A nursing home is commonly referred to as a skilled nursing facility, long term care (LTC) facility, or rest home, and may have a different standardized name throughout the United States, but is most commonly referred to as a nursing home. A nursing home traditionally offers 24-hour (skilled) nursing to the elderly or to disabled patients having a variety of medical conditions who require personal care services above that of an assisted living but do not require hospitalization. The personal care services provided may or may not include, but are not limited to: skilled nursing, long term inpatient care, room and board, meals, laundry, and assistance with: dressing, grooming, getting in and out of bed, medications, bathing, and toileting. For purposes of this dataset, an assisted living facility is defined as a facility where the elderly, who are not related to the operator, reside and receive care, treatment, or services. Although not at the level of a nursing home, the services are above the level of an independent living community. They may include several hours per week of supportive care, personal care, or nursing care per resident. Generally, an assisted living facility offers help in daily living (laundry, cooking, cleaning, etc.) and personal assistance (bathing, eating, clothing, etc.). Many assisted living facilities offer assistance with medication and a lesser level of nursing care than what is offered at a nursing home. Assisted living facilities may be regulated by size restrictions depending on which type of assisted living facility it is considered to be in the state in which it exists. For example, Adult Family Homes in Wisconsin have between 3-4 elderly residents while Community Based Residential Facilities have 5 or more. Almost every state has different terminology to describe their version of the assisted living facility system. The structures in which assisted living facilities exist are varied as well. Depending on the type, an assisted living facility may operate out of a personal residence or a nursing home style structure, and it may be set up as apartment style living or as a campus setting in a continuing care retirement community. Multiple assisted living facilities may exist at one location or may be co-located with nursing homes and/or other similar health care facilities. If a facility is licensed by a state and holds multiple licenses, it is represented once in this dataset for each license, even if the licenses are for the same location. This dataset does not include retirement communities, adult daycare facilities, or rehabilitation facilities. Nursing Homes that are operated by and co-located with a hospital are also excluded because the locations are included in the hospital dataset. Records with "-DOD" appended to the end of the [NAME] value are located on a military base, as defined by the Defense Installation Spatial Data Infrastructure (DISDI) military installations and military range boundaries. "#" and "*" characters were automatically removed from standard fields populated by TechniGraphics. Double spaces were replaced by single spaces in these same fields. Text fields in this dataset have been set to all upper case to facilitate consistent database engine search results. All diacritics (e.g., the German umlaut or the Spanish tilde) have been replaced with their closest equivalent English character to facilitate use with database systems that may not support diacritics. The currentness of this dataset is indicated by the [CONTDATE] field. Based on this field, the oldest record dates from 09/22/2009 and the newest record dates from 01/08/2010.

Hospitals in New Mexico The term "hospital" ... means an institution which- (1) is primarily engaged in providing, by or under the supervision of physicians, to inpatients > (A) diagnostic services and therapeutic services for medical diagnosis, treatment, and care of injured, disabled, or sick persons, or > (B) rehabilitation services for the rehabilitation of injured, disabled, or sick persons; (...) (5) provides 24-hour nursing service rendered or supervised by a registered professional nurse, and has a licensed practical nurse or registered professional nurse on duty at all times; ... (...) (7) in the case of an institution in any State in which State or applicable local law provides for the licensing of hospitals, > (A) is licensed pursuant to such law or > (B) is approved, by the agency of such State or locality responsible for licensing hospitals, as meeting the standards established for such licensing; (Excerpt from Title XVIII of the Social Security Act [42 U.S.C. § 1395x(e)], http://www4.law.cornell.edu/uscode/html/uscode42/usc_sec_42_00001395---x000-.html) Included in this dataset are General Medical and Surgical Hospitals, Psychiatric and Substance Abuse Hospitals, and Specialty Hospitals (e.g., Children's Hospitals, Cancer Hospitals, Maternity Hospitals, Rehabilitation Hospitals, etc.). TGS has made a concerted effort to include all general medical/surgical hospitals in New Mexico. Other types of hospitals are included if they were represented in datasets sent by the state. Therefore, not all of the specialty hospitals in New Mexico are represented in this dataset. Hospitals operated by the Veterans Administration (VA) are included, even if the state they are located in does not license VA Hospitals. Nursing homes and Urgent Care facilities are excluded because they are included in a separate dataset. Locations that are administrative offices only are excluded from the dataset. Records with "-DOD" appended to the end of the [NAME] value are located on a military base, as defined by the Defense Installation Spatial Data Infrastructure (DISDI) military installations and military range boundaries. Text fields in this dataset have been set to all upper case to facilitate consistent database engine search results. All diacritics (e.g., the German umlaut or the Spanish tilde) have been replaced with their closest equivalent English character to facilitate use with database systems that may not support diacritics. The currentness of this dataset is indicated by the [CONTDATE] field. Based upon this field, the oldest record dates from 06/16/2008 and the newest record dates from 06/27/2008

