Nahb Housing Market Index in the United States decreased to 39 points in March from 42 points in February 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.

DisclaimerBefore using this layer, please review the 2018 Rochester Citywide Housing Market Study for the full background and context that is required for interpreting and portraying this data. Please click here to access the study. Please also note that the housing market typologies were based on analysis of property data from 2008 to 2018, and is a snapshot of market conditions within that time frame. For an accurate depiction of current housing market typologies, this analysis would need to be redone with the latest available data.About the DataThis is a webmap of a polygon feature layer containing the boundaries of all census blockgroups in the city of Rochester. Beyond the unique identifier fields including GEOID, the only other field is the housing market typology for that blockgroup. The map is visualized based on market typology score with strongest market in pink, and weakest market in dark blue.Information from the 2018 Housing Market Study- Housing Market TypologiesThe City of Rochester commissioned a Citywide Housing Market Study in 2018 as a technical study to help inform development of the City's new Comprehensive Plan, Rochester 2034 , and retained czb, LLC - a firm with national expertise based in Alexandria, VA - to perform the analysis.Any understanding of Rochester’s housing market – and any attempt to develop strategies to influence the market in ways likely to achieve community goals – must begin with recognition that market conditions in the city are highly uneven. On some blocks, competition for real estate is strong and expressed by pricing and investment levels that are above city averages. On other blocks, private demand is much lower and expressed by above average levels of disinvestment and physical distress. Still other blocks are in the middle – both in terms of condition of housing and prevailing prices. These block-by-block differences are obvious to most residents and shape their options, preferences, and actions as property owners and renters. And, importantly, these differences shape the opportunities and challenges that exist in each neighborhood, the types of policy and investment tools to utilize in response to specific needs, and the level and range of available resources, both public and private, to meet those needs. The City of Rochester has long appreciated that a one-size-fits-all approach to housing and neighborhood strategy is inadequate in such a diverse market environment, and that is no less true today. To concisely describe distinct market conditions and trends across the city in this study, a Housing Market Typology was developed using a wide range of indicators to gauge market health and investment behaviors. This section of the Citywide Housing Market Study introduces the typology and its components. In later sections, the typology is used as a tool for describing and understanding demographic and economic patterns within the city, the implications of existing market patterns on strategy development, and how existing or potential policy and investment tools relate to market conditions.Overview of Housing Market Typology PurposeThe Housing Market Typology in this study is a tool for understanding recent market conditions and variations within Rochester and informing housing and neighborhood strategy development. As with any typology, it is meant to simplify complex information into a limited number of meaningful categories to guide action. Local context and knowledge remain critical to understanding market conditions and should always be used alongside the typology to maximize its usefulness.Geographic Unit of Analysis The Block Group – a geographic unit determined by the U.S. Census Bureau – is the unit of analysis for this typology, which utilizes parcel-level data. There are over 200 Block Groups in Rochester, most of which cover a small cluster of city blocks and are home to between 600 and 3,000 residents. For this tool, the Block Group provides geographies large enough to have sufficient data to analyze and small enough to reveal market variations within small areas.Four Components for CalculationAnalysis of multiple datasets led to the identification of four typology components that were most helpful in drawing out market variations within the city:• Terms of Sale• Market Strength• Bank Foreclosures• Property DistressThose components are described one-by-one on in the full study document (LINK), with detailed methodological descriptions provided in the Appendix.A Spectrum of Demand The four components were folded together to create the Housing Market Typology. The seven categories of the typology describe a spectrum of housing demand – with lower scores indicating higher levels of demand, and higher scores indicating weaker levels of demand. Typology 1 are areas with the highest demand and strongest market, while typology 3 are the weakest markets. For more information please visit: https://www.cityofrochester.gov/HousingMarketStudy2018/

The Russian banking sector health index was expected to improve gradually, according to the Expert RA estimates. For the period between July 2021 and July 2022, the index was projected to reach 91.3 percent.

