This data collection contains a stratified 1-percent sample of households, with separate records for each household, each "sample line" respondent, and each person in the household. These records were encoded from microfilm copies of original handwritten enumeration schedules from the 1950 Census of Population. Geographic identification of the location of the sampled households includes Census regions and divisions, states (except Alaska and Hawaii), Standard Metropolitan Areas (SMAs), and State Economic Areas (SEAs). The data collection was constructed from and consists of 20 independently-drawn subsamples stored in 20 discrete physical files. The 1950 Census had both a complete-count and a sample component. Individuals selected for the sample component were asked a set of additional questions. Only households with a sample line person were included in the 1950 Public Use Microdata Sample. The collection also contains records of group quarters members who were also on the Census sample line. Each household record contains variables describing the location and composition of the household. The sample line records contain variables describing demographic characteristics such as nativity, marital status, number of children, veteran status, education, income, and occupation. The person records contain demographic variables such as nativity, marital status, family membership, and occupation. (Source: downloaded from ICPSR 7/13/10)

Please Note: This dataset is part of the historical CISER Data Archive Collection and is also available at ICPSR at https://doi.org/10.3886/ICPSR08251.v1. We highly recommend using the ICPSR version as they may make this dataset available in multiple data formats in the future.

In 2021, close to ten percent of the 152.8 million homes in the United States were from the first decade of the 21st century. Between 2000 and 2009, approximately 14.6 million homes were constructed.

Der Datensatz enthält für die gegebenen Länder jeweils zwei Zeitreihen für die Wohneigentumsquote. Die erste Zeitreihe besteht aus den Rohdatenpunkten. Die Wohneigentumsquote ist in den meisten Ländern nur zu bestimmen Volks- oder Wohnungszählungszeitpunkten erhoben worden. Deswegen liegen für die Rohdaten Messungen nur zu einzelnen Zeitpunkten vor. Die Rohdaten aller Länder können aus dem Menü ‚Beschreibung‘ (blauer Button) unter dem letzten Punkt ‚Materialien zur Studie‘ / ‚Download weiterer Texte zu dieser Studie im PDF Format (Forschungsberichte, Publikationen, Materialien zur Studie)‘ (orangener Button mit PDF-Symbol) als Excel-Datei heruntergeladen werden. Die zweite Zeitreihe geht von der gleichen Datengrundlage aus und fügt eine lineare Interpolation hinzu, damit die Variable in Panelanalysen verwendet werden kann. Die lineare Interpolation kann man damit rechtfertigen, dass die Wohneigentumsquote eine sich nur langsam verändernde Größe ist. Ferner zeigen die jüngeren jährlichen Daten aus Umfragen, dass die Reihe keine großen Sprünge macht. Die interpolierten Zeitreihen befinden sich im Datenteil der Studie (orangener Button mit der Aufschrift ‚146 Zeitreihen (1900-2015) 1 Tabelle). Hier kann die Tabelle entweder komplett downgeloadet werden, oder es können Ländergruppen nach Kontinent oder einzelne Länder ausgewählt werden. Zur Definition der Wohneigentumsquote, der Ländervergleichbarkeit und länderspezifischen Besonderheiten sollten folgende methodische Punkte berücksichtigt werden: Erstens gibt es die auf die Wohnungseinheiten basierende Definition der Wohneigentumsquote, die alle selbstgenutzten Wohn-Einheiten zählt und sie durch alle Gebäude-Einheiten teilt. Diese Definition gilt für die Daten, die auf den Wohnungszählungen der Länder basieren, und der Autor S. Kohl bezieht sich auf diese Definition für die frühesten Zeiträume der Wohneigentums-Quoten. Zweitens hängt die auf Gebäude- bzw. Wohn-Einheiten basierende Definition davon ab, was als Gebäude-Einheit zählt und was zum Wohnungsbestand gehört. Die häufigsten internationalen Vergleiche basieren auf UN (UN 1974, Doling 1997: 35: 154) oder EU-Daten, die lediglich die jeweiligen nationalen statistischen Definitionen wiederholen, die sich erheblich unterscheiden (Behring, Helbrecht und Goldrian 2002). Obwohl die Definitionen der Wohneinheit zwischen den OECD-Ländern sehr ähnlich sind (vgl. Donnison und Ungerson 1982: 42), ist die Einbeziehung von z.B. Anhängern, Saison- und Wohnmobilen in den USA eine Ausnahme (US-Census 2013), die rund 7% des Wohnungsbestandes ausmachen und zu einer deutlich überdurchschnittlichenWohneigentumsquote führen. Diese Einheiten würden, wenn sie statistisch signifikant wären, in Deutschland wahrscheinlich nicht als Wohneinheiten gelten. Der Wohnungsbestand kann sich unterscheiden je nach dem, ob Unterkünfte wie Ferienhütten, Zweitwohnsitze, Wohnwagen, Schiffe, saisonale Wohneinheiten, leerstehende oder zeitweise unbewohnte Einheiten als Wohneinheiten behandelt werden. Die deutsche Definition des Wohnungsbestandes gehört zu den konservativeren im Vergleich zu denjenigen anderer nationaler Statistikämter (Destatis 1989: 7, SE / CZR 2004). Die einheitsbasierte Definition wird durch Kriegszerstörungen verzerrt, wie in Deutschland in den 1950er Jahren, als die offizielle Wohneigentumsquote auf Einheitsbasis mit 39,1% angegeben wurde. Die Zerstörung von überwiegend städtischem Wohnungsbau durch Luftschutzbauten hatte den gesamten Wohnungsbestand reduziert. Der Autor stützt sich deshalb im Falle von Deutschland auf die realistischere Hausbesitzquote von 26,7% im Jahr 1950 stützen (Glatzer 1980: 246). Zweitens gibt es haushaltsbasierte Definitionen der Wohneigentumsquote, die alle Eigentümer-Haushalte (Wohnungs-Eigentümer und Haus-Eigentümer) in das Verhältnis setzt zur Gesamtzahl der Haushalte. Diese Definition, die auf repräsentativen Umfragedaten basiert, ersetzte die auf Wohneinheiten basierenden Daten ab den 1980er Jahren. Der Autor bezieht sich auf diese Definition für die neueren Daten seiner Wohneigentumsquoten. Umfragen berücksichtigen tendenziell Wohnungs- und Hauseigentümer aus den mittleren Klassen stärker als andere Bevölkerungsgruppen. Dies scheint vor allem bei den Eurostat-Umfragen zu gelten, die deutlich höhere Zahlen liefern als nationale Erhebungen, weil das Verhältnis von befragten Eigentümerhaushalten zu allen Befragten höher ist als wohneinheitenbasierte Berechnungen. Dadurch kommt es zu einer Verzerrung bzw. zu höheren Eigentums-Quoten. Aus diesem Grund hat sich der Autor, soweit möglich, auf Quellen außerhalb von Eurostat gestützt, um den Vergleich mit Nicht-EU-Ländern nicht zu verzerren. Eine dritte Definition ist bevölkerungsbezogen und setzt die in Eigenheimen lebende Bevölkerung in das Verhältnis zur Bevölkerung insgesamt (Braun 2004). Diese Definition führt aufgrund der statistischen Prävalenz von Familien in den Eigentümerhaushalten zu höheren Wohneigentumsquoten als die erstgenannte. Dies...