Background We translated the Canadian residential long term care versions of the Alberta Context Tool (ACT) and the Conceptual Research Utilization (CRU) Scale into German, to study the association between organizational context factors and research utilization in German nursing homes. Both instruments are self-report questionnaires used with care providers working in nursing homes. Our aim was to assess the factor structure, reliability, and measurement invariance between care provider groups responding to these instruments. Methods In a stratified random sample of 38 nursing homes in one German region (Metropolregion Rhein-Neckar), we collected questionnaires from 273 care aides, 196 regulated nurses, 152 allied health providers, 6 quality improvement specialists, 129 clinical leaders, and 65 nursing students. The factor structure was assessed using confirmatory factor models. The first model included all ten Alberta Context Tool concepts. We also decided a priori to run two separate models for the scale-based and the count-based Alberta Tool concepts as suggested by the instrument developers. The fourth model included the five Conceptual Research Utilization Scale items. Reliability scores were calculated based on the parameters of the best-fitting factor models. Multiple-group confirmatory factor models were used to assess measurement invariance between the provider groups. Results Rather than the hypothesized ten-factor structure of the Alberta Context Tool, confirmatory factor models suggested thirt een factors. The one-factor solution of the Conceptual Research Utilization Scale was confirmed. The reliability was acceptable (> .7 in the entire sample and in all provider groups) for 10 of 13 Alberta Context Tool concepts. The reliability of the Conceptual Research Utilization Scale was high (.90 to .96). We could demonstrate partial strong measurement invariance for both Alberta Context Tool models and partial strict measurement invariance for the Conceptual Research Utilization Scale. Conclusions Our results suggest that the scores of the German ACT and the CRU Scale for nursing homes are acceptably reliable and valid. However, as the ACT lacked strict measurement invariance, observed variables (or scale scores based on them) cannot be compared between provider groups. Rather, group comparisons should be based on latent variable models, which consider the different residual variances of each group.

BackgroundThe delivery of high quality care is a fundamental goal for health systems worldwide. One policy tool to ensure quality is the regulation of services by an independent public authority. This systematic review seeks to identify determinants of compliance with such regulation in health and social care services.MethodsSearches were carried out on five electronic databases and grey literature sources. Quantitative, qualitative and mixed methods studies were eligible for inclusion. Titles and abstracts were screened by two reviewers independently. Determinants were identified from the included studies, extracted and allocated to constructs in the Consolidated Framework for Implementation Research (CFIR). The quality of included studies was appraised by two reviewers independently. The results were synthesised in a narrative review using the constructs of the CFIR as grouping themes.ResultsThe search yielded 7,500 articles for screening, of which 157 were included. Most studies were quantitative designs in nursing home settings and were conducted in the United States. Determinants were largely structural in nature and allocated most frequently to the inner and outer setting domains of the CFIR. The following structural characteristics and compliance were found to be positively associated: smaller facilities (measured by bed capacity); higher nurse-staffing levels; and lower staff turnover. A facility’s geographic location and compliance was also associated. It was difficult to make findings in respect of process determinants as qualitative studies were sparse, limiting investigation of the processes underlying regulatory compliance.ConclusionThe literature in this field has focused to date on structural attributes of compliant providers, perhaps because these are easier to measure, and has neglected more complex processes around the implementation of regulatory standards. A number of gaps, particularly in terms of qualitative work, are evident in the literature and further research in this area is needed to provide a clearer picture.

Snapshot img

Residential Real Estate Market Size 2025-2029

The residential real estate market size is forecast to increase by USD 485.2 billion at a CAGR of 4.5% between 2024 and 2029.