The RHPI measures price changes of single-family properties, adjusted for the impact of inflation. Real values are calculated using the so-called Personal Consumption Expenditure Deflator (PCE). This PCE, so the theory goes, includes expenditures that are not counted in the Consumer Price Index(CPI), such as medical and health care expenses paid by employers and other national health programs. Because the RHPI adjusts for house-buying power, it is also a measure of housing affordability. In the fourth quarter of 2022, housing prices in real terms in Luxembourg reached an index of approximately 187.5 index points.

The average transaction price of new housing in Europe was the highest in Norway, whereas existing homes were the most expensive in Austria. Since there is no central body that collects and tracks transaction activity or house prices across the whole continent or the European Union, not all countries are included. To compile the ranking, the source weighed the transaction prices of residential properties in the most important cities in each country based on data from their national offices. For example, in Germany, the cities included were Munich, Hamburg, Frankfurt, and Berlin. House prices have been soaring, with Sweden topping the ranking Considering the RHPI of houses in Europe (the price index in real terms, which measures price changes of single-family properties adjusted for the impact of inflation), however, the picture changes. Sweden, Luxembourg and Norway top this ranking, meaning residential property prices have surged the most in these countries. Real values were calculated using the so-called Personal Consumption Expenditure Deflator (PCE), This PCE uses both consumer prices as well as consumer expenditures, like medical and health care expenses paid by employers. It is meant to show how expensive housing is compared to the way of living in a country. Home ownership highest in Eastern Europe The home ownership rate in Europe varied from country to country. In 2020, roughly half of all homes in Germany were owner-occupied whereas home ownership was at nearly 97 percent in Romania or around 90 percent in Slovakia and Lithuania. These numbers were considerably higher than in France or Italy, where homeowners made up 65 percent and 72 percent of their respective populations.For more information on the topic of property in Europe, visit the following pages as a starting point for your research: real estate investments in Europe and residential real estate in Europe.

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Europe Commercial Real Estate Market Size 2025-2029

The Europe commercial real estate market size is forecast to increase by USD 91.4 billion at a CAGR of 5.7% between 2024 and 2029.

The European commercial real estate market is experiencing significant growth, with increasing private investment flowing into the region. This trend is driven by a number of factors, including the economic stability of European countries, attractive yields compared to other global markets, and the continued demand for urban space. However, this growth is not without challenges. 
One major concern is the rising interest rates, which have the potential to increase borrowing costs for investors and potentially dampen demand. Despite this, opportunities abound for companies seeking to capitalize on the market's dynamics. For instance, there is a growing demand for sustainable real estate, as well as a shift towards alternative asset classes such as student housing, healthcare real estate, and hospitality real estate.
To navigate this complex landscape effectively, companies must stay informed of the latest trends and challenges, and be prepared to adapt their strategies accordingly. Overall, the European commercial real estate market offers significant opportunities for growth, but also requires a strategic and agile approach to succeed.

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The European commercial real estate market encompasses a diverse landscape of travel-restriction resilient sectors, including warehouses and fulfillment centers catering to the in e-commerce spending. Urbanization continues to drive demand for adaptable office spaces in metro cities, with a growing emphasis on sustainable designs and technology-driven solutions. The commercial sector is undergoing digitalization, with brokers and managers leveraging media portals to streamline transactions and enhance client experiences. The hybrid work model is shaping office occupancy trends, as middle-class consumers and the working-age population adapt to flexible work arrangements. Foreign investments remain strong, particularly in sectors like logistics and data centers.
Vacancy rates, rental rates, absorption rates, and property valuations are closely monitored indicators of market health. Architects and engineers are tasked with designing spaces that accommodate the evolving needs of businesses, from flexible layouts to energy efficiency. Overall, the European commercial real estate market exhibits activity and growth, with trends leaning towards digitalization, sustainability, and adaptability.

How is this market segmented?