The data compilation is a review of the state-aided housing construction development in the Federal Republic of Germany. Public housing aims at the supply of cost-saving housing space for a special group of people, specified by law. In addition to the creation of low-cost living space the acquisition of owner-occupied real estate has been funded according to the second housing act, so that real estate was possible for broad levels of the population. Using different forms of subsidies (construction cost and expense subsidy, interest subsidy), the rents could be reduced below a rent needed to cover the costs of the residence and thereby opened for the legitimate low-income groups (direct funding of the projected buildings or flats: object-based aid or object support). This law has been replaced in 2001 by the reform of the social housing law. It regulates the housing and other measures to support households with rental housing, including housing cooperatives and the creation of owner-occupied real estate property for households that cannot adequately supply themselves with living space on the housing market. The construction of social housing in Germany on the basis of the second housing act has been a form of state transfer payment. Additionally social housing policy up to the 90s with its comprehensive public investments has been an important element of the state’s impact on the economy and urban development policy. This social housing act has been replaced by the new social housing law in 2001, a housing policy support instrument of the federal government and the governments of the single German federal ‘Länder’ (federal states), which consists of actions on several levels: social housing assistance, housing benefits, property development, building society promotion, housing bonus, pension fund law, residential support programs of the KfW development bank "initiative to build cost-effective and quality conscious”.

The statistics of the grants for social housing applies to housing construction projects that are funded by the public sector in social housing. In addition, the purchase of existing homes, which were funded by public sector, is included. The statistics on permits included until 1999 the following information: (1) Funded apartments and buildings (new building), without / with condominiums, (2) grant funds by purpose (promoting pathways), (3) financial ressources and (4) structure in the fully funded housing construction (building size, number of buildings, number of apartments, living space, estimated cost).