The market is experiencing significant growth, fueled by increasing marketing initiatives that attract potential buyers and tenants. This trend is driven by the rising demand for housing solutions that cater to the evolving needs of consumers, particularly in urban areas. However, the market's growth trajectory is not without challenges. Regulatory uncertainty looms large, with changing policies and regulations posing a significant threat to market stability. Notably, innovative smart home technologies, such as voice-activated assistants and energy-efficient appliances, are gaining traction, offering enhanced convenience and sustainability for homeowners.
As such, companies seeking to capitalize on the opportunities presented by the growing the market must navigate these challenges with agility and foresight. The residential construction industry's expansion is driven by urbanization and the rising standard of living in emerging economies, including India, China, Thailand, Malaysia, and Indonesia. By staying abreast of regulatory changes and implementing innovative marketing strategies, they can effectively meet the evolving needs of consumers and maintain a competitive edge. These regulatory shifts can impact everything from property prices to financing options, making it crucial for market players to stay informed and adapt quickly.

What will be the Size of the Residential Real Estate Market during the forecast period?

Explore in-depth regional segment analysis with market size data - historical 2019-2023 and forecasts 2025-2029 - in the full report.
Request Free Sample

In the dynamic housing market analysis, small flats continue to be a popular choice for both investors and first-time homebuyers, driven by affordability and urban growth. International investment in housing projects, including apartments and condominiums, remains strong, offering attractive investment returns. Real estate syndication and property management software facilitate efficient property ownership and management. Real estate loans, property insurance, and urban planning are essential components of the housing market, ensuring the development of affordable housing and addressing the needs of the middle class and upper middle class. Property disputes, property tax assessments, and real estate litigation are ongoing challenges, requiring careful attention from stakeholders.
Property search engines streamline the process of finding the perfect property, from studio apartments to luxury homes. Real estate auctions, land banking, and nano apartments are innovative solutions in the market, while property flipping and short sales provide opportunities for savvy investors. Urban growth and community development are key trends, with a focus on sustainable, planned cities and the integration of technology, such as real estate blockchain, into the industry. Developers secure building permits, review inspection reports, and manage escrow accounts during real estate transactions. Key services include contract negotiation, dispute resolution, and tailored investment strategies for portfolio management. Financial aspects cover tax implications, estate planning, retirement planning, taxdeferred exchanges, capital gains, tax deductions, and maintaining positive cash flow for sustained returns.

How is this Residential Real Estate Industry segmented?

The residential real estate industry 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.

Mode Of Booking

  Sales
  Rental or lease


Type

  Apartments and condominiums
  Landed houses and villas


Location

  Urban
  Suburban
  Rural


End-user

  Mid-range housing
  Affordable housing
  Luxury housing


Geography

  North America

    US
    Canada
    Mexico


  Europe

    France
    Germany
    UK


  APAC

    Australia
    Japan
    South Korea


  South America

    Brazil


  Rest of World (ROW)

By Mode Of Booking Insights

The sales segment is estimated to witness significant growth during the forecast period. The sales segment dominates the global residential real estate market and will continue to dominate during the forecast period. The sales segment includes the sale of any property that is majorly used for residential purposes, such as single-family homes, condos, cooperatives, duplexes, townhouses, and multifamily residences. With the growing population and urbanization, the demand for homes is also increasing, which is the major factor driving the growth of the sales segment. Moreover, real estate firms work with developers to sel

Hospitals in Kansas

The term "hospital" ... means an institution which-

(1) is primarily engaged in providing, by or under the supervision of physicians, to inpatients

(A) diagnostic services and therapeutic services for medical diagnosis, treatment, and care of injured, disabled, or sick persons, or (B) rehabilitation services for the rehabilitation of injured, disabled, or sick persons;

(...)

(5) provides 24-hour nursing service rendered or supervised by a registered professional nurse, and has a licensed practical nurse or registered professional nurse on duty at all times; ...

(...)

