar 2025.
• Serbia Real Residential Property Price Index data is updated quarterly, averaging 79.860 2010=100 from Mar 2000 to Jun 2025, with 102 observations.
• The data reached an all-time high of 144.820 2010=100 in Jun 2000 and a record low of 65.513 2010=100 in Sep 2002.
• Serbia Real Residential Property Price Index data remains active status in CEIC and is reported by Bank for International Settlements.
• The data is categorized under World Trend Plus’s Association: Property Sector – Table RK.BIS.RPPI: Selected Real Residential Property Price Index: 2010=100: Quarterly. [COVID-19-IMPACT]

Gross fixed capital formation for housing decreased significantly in several European countries in early 2020 but followed with a drop in the second quarter of the year with the coronavirus (COVID-19) outbreak. This translated into a halt of residential property investments. In countries like the United Kingdom (UK), Ireland, France, Spain, Italy, and Luxembourg the year-on-year percentage decrease was between ** and ** percent. Тhis was not the case with several countries that kept housing investment growing on an year-on-year basis in 2020: Greece, Hungary, Sweden, Denmark, and Czechia.

More in-depth data can be found in the report on the coronavirus impacting house prices in Europe in 2020 and 2021.

Context

The purpose of this dataset is to provide updated data on the Zillow Observed Rent Index (ZORI). Most of the Zillow datasets on Kaggle have not been updated in four years, and no other dataset except one contains information related to rent. Providing updated data on this will also allow the community to analyze the effects of COVID-19 on rent prices, which could not be done with previous available data sets.

Content

Zillow Observed Rent Index (ZORI): A smoothed measure of the typical observed market rate rent across a given region. ZORI is a repeat-rent index that is weighted to the rental housing stock to ensure representativeness across the entire market, not just those homes currently listed for-rent. The index is dollar-denominated by computing the mean of listed rents that fall into the 40th to 60th percentile range for all homes and apartments in a given region, which is once again weighted to reflect the rental housing stock. Details available in ZORI methodology. https://www.zillow.com/research/methodology-zori-repeat-rent-27092/

This dataset contains two files. The Metro dataset looks at the median rent prices for large US cities. The ZIP code dataset breaks the US cities down by their ZIP codes. Note that the region IDs in both datasets are only used for tracking purposes. Also, some of the ZIP codes under the Region Name are less than the standard five-digit zip code and unreliable. Even if you add zeros in accounting for possible formatting mistakes. It is recommended to remove these entries since there is no way to identify which ZIP code the entry actually represents. These entries are left in here in case some analyst can solve the issue.

Acknowledgements

Zillow provides many useful open source datasets that relate to housing, which can be found at Zillow Research Data. https://www.zillow.com/research/data/ This dataset was also prompted by an older dataset I came across that only lacked updated data. https://www.kaggle.com/zillow/rent-index Thumbnail and banner picture is from this pixabay artist https://pixabay.com/users/pexels-2286921/

Inspiration

1. Where are the cheapest and most expensive ZIP codes to live?
2. We all know rent increases overtime, but has it been increasing at a faster rate since 2014?
3. If rent has been increasing at a faster rate, what year did it increase the fastest?
4. What cities or ZIP codes are increasing rent the fastest and by how much?
5. Did rent continue to increase during the COVID-19 pandemic, and was it at a faster or slower rate than previous years?

European Union House Price Index: EU 27 excl UK data was reported at 155.790 2015=100 in Dec 2024. This records an increase from the previous number of 154.620 2015=100 for Sep 2024. European Union House Price Index: EU 27 excl UK data is updated quarterly, averaging 102.895 2015=100 from Mar 2005 (Median) to Dec 2024, with 80 observations. The data reached an all-time high of 155.790 2015=100 in Dec 2024 and a record low of 83.540 2015=100 in Mar 2005. European Union House Price Index: EU 27 excl UK data remains active status in CEIC and is reported by Eurostat. The data is categorized under Global Database’s European Union – Table EU.EB001: Eurostat: House Price Index: 2015=100. [COVID-19-IMPACT]