The market research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

Type

  Rental
  Lease
  Sales


End-user

  Offices
  Retail
  Leisure
  Others


Geography

  Europe

    France
    Germany
    Italy
    UK

By Type Insights

The rental segment is estimated to witness significant growth during the forecast period. The European commercial real estate market is experiencing a significant shift, with the rental segment leading the way in 2024. Office rental growth in Europe accelerated to 1.8% quarter-on-quarter in Q3 2022, resulting in an annual increase of over 5%. Notably, the UK, Benelux markets, and peripheral Europe experienced the highest growth rates. However, investment markets are showing caution, as buyers hesitate to pay earlier price levels due to economic uncertainties, inflation, and finance rates. Urbanization and social distancing measures continue to impact commercial real estate, driving the need for adaptable office spaces and sustainable designs. The commercial sector is also undergoing digitalization, with technology-driven solutions, smart building technology, and data analytics gaining popularity.

Additionally, e-commerce spending and changing customer behavior are leading to increased demand for warehouses, fulfillment centers, and logistics facilities. The Middle-class consumers and the working-age population's digitization of work further fuel the demand for managed office facilities, collaborative spaces, and digital infrastructure. Key trends include hybrid work patterns, energy-efficient features, green building certifications, and sustainable construction methods.

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The rental segment was valued at USD billion in 2019 and showed a gradual increase during the forecast period.

Market Dynamics

The Europe commercial real estate market is diverse, encompassing a wide range of property types, from office space leasing to industrial warehouse sites. Retail property deals and urban retail units remain a signifi

During the COVID-19 pandemic, the number of house sales in the UK spiked, followed by a period of decline. In 2023, the housing market slowed notably, and in September 2024, transaction volumes fell below 50,000. House sales volumes are affected by a number of factors, including mortgage rates, house prices, supply, demand, as well as the overall health of the market. The economic uncertainty and rising unemployment rates has also affected the homebuyer sentiment of Brits. How have UK house prices developed over the past 10 years? House prices in the UK have increased year-on-year since 2015, except for a brief period of decline in the second half of 2023 and the beginning of 2024. That is based on the 12-month percentage change of the UK house price index. At the peak of the housing boom in 2022, prices soared by nearly 14 percent. The decline that followed was mild, at under three percent. The cooling in the market was more pronounced in England and Wales, where the average house price declined in 2023. Conversely, growth in Scotland and Northern Ireland continued. What is the impact of mortgage rates on house sales? For a long period, mortgage rates were at record-low, allowing prospective homebuyers to take out a 10-year loan at a mortgage rate of less than three percent. In the last quarter of 2021, this period came to an end as the Bank of England rose the bank lending rate to contain the spike in inflation. Naturally, the higher borrowing costs affected consumer sentiment, urging many homebuyers to place their plans on hold and leading to a drop in sales.

Moran’s Index between housing prices and the health determinants.

The purpose of this study was to understand the relationship between happiness and housing prices in Canada. The happiness data were obtained from the General Social Survey between 2009 and 2013, asking respondents to report overall happiness level by using scale ranging between 1 to 10 points. House Price Indexes at the provincial level were constructed to cover the same period. The relationship between average house price change and average happiness was estimated using Ordinary Least Square and Logistic Regression techniques. Individual's characteristics were used as control variables. The study found that average happiness level is positively and significantly related to the change in housing prices for one group and not for another - for homeowners but not for renters. In addition, individuals with better health are much happier than individuals with poor health. Similarly, individuals with higher income are happier than individuals with less income. The implication of this study is that the government should design attractive policies to encourage homeownerships.

In 2023, the U.S. GDP increased from the previous year to about 27.36 trillion U.S. dollars. This increase in GDP can be attributed to a continued rebound from the impact of the coronavirus pandemic. Gross domestic product (GDP) refers to the market value of all goods and services produced within a country. In 2023, the United States has the largest economy in the world. See, for example, the Russian GDP for comparison.

What is GDP? Gross domestic product is one of the most important indicators used to analyze the health of an economy. GDP is defined by the BEA as the market value of goods and services produced by labor and property in the United States, regardless of nationality. It is the primary measure of U.S. production. The OECD defines GDP as an aggregate measure of production equal to the sum of the gross values added of all resident, institutional units engaged in production (plus any taxes, and minus any subsidies, on products not included in the value of their outputs).