Depending on the purpose of the granted funding between the following cases has been distinguished: Cases funded by means of the so called first funding procedure. These are cases of the traditional publicly funded social housing. Since 1966 further cases were funded by means of the so called second funding procedure. Funding of housing units in the frame of tax-advantaged housing construction for people with higher incomes are cases belonging to the second funding procedure. Finally, from 1989 cases funded by means of the agreed funding, the so called third funding procedure. Those building projects, in which between lender, grant donor, and builder an agreement is made on amount and use of the funding, covered by the third funding procedure.

According to the act on the reform of the social housing law (2001) an annual statistics on the governmental granted funding is produced.

Data tables in HISTAT (Topic: Bautätigkeit, Wohnungen):

A. Bewilligungen, im öffentlich geförderten sozialen Wohnungsbau (1960-1999)

A.01a Übersicht: Öffentlich geförderte Wohnungen im sozialen Wohnungsbau, Früheres Bundesgebiet, Deutschland (1950-2003) A.01b Bewilligungen im öffentlich geförderten sozialen Wohnungsbau: Gebäude und Wohnungen, Früheres Bundesgebiet (1950-1999) A.01c Bewilligungen im öffentlich geförderten sozialen Wohnungsbau: Gebäude und Wohnungen, Neue Länder (1991-1999) A.01d Bewilligungen im öffentlich geförderten sozialen Wohnungsbau: Gebäude und Wohnungen, Deutschland (1991-1999) A.02a Förderungsmittel nach Art der Förderung (Förderungswege), Früheres Bundesgebiet (1960-1998) A.02b Förderungsmittel nach Art der Förderung (Förderungswegen), Neue Länder (1991-1998) A.02c Förderungsmittel nach Art der Förderung (Förderungswegen), Deutschland (1991-1998) A.03a Veranschlagte Finanzierungsmittel insgesamt nach Finanzquellen, Früheres Bundesgebiet (1960-1998) A.03b Veranschlagte Finanzierungsmittel insgesamt nach Finanzquellen, Neue Länder (1991-1998) A.03c Veranschlagte Finanzierungsmittel insgesamt nach Finanzquellen, Deutschland (1991-1998) A.04 Veranschlagte Finanzierungsmittel insgesamt nach Förderungswegen (1960-1999)

B. Struktur im voll geförderten reinen Wohnungsbau (1960-1999)

B.01a Wohngebäude mit 1 und 2 Wohnungen (Förderung insgesamt): Gebäudezahl, Wohnungsgröße und veranschlagte Gesamtkosten nach Kostenarten, Früheres Bundesgebiet (1962-1998) B.01b Wohngebäude mit...

This data collection is one in a series of financial surveys of consumers conducted annually since 1946. In a nationally representative sample, the head of each spending unit (usually the husband, the main earner, or the owner of the home) was interviewed. The basic unit of reference in the study was the spending unit, but some family data are also available. The questions in the 1950 survey covered the respondent's attitudes toward national economic conditions and price activity, as well as the respondent's own financial situation. Other questions examined the spending unit head's occupation, and the nature and amount of the spending unit's income, debts, liquid assets, changes in liquid assets, savings, investment preferences, and actual and expected purchases of cars and other major durables. The survey also elicited respondent's attitudes about different methods of using income remaining after expenses were met, e.g., investing in stocks or putting money in savings. In addition, the survey explored in detail the subject of housing, e.g., previous and present home ownership, value of respondent's dwelling, and mortgage information. Further questions concerned life insurance (including number of policies, types, and premiums) and common stock ownership, purchases, and sales. The 1950 survey included a separate questionnaire for farmers that contained differing questions on sources of income and housing. Personal data include number of people in the spending unit, age, sex, and education of the head, and the race and sex of the respondent. (Source: downloaded from ICPSR 7/13/10)

Please Note: This dataset is part of the historical CISER Data Archive Collection and is also available at ICPSR at https://doi.org/10.3886/ICPSR03612.v1. We highly recommend using the ICPSR version as they may make this dataset available in multiple data formats in the future.

How many households are in the U.S.?

In 2023, there were 131.43 million households in the United States. This is a significant increase from 1960, when there were 52.8 million households in the U.S.

What counts as a household?

According to the U.S. Census Bureau, a household is considered to be all persons living within one housing unit. This includes apartments, houses, or single rooms, and consists of both related and unrelated people living together. For example, two roommates who share a living space but are not related would be considered a household in the eyes of the Census. It should be noted that group living quarters, such as college dorms, are not counted as households in the Census.