(7) in the case of an institution in any State in which State or applicable local law provides for the licensing of hospitals,

(A) is licensed pursuant to such law or (B) is approved, by the agency of such State or locality responsible for licensing hospitals, as meeting the standards established for such licensing;

(Excerpt from Title XVIII of the Social Security Act [42 U.S.C. § 1395x(e)], )

Included in this dataset are General Medical and Surgical Hospitals, Psychiatric and Substance Abuse Hospitals, and Specialty Hospitals (e.g., Children's Hospitals, Cancer Hospitals, Maternity Hospitals, Rehabilitation Hospitals, etc.).

TGS has made a concerted effort to include all general medical/surgical hospitals in Kansas. Other types of hospitals are included if they were represented in datasets sent by the state. Therefore, not all of the specialty hospitals in Kansas are represented in this dataset.

Hospitals operated by the Veterans Administration (VA) are included, even if the state they are located in does not license VA Hospitals.

Nursing homes and Urgent Care facilities are excluded because they are included in a separate dataset. Locations that are administrative offices only are excluded from the dataset.

Records with "-DOD" appended to the end of the [NAME] value are located on a military base, as defined by the Defense Installation Spatial Data Infrastructure (DISDI) military installations and military range boundaries.

Text fields in this dataset have been set to all upper case to facilitate consistent database engine search results.

All diacritics (e.g., the German umlaut or the Spanish tilde) have been replaced with their closest equivalent English character to facilitate use with database systems that may not support diacritics.

The currentness of this dataset is indicated by the [CONTDATE] field. Based upon this field, the oldest record dates from 05/09/2006 and the newest record dates from 05/07/2008

BackgroundThe delivery of high quality care is a fundamental goal for health systems worldwide. One policy tool to ensure quality is the regulation of services by an independent public authority. This systematic review seeks to identify determinants of compliance with such regulation in health and social care services.MethodsSearches were carried out on five electronic databases and grey literature sources. Quantitative, qualitative and mixed methods studies were eligible for inclusion. Titles and abstracts were screened by two reviewers independently. Determinants were identified from the included studies, extracted and allocated to constructs in the Consolidated Framework for Implementation Research (CFIR). The quality of included studies was appraised by two reviewers independently. The results were synthesised in a narrative review using the constructs of the CFIR as grouping themes.ResultsThe search yielded 7,500 articles for screening, of which 157 were included. Most studies were quantitative designs in nursing home settings and were conducted in the United States. Determinants were largely structural in nature and allocated most frequently to the inner and outer setting domains of the CFIR. The following structural characteristics and compliance were found to be positively associated: smaller facilities (measured by bed capacity); higher nurse-staffing levels; and lower staff turnover. A facility’s geographic location and compliance was also associated. It was difficult to make findings in respect of process determinants as qualitative studies were sparse, limiting investigation of the processes underlying regulatory compliance.ConclusionThe literature in this field has focused to date on structural attributes of compliant providers, perhaps because these are easier to measure, and has neglected more complex processes around the implementation of regulatory standards. A number of gaps, particularly in terms of qualitative work, are evident in the literature and further research in this area is needed to provide a clearer picture.

The US Department of Homeland Security, Homeland Infrastructure Foundations - Level Data (HIFLD) provided geographic shapefiles for United States Urgent Care Facilities. This feature class/shapefile contains Urgent Care Facilities recognized by the US Department of Homeland Security within the US territories of Puerto Rico. Urgent Care Facilities Urgent care is defined as the delivery of ambulatory medical care outside of a hospital emergency department on a walk-in basis without a scheduled appointment. (Source: Urgent Care Association of America) The Urgent Care dataset consists of any location that is capable of providing emergency medical care and must provide emergency medical treatment beyond what can normally be provided by an EMS unit, must be able to perform surgery, or must be able to provide recuperative care beyond what is normally provided by a doctor's office. In times of emergency, the facility must be able to accept patients from the general population or patients from a significant subset of the general population (e.g., children). Although all Urgent Care facilities are intended to be included in this dataset, the newest facilities may not be included. This data set includes "mobile" urgent care center that provides urgent care to private residences, which is plotted at its administrative building. Entities that are excluded from this dataset are administrative offices, physician offices, workman compensation facilities, free standing emergency rooms, and hospitals. Urgent Care facilities that are operated by and co-located with a hospital are also excluded because the locations are included in the hospital dataset.