GDP and national debt

Although the United States had the highest Gross Domestic Product (GDP) in the world in 2022, this does not tell us much about the quality of life in any given country. GDP per capita at purchasing power parity (PPP) is an economic measurement that is thought to be a better method for comparing living standards across countries because it accounts for domestic inflation and variations in the cost of living.

While the United States might have the largest economy, the country that ranked highest in terms of GDP at PPP was Luxembourg, amounting to around 141,333 international dollars per capita. Singapore, Ireland, and Qatar also ranked highly on the GDP PPP list, and the United States ranked 9th in 2022.

BackgroundWhere the data come fromThe Mortgage Performance Trends data come from the NMDB, a joint project we’ve undertaken with the Federal Housing Finance Agency (FHFA). For more information, visit the NMDB program page .The core data in the NMDB come from data maintained by one of the top three nationwide credit repositories. The NMDB has a nationally representative, 5 percent sample of all outstanding, closed-end, first-lien, 1–4 family residential mortgages.The data and analyses presented herein are the sole product of the CFPB. Use of information downloaded from our website, and any alteration or representation regarding such information by a party, is the responsibility of such party.Why the data matterMortgage delinquency rates reflect the health of the mortgage market, and the health of the overall economy.The 30–89 mortgage delinquency rate is a measure of early stage delinquencies. It generally captures borrowers that have missed one or two payments. This rate can be an early indicator of mortgage market health. However, this rate is seasonally volatile and sensitive to temporary economic shocks.The 90–day delinquency rate is a measure of serious delinquencies. It generally captures borrowers that have missed three or more payments. This rate measures more severe economic distress.PrivacyThe Mortgage Performance Trends data have many protections in place to protect personal identity. Before the CFPB or the FHFA receive any data for the NMDB, all records are stripped of information that might reveal a consumer’s identity, such as names, addresses, and Social Security numbers. All data shown are aggregated by state, metropolitan statistical area, or county.

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US Residential Construction Market Size 2025-2029

The residential construction market size in the US is forecast to increase by USD 242.9 million at a CAGR of 4.5% between 2024 and 2029.

The residential construction market is experiencing significant growth, driven by several key factors. Firstly, the increasing household formation rates in the US continue to fuel demand for new housing units. Secondly, there is a rising focus on sustainability in residential construction projects, with homebuilders increasingly adopting energy-efficient and eco-friendly building materials and practices.
However, the market also faces challenges, including a shortage of skilled labor for large-scale residential real estate projects, which can impact project timelines and budgets. These trends and challenges are shaping the future of the residential construction industry in the US.

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The residential construction market is experiencing a significant shift as the affordable housing trend gains momentum. The Federal Reserve's decision to keep the federal funds rate low has contributed to a decrease in mortgage rates, making it an opportune time for home buyers to enter the market. However, the housing supply remains a concern, with construction spending in the residential investment sector showing only modest growth. The labor market's current state is another factor influencing the residential construction industry. With a low unemployment rate, there is a high demand for labor, leading to increased wages and, in turn, higher construction costs.
Inflation also poses a challenge, as it erodes the purchasing power of home buyers and builders alike. The economy's overall health plays a crucial role in the residential construction market's dynamics. A strong economy typically leads to increased demand for new homes, as evidenced by the double-digit growth in housing starts and building permits for single-family homes. However, a recession can lead to a significant decrease in construction activity, as seen in the cancellation rate of housing projects. The Federal Reserve's interest rate decisions, inflation, and the economy's health all impact the residential construction market. Affordable housing programs, such as housing choice vouchers and fair housing programs, play a vital role in ensuring access to housing for a broader population. The construction sectors must navigate these market dynamics to remain competitive and meet the demand for new homes.
The US residential construction market is seeing significant shifts, driven by various housing market trends. Sustainable homebuilding practices are gaining momentum, with a focus on energy-efficient homes and green building materials. Modular construction and prefab housing are becoming increasingly popular for their cost-effective and timely solutions. Urban redevelopment projects are revitalizing city areas, while suburban expansion is fueling demand for new homes. Affordable housing projects are crucial in addressing housing shortages, and real estate investment continues to thrive in these sectors. Smart home integration is also on the rise, with luxury home construction embracing high-tech features. The impact of mortgage rates, coupled with multifamily housing growth and home renovation demand, adds complexity to the market's dynamics.