Household changes

While the population of the United States has been increasing, the average size of households in the U.S. has decreased since 1960. In 1960, there was an average of 3.33 people per household, but in 2023, this figure had decreased to 2.51 people per household. Additionally, two person households make up the majority of American households, followed closely by single-person households.

After the entry into force of major housing policy laws in the first 20 or 30 years of the Federal Republic of Germany (First and Second Housing Act; housing - premium law; Housing Benefit Act; Urban Development Act) the associated support ("subsidies", financial or tax benefits which affect households immediately, indirectly but with importance for their economic live, are accounted as subsidies for housing, this for example includes the promotion of savings capital formation in building societies) contributed significantly until the end of 1980 to the construction of 16,7 million apartments (of which 7.1 million were family homes) and to the modernization of housing stock. Wealth creation was influenced by decisive impulses. Also direct transfer payments (public, housing premiums, etc.) and tax incentives (property tax reduction, accelerated depreciation under § 7b income tax act, depreciation according to § 82a of the income tax etc.) were made. The volume increased also by other not exactly quantifiable loss of tax revenue resulting from the regulation of the general tax law (including fiscal consequences of the build-owner model). Further losses of tax revenue as a consequence of not contemporary basic values need to be taken into account. “Insofar the research question of the author ‘Subsidies without counter performance?’ should deal with a much discussed problem because one can consider losses of tax revenue and allocation of funds as integral parts conscious political action and not as arbitrary distribution of election gifts. But actually this is a terra incognita. The extent of housing shortage after the Second World War did not leave room for such discussions. Therefor a systematic debate about the distributional effects of housing policy began relatively late, it started when in spite of the high volume of funding disparities in the provision of housing, the financial restrictions the public sector became more obvious.” (Kornemann, a. cit., p. 42 f.). It is undisputed that the state aid has contributed significantly to the sustainable improvement of the housing situation in the Federal Republic of Germany. The author summarizes the main results of government incentives for equity capital formation and for rent or load reduction as well as for the development of the volume of housing construction in overviews and concludes with a critique of the services and instruments of official housing policy.

Data tables in HISTAT: A.01 Government support measures for equity capital creation, in Mill. DM (1950-1980) A.02 Government support measures for Rental or load reduction, in Mill. DM (1950-1980) A.03 Volume of housing and construction completions, in billion DM (1950-1980)

This built area can also be described as an “urban task” or an urban envelope and is defined as the area delimiting a set of parcels built on a given date. This envelope is only a spatial reference for locating a boundary of construction according to different design criteria. However, that envelope does not in any way constitute the currently urbanised part defined by virtue of the application of land law, which is much more restricted, which is determined on the basis of factual elements of the ground and on the basis of jurisprudential criteria. This built sector serves only as a reference point to contribute to the assessment of the consumption of space in urban planning documents. Some specific features of the spatial distribution of built-up areas are observed in more detail. These differences can be attributed to the land structure of agricultural areas (cultural typology, parcel geometry, cultural methods of setting up farms, etc.), to land-based urbanisation patterns depending on the territory or, on the contrary, to more intensified forms of this residential development (e.g. regulatory aspect of urban planning documents). In the department, these different forms of urban envelopes are identifiable. For example, in the Deux-Sèvres, the periphery of Parthenay is composed of a scattered set of habitat represented by an urban envelope in cloud of dots. Whereas in contrast, Niort’s periphery is marked by larger but more concentrated envelopes. This data specifies the number of parcels that make up each urban envelope. This allows, by simple processing, to select only the corresponding urban envelopes, those consisting of at least four units.

This map shows the historical housing unit change in consistent 2010 census tract boundaries from 1940 to 2019. In many cities over that time period—especially in the 1950s and 1960s—federal, state, and local governments demolished thousands of housing units as part of their "urban renewal" programs. These neighborhoods were typically in the older parts of city centers, contained lower income populations, and had higher shares of Black, Hispanic, and immigrant residents than their respective cities. Homes were typically replaced with new interstate highways and thoroughfares, stadiums, civic buildings, parking lots, high rises, rights of way, and other non-residential uses. In a fraction of cases, homes were replaced with public housing. Many of these areas show up as red on this map because they still have not regained the level of housing they had before World War II.Urban renewal is not the only reason for housing loss. Many tracts in places that have been undergoing population decline—especially cities in the North and Midwest and many rural communities—have also lost considerable amounts of housing over this time period.On the other side of things, many suburban and exurban areas—especially in the South and West—have experienced significant population and housing unit growth. These places show up as blue on this map.The data used to make this map comes from the Historical Housing Unit and Urbanization Database 2010, or HHUUD10. To read more on the methodologies used to estimate the housing unit counts, please refer to the methods paper. To download the data in tabular form, please visit the data repository. To download the feature layer used to make this map or read about the attributes, see the feature layer. Please also remember that these data are estimates and are therefore imperfect. They should be treated like all interpolated data: with caution and a healthy dose of skepticism.Citation:Markley, S.N., Holloway, S.R., Hafley, T.J., Hauer, M.E. 2022. Housing unit and urbanization estimates for the continental U.S. in consistent tract boundaries, 1940–2019. Scientific Data 9 (82). https://doi.org/10.1038/s41597-022-01184-x