Records with "-DOD" appended to the end of the [NAME] value are located on a military base, as defined by the Defense Installation Spatial Data Infrastructure (DISDI) military installations and military range boundaries. At the request of NGA, text fields in this dataset have been set to all upper case to facilitate consistent database engine search results. At the request of NGA, all diacritics (e.g., the German umlaut or the Spanish tilde) have been replaced with their closest equivalent English character to facilitate use with database systems that may not support diacritics. The records within this dataset were compiled between 2004-11-22 through 2009-07-17.

The complete dataset for 50 States can be obtained from the HIFLD website: https://hifld-dhs-gii.opendata.arcgis.com/datasets/0d748999f5eb4e76a7e0389442381af6_0 The shape file metadata: https://www.arcgis.com/sharing/rest/content/items/0d748999f5eb4e76a7e0389442381af6/info/metadata/metadata.xml?format=default&output=html

The Veterans Health Administration Medical Facilities dataset includes Veteran Affairs hospitals, Veteran Affairs Residential Rehabilitation Treatment Programs (RRTP), Veteran Affairs Nursing Home Care Units (NHCU), Veteran Affairs Outpatient Clinics (VAOC), Vet Centers, and Veteran Affairs Medical Centers (VAMC). It should not include planned and suspended (non-operational) sites and mobile clinics. These definitions were set by the Veterans Health Administration (VHA) Policy Board in December 1998 and are the basis for defining the category and the additional service types for each VHA service site. These definitions cover sites generally owned by the Department of Veterans Affairs (VA) with the exception of leased and contracted community-based outpatient clinics (CBOCs).1. VA HOSPITAL: an institution (health care site) that is owned, staffed and operated by VA and whose primary function is to provide inpatient services. NOTE: Each geographically unique inpatient division of an integrated facility is counted as a separate hospital.2. VA RESIDENTIAL REHABILITATION TREATMENT PROGRAM (RRTP): provides comprehensive health and social services in a VA facility for eligible veterans who are ambulatory and do not require the level of care provided in nursing homes.3. VA NURSING HOME CARE UNITS (NHCU): provides care to individuals who are not in need of hospital care, but who require nursing care and related medical or psychosocial services in an institutional setting. VA NHCUs are facilities designed to care for patients who require a comprehensive care management system coordinated by an interdisciplinary team. Services provided include nursing, medical, rehabilitative, recreational, dietetic, psychosocial, pharmaceutical, radiological, laboratory, dental and spiritual.4. VA OUTPATIENT CLINICS:a. Community-Based Outpatient Clinic (CBOC): a VA-operated, VA-funded, or VA-reimbursed health care facility or site geographically distinct or separate from a parent medical facility. This term encompasses all types of VA outpatient clinics, except hospital-based, independent and mobile clinics. Satellite, community-based, and outreach clinics have been redefined as CBOCs. Technically, CBOCs fall into four Categories, which are: >(i) VA-owned. A CBOC that is owned and staffed by VA. >(ii) Leased. A CBOC where the space is leased (contracted), but is staffed by VA. NOTE: This includes donated space staffed by VA. >(iii) Contracted. A CBOC where the space and the staff are not VA. This is typically a Healthcare Management Organization (HMO)-type provided where multiple sites can be associated with a single station identifier. >(iv) Not Operational. A CBOC which has been approved by Congress, but has not yet begun operating.b. Hospital-Based Outpatient Clinic: outpatient clinic functions located at a hospital.c. Independent Outpatient Clinic: a full-time, self-contained, freestanding, ambulatory care clinic that has no management, program, or fiscal relationship to a VA medical facility. Primary and specialty health care services are provided in an outpatient setting.5. VET CENTER: Provides professional readjustment counseling, community education, outreach to special populations, brokering of services with community agencies, and access to links between the veteran and VA.6. VA MEDICAL CENTER (VAMC): a medical center is a unique VA site of care providing two or more types of services that reside at a single physical site location. The services provided are the primary service as tracked in the VHA Site Tracking (VAST) (i.e., VA Hospital, Nursing Home, Domiciliary, independent outpatient clinic (IOC), hospital-based outpatient clinic (HBOC), and CBOC). The definition of VA medical center does not include the Vet Centers as an identifying service. This dataset is based upon GFI data received from the National Geospatial-Intelligence Agency (NGA). At the request of NGA, text fields in this dataset have been set to all upper case to facilitate consistent database engine search results. At the request of NGA, all diacritics (e.g., the German umlaut or the Spanish tilde) have been replaced with their closest equivalent English character to facilitate use with database systems that may not support diacritics. The currentness of this dataset is indicated by the [CONTDATE] attribute. Based upon this attribute, the oldest record dates from 09/21/2007 and the newest record dates from 10/15/2007.

