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.

Accelerated Russian ruble devaluation, caused by the coronavirus (COVID-19) expansion and sinking oil prices, generated an increasingly popular fear of a possible mortgage rate growth in the country. Consequently, the residential real estate demand growth led to increased prices in the secondary market. The highest increase was marked in Krasnoyarsk at two percent, while Moscow made it in the top three with a 1.5 percent increment on average.

For further information about the coronavirus (COVID-19) pandemic, please visit our dedicated Facts and Figures page.

In this Economic Commentary , we compare characteristics of the 2000–2006 house-price boom that preceded the Great Recession to the house-price boom that began in 2020 during the COVID-19 pandemic. These two episodes of high house-price growth have important differences, including the behavior of rental rates, the dynamics of housing supply and demand, and the state of the mortgage market. The absence of changes in fundamentals during the 2000s is consistent with the literature emphasizing house-price beliefs during this prior episode. In contrast to during the 2000s boom, changes in fundamentals (including rent and demand growth) played a more dominant role in the 2020s house-price boom.

The data in this paper are divided into two main sections, which are data on the housing market and data on epidemic case information. The time span of the data sample is from December 1, 2019 to April 26, 2020.The original data of the housing market aspect such as the second-hand house price index in Wuhan and the surrounding provincial capital cities were obtained from Chain Home and Baidu Maps. Among them, there are 53,541 valid records of residential transactions in second-hand neighborhoods, with a final total of 347,720 after data cleaning (5582 in Wuhan; 5710 in Hefei; 7988 in Xi'an; 2066 in Changsha; 5910 in Zhengzhou; and 7464 in Chongqing).

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.

Graph and download economic data for Median Sales Price of Houses Sold for the United States (MSPUS) from Q1 1963 to Q2 2025 about sales, median, housing, and USA.

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.

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...

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]

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.

We’ve examined how pandemic-related to disruption to office working, retail operations and the hospitality sector has affected the real estate market.

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.

Commercial banks are expected to help the federal government deflate Canada’s housing bubble after the COVID-19 (coronavirus) pandemic.

The coronavirus (COVID-19) outbreak, which was aggravated by a drastic reduction in oil prices, led to a significant devaluation of the Russian ruble in March 2020. Consequently, in the view of a possible interest rate increase on mortgage loans, a notable demand growth on real estate was recorded countrywide. The estimated average demand increase in 2020 relative to 2019 was measured between 12 and 15 percent.

For further information about the coronavirus (COVID-19) pandemic, please visit our dedicated Facts and Figures page.

According to Cognitive Market Research, the global Prefabricated Home market size was USD 145142.6 million in 2024. It will expand at a compound annual growth rate (CAGR) of 7.00% 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 58057.04 million in 2024 and will grow at a compound annual growth rate (CAGR) of 5.2% from 2024 to 2031.
Europe accounted for a market share of over 30% of the global revenue with a market size of USD 43542.78 million.
Asia Pacific held a market share of around 23% of the global revenue with a market size of USD 33382.80 million in 2024 and will grow at a compound annual growth rate (CAGR) of 9.0% from 2024 to 2031.
Latin America had a market share of more than 5% of the global revenue with a market size of USD 7257.13 million in 2024 and will grow at a compound annual growth rate (CAGR) of 6.4% 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 2902.85 million in 2024 and will grow at a compound annual growth rate (CAGR) of 6.7% from 2024 to 2031.
The Wood held the highest Prefabricated Home market revenue share in 2024.