The aim of the investigation is, first, to analyse, how and in what extend the housing economy – under special circumstances – was subordinated to the state’s responsibility and therefore an active housing policy was needed. Second, on the basis of the gained results, the carried housing policy since the First World War should be subject to a detailed analysis. The discussion of necessity and extent of state housing policy is done on the basis of the construction liberalism before 1914. The second task of investigation is the representation of the housing policy development in Germany and its results in the interwar period and the period after 1945. In matter-of-fact terms, the arguments focus primarily on housing policy activities of the German Empire and of the Federal Republic of Germany respectively. Topics Datatables in the search- and downloadsystem HISTAT: Information: HISTAT is offered only in German language. Datentabellen in HISTAT:A.01 Preisindex für Wohngebäude insgesamt (1913-1971)(= Priceindices of residential buildings)A.02 Die Finanzierung des Wohnungsbaus nach ihren Quellen in Deutschland (1924-1939)(= Financing housing construction by finance sources in Germany)A.03 Der Roh- und Reinzugang an Wohnungen in Deutschland (1919-1939)(= New entries of housing in Germany)A.04 Anteil öffentlich geförderter Wohnungen und der Bauherren an den Wohnungsfertigstellungen in Deutschland (1927-1939)(= Portion of public funded housing and of house builder on housing completion in Germany)A.05 Entwicklung der von der deutschen Bau- und Bodenbank verwalteten Reichs- und Treuhandmittel (1927-1943)(= Development of monetary funds, managed by construction banks)B.01 Art der Förderung im öffentlich geförderten sozialen Wohnungsbau in der Bundesrepublik (1957-1970)(= Official granting of social housing construction)B.02 Die Finanzierung des Wohnungsbaus nach ihren Quellen in der Bundesrepublik (1950-1971)(= Financing of housing construction by finance sources in the Federal Republic of Germany)B.03 Leistung der Kapitalsammelstellen für die Finanzierung des Wohnungsbaus in der Bundesrepublik (1950-1971)(= Benefits of so called ‚capital gathering places‘ for the financing of housing construction in the Federal Republic of Germany) B.04 Struktur des Wohnungsbaus in der Bundesrepublik (1949-1971)(= Structures of the housing construcition in the Federal Republic of Germany)

Graph and download economic data for All-Transactions House Price Index for the United States (USSTHPI) from Q1 1975 to Q4 2024 about appraisers, HPI, housing, price index, indexes, price, and USA.

After the entry into force of major housing policy laws in the first 20 or 30 years of the Federal Republic of Germany (First and Second Housing Act; housing - premium law; Housing Benefit Act; Urban Development Act) the associated support ("subsidies", financial or tax benefits which affect households immediately, indirectly but with importance for their economic live, are accounted as subsidies for housing, this for example includes the promotion of savings capital formation in building societies) contributed significantly until the end of 1980 to the construction of 16,7 million apartments (of which 7.1 million were family homes) and to the modernization of housing stock. Wealth creation was influenced by decisive impulses. Also direct transfer payments (public, housing premiums, etc.) and tax incentives (property tax reduction, accelerated depreciation under § 7b income tax act, depreciation according to § 82a of the income tax etc.) were made. The volume increased also by other not exactly quantifiable loss of tax revenue resulting from the regulation of the general tax law (including fiscal consequences of the build-owner model). Further losses of tax revenue as a consequence of not contemporary basic values need to be taken into account. “Insofar the research question of the author ‘Subsidies without counter performance?’ should deal with a much discussed problem because one can consider losses of tax revenue and allocation of funds as integral parts conscious political action and not as arbitrary distribution of election gifts. But actually this is a terra incognita. The extent of housing shortage after the Second World War did not leave room for such discussions. Therefor a systematic debate about the distributional effects of housing policy began relatively late, it started when in spite of the high volume of funding disparities in the provision of housing, the financial restrictions the public sector became more obvious.” (Kornemann, a. cit., p. 42 f.). It is undisputed that the state aid has contributed significantly to the sustainable improvement of the housing situation in the Federal Republic of Germany. The author summarizes the main results of government incentives for equity capital formation and for rent or load reduction as well as for the development of the volume of housing construction in overviews and concludes with a critique of the services and instruments of official housing policy.