Determinants coded to the characteristics of individuals domain.

Determinants of regulatory compliance where evidence is most consistent.

The South Korean residential real estate market, valued at $345.19 million in 2025, is projected to experience robust growth, exhibiting a Compound Annual Growth Rate (CAGR) of 13.07% from 2025 to 2033. This expansion is driven by several factors. Firstly, a growing population, particularly in urban centers like Seoul, fuels increasing demand for housing. Secondly, government initiatives aimed at improving infrastructure and incentivizing homeownership contribute significantly to market expansion. Furthermore, a strengthening economy and rising disposable incomes empower more individuals to invest in residential properties. The market is segmented by property type (apartments and condominiums, landed houses and villas) and geography (Seoul and other locations), with Seoul expected to command a larger share due to its concentration of economic activity and population density. Competition is fierce amongst major players like Korea Land and Housing Corporation, Hines, and ShinYoung Greensys, leading to innovative developments and competitive pricing strategies. Potential restraints include government regulations on land usage, fluctuations in interest rates impacting mortgage accessibility, and global economic uncertainties that may influence investment flows. Despite these potential challenges, the long-term outlook for the South Korean residential real estate market remains positive. The continued urbanization trend and sustained economic growth are expected to counterbalance the restraining factors, ensuring consistent market expansion throughout the forecast period. The dominance of large developers combined with the increasing demand from a growing middle class will likely lead to a sustained period of elevated construction activity and transaction volumes. Furthermore, the focus on sustainable and technologically advanced housing solutions will likely shape future developments, creating opportunities for companies specializing in green building technologies and smart home integration. The market’s performance will closely track South Korea's overall economic health and government policies regarding housing affordability and urban planning. This report provides a detailed analysis of the South Korea residential real estate market, covering the period from 2019 to 2033. It examines market dynamics, trends, and future prospects, incorporating data from the historical period (2019-2024), base year (2025), and forecast period (2025-2033). The report is invaluable for investors, developers, policymakers, and anyone seeking a comprehensive understanding of this dynamic market. High-impact keywords such as South Korea real estate, Seoul apartments, Korean housing market, modular housing Korea, and residential real estate investment Korea are strategically integrated for enhanced search engine optimization. Recent developments include: January 2023: International architecture office KPF has unveiled the design for Parkside Seoul, a new mixed-use neighborhood planned for the South Korean capital to complement the surrounding natural elements and pay homage to Yongsan Park. The 482,600 square meter development is composed of a layered exterior envelope encompassing various programs and public amenities to enhance the residents’ experience of space. Besides the residential units, the complex includes office and retail spaces, hospitality facilities, and public and green spaces., April 2023: Korea’s GS E&C has launched its premium modular housing division, XiGEIST. GS E&C is a global entity that spans civil engineering, building, oil & gas, power plants, and renewable energy. They already own a high-end apartment brand, Xi, and they’re not new to the modular housing market, with acquisitions of some significant modular home companies in Poland, Britain, and the USA in recent years. Their modular homes will be manufactured at the company’s recently opened automated panelised prefabrication plant in South Korea, where they hope to achieve a 30% reduction in construction time, with a delivery timeline of eight weeks.. Key drivers for this market are: Government's Plans to Supply New Homes. Potential restraints include: Rising Interest Rates. Notable trends are: Urbanization in the Country is Driving the Market.

Determinants coded to the intervention characteristics domain.