How is this market segmented and which is the largest segment?

The market research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

Product

  Apartments and condominiums
  Villas
  Other types


Type

  New construction
  Renovation


Application

  Single family
  Multi-family


Geography

  US

By Product Insights

The apartments and condominiums segment is estimated to witness significant growth during the forecast period.

The residential construction market in the US is experiencing growth in the apartment and condominium sectors, driven by shifting preferences and lifestyle choices. Urbanization is a significant factor fueling this trend, as more individuals opt for the conveniences and amenities offered in urban areas. As a result, developers are constructing modern, sustainable, and community-focused living spaces in the form of high-rise apartment buildings and condominium complexes. These structures cater to various demographics, including intergenerational groups and younger generations, reflecting diverse living circumstances. The labor economy and vaccination rates have also contributed to the continued activity in the residential sector, allowing for steady progress in construction projects. While the non-residential sector has faced challenges, the residential sector remains a vi

The number of Mortgages that are 90 or more days delinquent refers to the count of home loans where borrowers have missed payments for at least three consecutive months. This data is crucial in assessing the health of the housing market and the financial stability of borrowers. The delinquency rate serves as an indicator of potential defaults and financial distress among homeowners.

This dataset focuses on mortgages that are 90 or more days delinquent at the county level across the United States, spanning from January 2008 to September 2019. Mortgages that are 90 or more days delinquent represent loans secured by real estate (typically homes) where borrowers have not made their mortgage payments for at least 90 days or more. This delinquency period is a critical threshold in the mortgage industry and is often an indicator of financial distress for homeowners. Understanding these delinquencies is crucial for assessing the financial health of homeowners and the housing market within various regions, aiding in economic analysis and policy formulation.

United Kingdom HICPH: Health Insurance data was reported at 117.506 2015=100 in Jun 2018. This stayed constant from the previous number of 117.506 2015=100 for May 2018. United Kingdom HICPH: Health Insurance data is updated monthly, averaging 81.666 2015=100 from Jan 2005 (Median) to Jun 2018, with 162 observations. The data reached an all-time high of 117.506 2015=100 in Jun 2018 and a record low of 52.021 2015=100 in Mar 2005. United Kingdom HICPH: Health Insurance data remains active status in CEIC and is reported by Office for National Statistics. The data is categorized under Global Database’s UK – Table UK.I002: Harmonised Index of Consumer Prices: 2015=100: incl Owner Occupiers Housing Costs.

Revenue for the Real Estate Development and Management industry in China is expected to decrease at a CAGR of 3.9% over the five years through 2024. This trend includes an expected decrease of 2.3% in the current year.Since August 2020, the People's Bank of China and the China Banking and Insurance Regulatory Commission have proposed three debt indicators for real estate development and management companies through which the company's financial health can be rated. This new policy has exacerbated the company's debt pressure, making it unable to repay old debts by borrowing new debt. Some real estate companies faced a liquidity crisis.In 2022, the city's lockdown and laying-off caused by COVID-19 epidemic led to the pressure of delaying the delivery of houses. The industry's newly constructed and completed areas decreased significantly throughout the year. In addition, the epidemic has impacted sales in the real estate development and management industry, and some sales offices have been forced to close temporarily. In 2022, the sales area of commercial housing decreased by 24.3%, and the sales of commercial housing decreased significantly by 29.8%.Industry revenue will recover at an annualized 3.4% over the five years through 2029. Over the next five years, the industry's drag on GDP will weaken, and industry growth will stabilize. However, high housing prices have become a major social problem in China. Under the measures on the principle that residential real estate is used for living, not speculation, the financial attributes of real estate will gradually weaken, and housing prices will tend to stabilize.

This metadata document provides details of the data used for the dissertation: “Improving Commercial Property Price Statistics”. The study explores data related and methodological challenges in the construction of price statistics for commercial real estate.