Data tables in HISTAT: A.01 Government support measures for equity capital creation, in Mill. DM (1950-1980) A.02 Government support measures for Rental or load reduction, in Mill. DM (1950-1980) A.03 Volume of housing and construction completions, in billion DM (1950-1980)

In 2021, there were about 338,000 home structure fires reported in the United States. This is a decrease from the previous year, when there were 356,500 home structure fires reported across the country.

In vier Kapiteln analysiert Hannsjörg Buck nicht nur die Wohnungspolitik der SBZ / DDR von 1945 bis 1989, sondern belegt seine kritischen Ausführungen durch zahlreiche Statistiken und insbesondere durch bisher kaum oder gar nicht bekannte Dokumente, auch solchen vertraulichen Charakters. Die Untersuchung versucht zu zeigen, dass eine ideologisch basierte Wohnungspolitik zum Scheitern verurteilt ist. Eingeordnet in die Wirtschaftspolitik der SED legt der Autor eine ausführliche Gesamtdarstellung der Wohnungspolitik der SBZ/DDR vor. Gestützt auf umfangreiches Zahlenmaterial und grundlegende archivalische Quellenstudien analysiert er die wohnungspolitischen Aktivitäten der SBZ/DDR. Die Autor gliedert die Untersuchung in vier Teile, die folgenden Perioden entsprechen: Teil I: Wohnungspolitik in der SBZ von 1945 – 1949; Teil II: Wohnungspolitik der DDR von der Staatsgründung 1949 bis zum Mauerbau 1961; Teil III: Wohnungspolitik der DDR vom Mauerbau 1961 bis zum Sturz Ulbrichts 1970/71; Teil IV: Wohnungspolitik als Kernstück der Sozialpolitik der DDR 1971 – 1989. Wichtige Zeitreihen sind u.a.:- Neugebaute Wohnungen im privaten Wohnungsbau der DDR;- Aufteilung der Neubauleistungen bei Wohnungen auf einzelne Bauträger;- Durch Modernisierung fertiggestellte Wohnungen in der DDR;- Durch Neubau und Modernisierung fertiggestellte Wohnungen in der DDR;- Entwicklung des Wohnungsbestandes in Wohn- und Nichtwohngebäuden im Gebiet der DDR und Berlin (Ost);- Gebaute Wohnungen in der SBZ/DDR;- Wohnungen in sämtlichen Gebäudearten aufgeteilt nach Ausstattungsmerkmalen;- Wohnungsbestand in der DDR, aufgeteilt nach Eigentumsformen.