The Real Estate Agency Franchises industry provides real estate services through franchisees, who pay franchisors royalty and renewal fees. The industry is grappling with significant challenges, including high residential property prices and escalating operational costs. The rapid increase in housing prices has created barriers for first-home buyers, decreasing transaction volumes and harming franchises’ revenue. Many prospective homeowners are either delaying their purchases or shifting their focus to more affordable options, like townhouses or apartments, diverting interest from higher-end properties traditionally marketed by franchises. Also, technology investments, increasing rental expenses for prime locations and compliance with evolving regulations are raising operational costs, constraining profitability. However, independent agencies are increasingly seeking affiliation with franchises so they can leverage their brand recognition and support systems to navigate a rapidly changing market landscape and remain competitive. Industry revenue is expected to have fallen at an annualised 2.5% over the five years through 2024-25, to $10.9 billion. This includes an anticipated 2.3% dip in 2024-25 as the real estate market continues to face pressures from high demand, low supply, labour costs and rental affordability challenges. In the coming years, favourable market conditions and government initiatives are poised to support industry growth. As economic conditions improve and consumer confidence grows, more buyers are projected to enter the housing market, increasing housing transfers and enhancing franchises’ profitability. Improved lending practices may empower potential homeowners, leading to a rise in transactions, which will benefit franchises reliant on volume. Rising business confidence is set to stimulate demand for real estate, attracting both local and foreign investors and encouraging new construction projects. Projected decreases in the cash rate are also poised to revive market activity, enhancing accessibility for buyers and investors. Overall, industry revenue is forecast to climb at an annualised 1.7% over the five years through 2029-30, to $11.8 billion.

Snapshot img

Singapore Real Estate Market Size 2025-2029

The singapore real estate market size is forecast to increase by USD 62.6 billion at a CAGR of 4.6% between 2024 and 2029.

The market is witnessing significant growth, driven primarily by the burgeoning demand for industrial infrastructure. This trend is fueled by the country's status as a global business hub, attracting numerous multinational corporations seeking to establish a presence. Concurrently, marketing initiatives in the real estate industry are gaining momentum, with developers increasingly adopting innovative strategies to differentiate their offerings and cater to diverse customer segments. However, this market landscape is not without challenges. Regulatory uncertainty looms large, with ongoing debates surrounding potential changes to property cooling measures and land use regulations. These uncertainties could deter investors and developers, potentially hindering market growth. As such, navigating the complex regulatory environment and staying abreast of policy developments will be crucial for companies looking to capitalize on opportunities and mitigate risks in the Singapore Real Estate market.

What will be the size of the Singapore Real Estate Market during the forecast period?

Explore in-depth regional segment analysis with market size data - historical 2019-2023 and forecasts 2025-2029 - in the full report.
Request Free Sample

The Singapore real estate market exhibits dynamic activity in various sectors. The sub-sale market experiences continuous fluctuations, influenced by property valuation models and market forecasting. Property law plays a crucial role in real estate financing and collective sales, including en bloc and strata title transactions. Property investment funds and real estate syndication provide financing options for freehold and leasehold properties. Real estate litigation arises from property disputes, necessitating ethical conduct in property management services. Proptech adoption streamlines property search engines and portfolio management, while property tax incentives stimulate investment. Rental management services and property insurance mitigate risks in the diverse real estate landscape. Property market trends encompass master plans, property crowdfunding, and real estate marketing strategies.

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. AreaResidentialCommercialIndustrialMode Of BookingSalesRental and leaseTypeLanded houses and villasOffice spaceApartments and condominiumsStore spaceOthersPriceMid-tierEntry-levelLuxuryGeographyAPACSingapore

By Area Insights

The residential segment is estimated to witness significant growth during the forecast period.

The Singapore real estate market encompasses various sectors, including residential, commercial, and industrial properties. The residential segment, comprised of apartments, condominiums, single-family homes, and other living arrangements, experiences significant demand due to population growth and the country's robust economy. Urban renewal projects and sustainable development initiatives contribute to the transformation of the property market. Commercial real estate, including office buildings and retail spaces, benefit from the thriving economy and increasing business activities. Property management companies employ technology, such as virtual and augmented reality, to enhance the property buying and selling experience. Real estate investment trusts and funds provide opportunities for investors seeking capital appreciation and rental income. Property prices have been on an upward trend due to high demand and limited supply, with vacancy rates remaining relatively low. Property taxes, stamp duty, and government policies influence the market dynamics. Urban planning and infrastructure development are essential for economic growth and smart city initiatives. Real estate developers and proptech startups leverage technology, including artificial intelligence and big data, to streamline property transactions and enhance property management. The rental market, property valuation, and property development are shaped by various factors, including rental yield, housing affordability, and market sentiment. Land use planning and regulations play a crucial role in shaping the real estate landscape. Capital appreciation and rental income continue to attract investors to the market, with mortgage rates influencing affordability. Smart home technologies and green building standards add value to both residential and commercial properties.