Short abstract of the dissertation

Since the financial crisis of 2008, National Statistical Institutes (NSIs) have worked to develop commercial real estate (CRE) indicators for official statistics. These indicators are considered essential in financial stability monitoring and may help contain the consequences of future crises or even prevent future crises. However, progress at NSIs to develop these indicators has been slow due to challenges like low observation numbers and high heterogeneity. This dissertation addresses these challenges by exploring data issues and suggesting methodological improvements.

The first three studies focus on data challenges regarding share deals and portfolio sales. Both are real estate trading constructions that are specific to CRE. The results show that share deals and portfolio sales significantly differ from the rest of the market. Therefore, under specific circumstances, CRE indicators could benefit from including these trading types. The final two studies focus on methodological challenges regarding index construction methods and the role of sustainability in real estate pricing. The results show that, by combining established techniques, it is possible to construct price indices that meet official statistics’ standards. Furthermore, the results uncover a complex relationship between sustainability and prices: while energy efficiency generally involves price premiums, others aspects like health and environment display a discount for low sustainable properties.

Overall, this dissertation contributes to the legislative framework that is currently being developed for EU countries to publish official statistics for commercial real estate and adds to the academic discussion by presenting innovative techniques for data analyses and index construction.

Data sources

The following data sources were used:

1. Bussiness Register (Statistics Netherlands)
2. Transactions linked to the Register of Adresses and Buildings (BAG)
3. Linking table buildings and companies (Dutch Land Registry Office)
4. Property Transfer Tax data (Dutch Tax Authorities)
5. Building sustainability scores (W/E advisors)Commercial real estate transactions (Dutch Land Registry Office)
6. Commercial real estate transactions (Dutch Land Registry Office)

Processing methodology

1. The data is originally stored in an SQL database and is processed with SQL and R code (version 4.2). In the code, the name of the table is tbl_SPE_2_ABR_Bedrijfsinfo. The data is used for deriving company transfers by comparing ownership states of various periods. The first period that an ownership differs of the same company indicates an ownership transfer.
2. The data is originally stored in an SQL database and is processed with SQL and R code (version 4.2). In the code, the name of the table is tbl_SPE_6_ABR_CompleetMicro. The data is used for calcuting the size of real estate share deals and estimating price developments by applying appropriate filters and counting the output.
3. The data is originally stored in an SQL database and is processed with R code (version 4.2). In the code, the name of the table is SPE_KADASTER. The data is used for finding real estate information that corresponds to company transfers by linking the company register (ABR) to the real estate register (BAG).
4. The data is originally stored in an SQL database and is processed with R code (version 4.2). In the code, the name of the table is tbl_SPE_3_OVB_Bedrijfsinfo. The data is used for deriving real estate share deals by linking this table (Kadaster) to the real estate register (BAG).
5. The data is originally stored in an SQL database and is processed with R code (version 4.2). In the code, the name of the table is duurzaamheid_input_regressie2. The data is used for finding the relationship between sustainabilty measures and real estate transaction prices by linking sustainabilty scores from a consultancy (WE) to transaction prices (Cadastre) and running regression analyses.
6. The data is originally stored in an SQL database and is processed with R code (version 4.2). In the code, the name of the table is tbl_OV20_pand. The data is used for 4 purposes (separate studies).

• (1) Chapter 3: Determining the price effect of portfolio sale by running regression analyses
• (2) Chapter 4: Developing methods to include portfolio sales in CPPI calcutions by using auxilary data of the real estate properties.
• (3) Chapter 5: Developing a price index method for small domains by using these data to test the outcomes
• (4) Chapter 6: Determining the relationship between sustatinability by running regression analyses

Data restrictions

As part of the CBS law, sharing micro-data outside of the CBS-environment is prohibited. Furthermore, CBS manages the data, but in some cases other parties are still formal owners of the data. The 2 other parties are The Land Registry Office and WE consultancy. Ownership and intellectual property rights are managed in contracts with both owners. It was agreed upon that the data can only be used for the purpose of the PhD study and that the microdata will never be externally disseminated. The data is still owned by them and the intellectual property rights of the analyses belong to me. An intended use of the microdata should be approved by both Statistics Netherlands and the formal data owner. Because of the above, no data can be publicly shared.