Datentabellen in HISTAT:Die einzelnen Datentabellen sind nach folgenden Zeitperioden gegliedert:A – Tabellen: Teil I, Wohnungspolitik in der SBZ von 1945 – 1949;B – Tabellen: Teil II, Wohnungspolitik der DDR von der Staatsgründung 1949 bis zum Mauerbau 1961;C – Tabellen: Teil III, Wohnungspolitik der DDR vom Mauerbau 1961 bis zum Sturz Ulbrichts 1970/71;D – Tabellen: Teil IV, Wohnungspolitik als Kernstück der Sozialpolitik der DDR 1971 – 1989. Verzeichnis der Tabellen in HISTAT: A. Teil I: Wohnungspolitik in der SBZ von 1945 - 1949A.01 Wohnungsbestand in Ländern der Sowjetischen Besatzungszone Deutschlands vor dem 2. Weltkrieg und Ausmaß der durch Kriegseinwirkung zerstörten Wohnungen (1939-1946)A.02 Private Haushalte, Wohnungsbestand und Wohnungsdefizit in den Ländern der Sowjetischen Besatzungszone Deutschlands (1946)A.03 In Notunterkünften untergebrachte Personen in der Sowjetischen Besatzungszone (1945-1950)A.04 Rückgewinnung von teilweise zerstörten und unbewohnbaren Wohnungen in den Ländern der SBZ durch Instandsetzungsmaßnahmen (1945-1950)A.05 Von den Wohnungsbehörden der SBZ beschlagnahmter Wohnraum (1946-1950)A.06 Das "Bodenreform-Bauprogramm" der SBZ: Planziele und Planerfüllung bei Errichtung von Neubauern-Wohngebäuden (1946-1953) B. Teil II: Wohnungspolitik der DDR von der Staatsgründung 1949 bis zum Mauerbau 1961B.01 Verteilung der Bauleistung der Bauwirtschaft der DDR (ohne Bauhandwerk) auf Betriebe verschiedener Eigentumsformen (1950-1962)B.02 Bauleistungen (Bau- u. Montageproduktion) der Betriebe verschiedener Eigentumsformen der Bauwirtschaft der DDR (Bauindustrie ohne Bauhandwerk) für den Wohnungsbau (1953-1972)B.03 Träger des Wohnungsbaus in der DDR 1950, während des ersten Fünfjahresplanes 1951-1955, 1956 (1950-1956)B.04 Neubau von Wohnungen in der DDR, nach Bauherren verschiedener Eigentumsformen (1955-1973)B.05 Wohnungsbau in der DDR nach Bauherren verschiedener Eigentumsformen (1950-1965)B.06 Entwicklung der Arbeiterwohnungsbaugenossenschaften (AWG) in der DDR (1954-1964)B.07 Planziele und Planerfüllung im Wohnungsbau der DDR (1954-1965)B.08 Eheschließungen und Zugewinn von Wohnungen in der DDR (1948-1965) C. Teil III: Wohnungspolitik der DDR vom Mauerbau 1961 bis zum Sturz Ulbrichts 1970/71C.01 Jahresplanziele und jährliche Planerfüllung im Wohnungsbau der DDR (1960-1970)C.02 Anteil der in Montagebauweise errichteten Neubauwohnungen in der DDR (1956-1970)C.03 Durchschnittliche Bauzeit zur Errichtung neuer Wohnungen in der DDR (1958-1970)C.04 Entwicklung der Arbeiterwohnungsbaugenossenschaften (AWG) in der DDR (1954-1977)C.05 Einsatz von Investitionskapital für den Neubau von Wohnungen in der DDR (1955-1971)C.06 Wohnungsbestand aufgeteilt nach der Zahl der Wohnräume (1961-1971)C.07 Wohnungen in Wohngebäuden der DDR aufgeteilt nach der Eigentumsform der Gebäude (1950-1971)C.08 Wohnungen in Wohngebäuden der DDR aufgeteilt nach dem Baujahr der Gebäude (1961-1971)C.09 Ausstattung der in der SBZ/DDR neugebauten Wohnungen mit Wohnkomfort (1949-1970)C.10 Neugebaute Wohnungen in der DDR und in der BRD je 1000 Einwohner (1959-1971)C.11 Gebaute Wohnungen in der DDR (1955-1971)C.12 Beitrag des genossenschaftlichen Wohnungsbaus zum Bau neuer Wohnungen und zur Schaffung von Wohnungen durch Um- und Ausbau (1955-1972)C.13 Wohnungsbau in der DDR aufgeteilt nach Bauherren verschiedener Eigen...

Phase I of the mapping tool displays residential parcels categorized by the year constructed, based off of New Jersey's statewide parcel dataset (MOD-IV). You can also find a breakdown of housing age by county and municipality. Housing are categorized into four categories – pre-1950, 1951-1978, post-1978, and unavailable. Prior to the 1950s, lead-based paint was commonly used for both home interiors and exteriors. Exposure in older homes happens when lead-based paint starts to deteriorate, cracking or peeling away from the walls. That decay results in lead-contaminated dust, which may be directly ingested or inhaled, and paint chips, which may be touched or, less commonly, ingested. Living in a house with lead-based paint can result in a chronic accumulation of the heavy metal in the body. Houses built after 1978 are less likely to contain lead-based paints. That year, Congress banned the use of lead-based paint in homes built or rehabilitated with federal funding through the Lead-Based Paint Poisoning Prevention Act. By 1992, the act was amended to address lead-contaminated dust and soil in homes, as well as adopt preventive strategies to reduce future lead exposure. These homes face the lowest risk of potential lead exposure. In the 1950s, the paint industry voluntary adopted its own standards to phase out and prohibit the use of lead additives, such that homes built between 1950 and 1978 have only some risk of potential lead exposure.