Request Free Sample

The Residential segment was valued at USD 100.30 billion in 2019 and showed a gradual increa

An export of the Ohio Public Health Data Warehouse, known as Ohio OneSource.http://publicapps.odh.ohio.gov/EDW/DataCatalogThe Ohio Public Health Data Warehouse is a self-service online tool where anyone can obtain the most recent public health data available about Ohio.

                  Citation:
                  Please use the following 

citation in any publication or release which uses or references data from the Warehouse: "These data were provided by the Ohio Department of Health. The Department specifically disclaims responsibility for any analyses, interpretations or conclusions".

Information for authorized public health personnel and IRB-approved researchers to access ODH’s secure data warehouse can be found here. http://publicapps.odh.ohio.gov/EDW/DataBrowser/Browse/OhioOneSourceOhio OneSourceCategory:Data Quality Latest Update:5/21/2018 Description: Find licensed providers. Contact Email: informatics@odh.ohio.govPurpose:This tool is intended to provide a “one stop shop” to search, filter, and extract information for all licensed healthcare facilities within the State of Ohio. Examples of provider types include, but are not limited to the following:

AS - Ambulatory Surgical CenterCI - Correctional InstitutionCL - ClinicCT- Chemical TreatmentDU - Dialysis UnitEM - Emergency Medical ServiceFA - First Aid DepartmentHH - Home Health CareHS - HospitalIM - Imaging / DiagnosticLA - LaboratoryMG - Medical Gas ServicesMH - Mental HealthNH - Nursing HomePC - Practitioner CorporationPMC - Pain Management ClinicPS - Pharmacy ServicesPT - Physical TherapyTE - TeachingUR - Urgent Care
*Data for this facility lookup tool is provided by the Ohio Board of Pharmacy and the Ohio Department of Health.

Urgent Care Facilities Urgent care is defined as the delivery of ambulatory medical care outside of a hospital emergency department on a walk-in basis without a scheduled appointment. (Source: Urgent Care Association of America) The Urgent Care dataset consists of any location that is capable of providing emergency medical care and must provide emergency medical treatment beyond what can normally be provided by an EMS unit, must be able to perform surgery, or must be able to provide recuperative care beyond what is normally provided by a doctor's office. In times of emergency, the facility must be able to accept patients from the general population or patients from a significant subset of the general population (e.g., children). Florida and Arizona license Urgent Care facilities within their state. However, the criteria for licensing and the criteria for inclusion in this dataset do not appear to be the same. For these two states, this dataset contains entities that fit TGS' criteria for an Urgent Care facility but may not be licensed as Urgent Care by the state. During processing, TGS found that this is a rapidly changing industry. Although TGS intended for all Urgent Care facilities to be included in this dataset, the newest facilities may not be included. Entities that are excluded from this dataset are administrative offices, physician offices, workman compensation facilities, free standing emergency rooms, and hospitals. Urgent Care facilities that are operated by and co-located with a hospital are also excluded because the locations are included in the hospital dataset. ID# 10194253 is a "mobile" urgent care center that provides urgent care to private residences. This entity is plotted at its administrative building. Records with "-DOD" appended to the end of the [NAME] value are located on a military base, as defined by the Defense Installation Spatial Data Infrastructure (DISDI) military installations and military range boundaries. At the request of NGA, text fields in this dataset have been set to all upper case to facilitate consistent database engine search results. At the request of NGA, all diacritics (e.g., the German umlaut or the Spanish tilde) have been replaced with their closest equivalent English character to facilitate use with database systems that may not support diacritics. This dataset does not contain any Urgent Care facilities in American Samoa, Guam, the Virgin Islands, or the Commonwealth of the Northern Mariana Islands. The currentness of this dataset is indicated by the [CONTDATE] field. Based upon this field, the oldest record is dated 11/22/2004 and the newest record is dated 07/17/2009.