If one intends to do research on these data, an application for data use can be requested at CBS. CBS will charge costs for anonymising the data and providing a closed environment to work with the data. More information on this can be found at: https://www.cbs.nl/en-gb/our-services/customised-services-microdata/microdata-conducting-your-own-research

Contact information

Author: Farley Ishaak

Statistics Netherlands | Henri Faasdreef 312 | P.O. Box 24500 | 2490 HA The Hague

TU Delft | Delft University of Technology | Faculty of Architecture and the Built Environment

Department of Management in the Built Environment | P.O. Box 5043 | 2600 GA Delft

M +31 6 46307974 | ff.ishaak@cbs.nl | f.f.ishaak@tudelft.nl

In 2024, the estimated value of the global commercial real estate market was over 38.5 trillion U.S. dollars, up from 36.7 trillion U.S. dollars the year before. The North America region had the largest market size, valued at over 13 trillion U.S. dollars, slightly higher than Asia-Pacific and Europe, Middle East, and Africa (EMEA). What is the market size of listed commercial real estate? The listed real estate market comprises real estate companies that are traded on stock exchanges and varies across different regions. In 2023, the size of the listed real estate market was about 3.2 trillion U.S. dollars, with the North America region comprising the largest share. Which real estate sector is most popular for investment? Real estate has earned itself a good name as an investment vehicle among Ultra-High-Net-Worth Individuals (UHNWIs). In 2024, some of the real estate sectors increasingly attracting UHNWI’s interest were healthcare and education properties.

Abstract

The most recent estimate of monetary poverty in Armenia found that nearly 30 percent of the population lives below the national poverty threshold. However, because the Armenian social protection system provides some, though limited, basic support, monetary measures provide only a partial picture of the negative effects of poverty on well-being and the lack of positive capabilities.

In 2013, the National Statistical Service of the Republic of Armenia and the World Bank began work on a national measure of multidimensional poverty to supplement the consumption poverty indicator. This measure, which was identified through consultations with many stakeholders in Armenia, reflects deprivations specific to Armenia in the areas of education, health, labor, housing conditions, and basic needs. The approach offers insights into the complexity, depth, and persistence of poverty in the country; tailoring it specifically to the country context enhances its relevance for policy.

The national measure of multidimensional poverty for Armenia uses the Alkire-Foster approach.This tailored measure is not intended to be used in international comparisons; it is simply representative of the country and its specific development challenges. For every multidimensional measure, the dimensions, weights, and a method for aggregation must be selected.

The first step in constructing the measure of multidimensional poverty is to select dimensions that reflect achievements or deprivations. These indicators complement the national monetary poverty measure with information that better captures nonmonetary aspects of well-being. The primary dimensions of the measure are basic needs, housing, education, labor, and health.

The datasets documented here include 2010-2015 national multidimensional poverty indices, constructed using Armenia Integrated Living Conditions Survey (ILCS) data from 2010 to 2015.

Geographic coverage

National, urban-rural-Yerevan levels

Analysis unit

• household

Kind of data

Sample survey data [ssd]

Sampling procedure

Each year Integrated Living Conditions Survey (ILCS) interviews more than 5,000 households; is representative at the regional level (marz level, which corresponds to the NUTS 3 regions); and provides comparable data starting from the early 2000s.

Mode of data collection

Face-to-face [f2f]

Research instrument

The Integrated Living Conditions Survey (ILCS) asks about education, labor market outcomes, health behavior, and living conditions of households and individuals. It also collects detailed data on consumption behavior and is used to calculate Armenia's official poverty rate. Since the measure of multidimensional poverty is meant to complement the analysis of consumption poverty, using the same survey instrument is crucial. On the other hand, a serious drawback of using existing rather than new data-constructing the measure on multidimensional poverty is limited by the ILCS information available.

The Jarque-Bera statistic tests the null hypothesis of normality for the sample returns.