Market Dynamics of Prefabricated Home Market

Key Drivers for Prefabricated Home Market

Rising Urbanization to Increase the Demand Globally

The market for prefabricated homes is heavily influenced by the growing urbanization, which creates a need for quick and inexpensive housing options. Because many people cannot afford traditional solutions due to the rapid increase in metropolitan housing prices relative to income growth, prefabricated home affordability is a concern. Their cost-effectiveness offers a suitable alternative. Additionally, they occupy faster than traditional procedures because of their modular nature, which is anticipated to reduce holding costs. Prefabricated homes are an attractive choice for those searching for affordable and timely housing options in urban areas due to their affordability and speed. There is a growing prefabricated housing market as seen by the increasing prevalence of prefabricated homes in the commercial, industrial, and residential sectors. Their potential in a bigger prefabricated home market is demonstrated by the increase in sales. Furthermore, the sustainability, efficiency, and quality of prefabricated homes are increasing due to ongoing technological advancements in construction techniques, materials, and designs. These advancements facilitate the continuous expansion of the industry and establish prefabricated homes as a flexible and appealing option for several sectors.

Innovative Home Design to Propel Market Growth

Consumer preference for sustainable living, energy efficiency, and customisation in homes is rising. Prefabricated homes, with their modern designs, satisfy these criteria. Technological advancements like 3D printing and AI-driven design tools have made complex prefab designs possible, increasing the market's attractiveness. Emerging lifestyles such as tiny homes are driving innovative prefab solutions tailored to specific groups. New designs are appealing to a wide range of customers, which drives market expansion by drawing in new clientele. Premiumization occurs when prefabricated homes with superior design and craftsmanship command higher prices, hence raising the overall market value. A competitive prefabricated homes market environment is created by innovative designs that enable producers to stand out from the competition and appeal to design-conscious buyers.

Restraint Factor for the Prefabricated Home Market

Perception and Stereotypes to Limit the Sales

Changing the public's perspective and the preconceptions around prefabricated homes is one of the main obstacles. Many individuals still hold outmoded beliefs about prefabricated homes, believing them to be of worse quality or offering fewer customizing options than traditional residences. Negative perceptions limit penetration by keeping potential buyers out of the market. Stereotypes about poor quality affect price points and reduce perceived value. A tarnished reputation deters talent and investors, which impedes the industry's expansion.

Impact of Covid-19 on the Prefabricated Home Market

There have been positive as well as negative impacts of the COVID-19 epidemic on the prefabricated home market. People started lookin...

2020 data points are the average of 2019 and 2021 data points and are included solely to maintain chart continuity. The U.S. Census Bureau did not release 2020 ACS 1-year estimates due to COVID-19. These figures should not be interpreted as an actual estimate for 2020. Some racial and ethnic categories are suppressed to avoid misleading estimates when the relative standard error exceeds 30%.

Data Source: American Community Survey (ACS) 1-Year Estimates

Why This Matters

Homeownership has historically been an important source of intergenerational wealth. For many, homeownership can provide financial and housing security.Rising home prices over the past two decades have outpaced wage growth, perpetuating significant racial disparities in homeownership rates and contributing to the displacement of Black residents and other people of color from the District.

A history of redlining and racist real estate practices, like racial covenants, barred Black and other people of color from homeownership.

The District's Response

Convening of the Black Homeownership Strikeforce to address past harms and increase equitable homeownership rates through targeted, evidence-based recommendations, and setting the goal of creating 20,000 new Black homeowners by 2030.

Programs to enable homeowning families and individuals to remain in their homes, including the Homestead Deduction and Senior Citizen or Disabled Property Owner Tax Relief and the Heir Property Assistance Program.

Inclusionary Zoning (IZ) Affordable Housing Program and financial assistance programs like the Home Purchase Assistance Program (HPAP), Employer Assisted Housing Program (EAHP), and Negotiated Employee Assistance Home Purchase Program (NEAHP) to support homeownership among District residents.

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 Peru Gold Production

• Peru Real Residential Property Price Index was reported at 109.464 2010=100 in Jun 2025.
• This records an increase from the previous number of 108.677 2010=100 for Mar 2025.
• Peru Real Residential Property Price Index data is updated quarterly, averaging 120.669 2010=100 from Mar 1998 to Jun 2025, with 110 observations.
• The data reached an all-time high of 156.972 2010=100 in Jun 2014 and a record low of 57.159 2010=100 in Sep 2006.
• Peru 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 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...