The system of social indicators for the Federal Republic of Germany - developed in its original version as part of the SPES project under the direction of Wolfgang Zapf - provides quantitative information on levels, distributions and changes in quality of life, social progress and social change in Germany from 1950 to 2013, i.e. over a period of more than sixty years. With the approximately 400 objective and subjective indicators that the indicator system comprises in total, it claims to measure welfare and quality of life in Germany in a differentiated way across various areas of life and to monitor them over time. In addition to the indicators for 13 areas of life, including income, education and health, a selection of cross-cutting global welfare measures were also included in the indicator system, i.e. general welfare indicators such as life satisfaction, social isolation or the Human Development Index. Based on available data from official statistics and survey data, time series were compiled for all indicators, ideally with annual values from 1950 to 2013. Around 90 of the indicators were marked as "key indicators" in order to highlight central dimensions of welfare and quality of life across the various areas of life. The further development and expansion, regular maintenance and updating as well as the provision of the data of the system of social indicators for the Federal Republic of Germany have been among the tasks of the Center for Social Indicator Research, which is based at GESIS, since 1987. For a detailed description of the system of social indicators for the Federal Republic of Germany, see the study description under "Other documents".
Level of housing supply: Dwelling per household; Vacancy rate; Living space per person; Living space per person. Quality of housing facilities: Dwellings without standard furnishings; Dwellings without standard amenities (SOEP). Quality of living environment: Noisy dwellings. Cost of housing provision: Average rent burden; Households with high rent burden. Home ownership: Households in home ownership. Inequality in home ownership: Home ownership of self-employed and employees in comparison; Comparison of home ownership by blue-collar and white-collar workers. Subjective assessment of housing conditions; Housing satisfaction.

Private companies were responsible for most of the new homes built in the United Kingdom (UK) in 2023. Housing completions in the UK decreased for three years in a row between 2007 and 2010. This was followed by several years of fluctuation and a gradual increase from 2013 to 2019. The number of homes completed in England remained relatively stable in 2021 and 2022, after reaching a low point in the second quarter of 2020 due to the restrictions implemented to prevent the spread of COVID-19. Construction starts and completions Comparing the number of starts and completions in London side-by-side shows that whenever there is a significant growth or fall in the number of projects started, that peak or valley tends to be reflected in the number of buildings completed a couple of years later. Nevertheless, disruptions, delays, and other obstacles may affect that correlation. Still, observing how many home construction projects started in the UK can provide some insight into the level of activity that construction companies may have in the near future. Given that the number of housing starts is forecast to fall in 2023, there might be slightly less work to be carried out the following year. Nevertheless, housing starts are expected to pick up again by 2024 and 2025. Housing associations in the UK Housing associations are not-for-profit organizations created to develop and rent homes for a lower price than in the private market. They have acquired certain relevance in the UK, although this type of organization also exists in other countries. On several occasions during the past decade, over a fifth of housing starts in London were developed by housing associations. Meanwhile, the number of new homes completed in Scotland by housing associations has increased a lot throughout the years, with several thousand units constructed every year during the past decades.

description: This polygon shapefile provides county or county-equivalent boundaries for the conterminous United States and was created specifically for use with the data tables published as Selected Items from the Census of Agriculture for the Conterminous United States, 1950-2012 (LaMotte, 2015). This data layer is a modified version of Historic Counties for the 2000 Census of Population and Housing produced by the National Historical Geographic Information System (NHGIS) project, which is identical to the U.S. Census Bureau TIGER/Line Census 2000 file, with the exception of added shorelines. Excluded from the CAO_STCOFIPS boundary layer are Broomfield County, Colorado, Menominee County, Wisconsin, and the independent cities of Virginia with the exception of the 3 county-equivalent cities of Chesapeake City, Suffolk, and Virginia Beach. The census of agriculture was not taken in the District of Columbia for 1959, but available data indicate few if any farms in that area, the polygon was left in place to preserve the areas of the surrounding counties. Baltimore City, Maryland was combined with Baltimore County and the St. Louis City, Missouri, was combined with St. Louis County. La Paz County, Arizona was combined with Yuma County, Arizona and Cibola County, New Mexico was combined with Valencia County, New Mexico. Minor county border changes were at a level of precision beyond the scope of the data collection. A major objective of the census data tabulation is to maintain a reasonable degree of comparability of agricultural data from census to census. The tabular data collection is from 14 different censuses where definitions and data collection techniques may change over time and while the data are mostly comparable, a degree of caution should be exercised when using the data in analysis procedures. While the data are at a county-level resolution, a regional approach is more appropriate than a county-by-county analysis. The main purpose of this layer is to provide a base to generate a county raster for the allocation of agricultural census values to specific (agricultural) pixels. Vector format is provided so the raster pixel size can be user designated. References cited: LaMotte, A.E., 2015, Selected items from the Census of Agriculture at the county level for the conterminous United States, 1950-2012: U.S. Geological Survey data release, http://dx.doi.org/10.5066/F7H13016. National Historical Geographic Information System, Minnesota Population Center, 2004, Historic counties for the 2000 census of population and housing: Minneapolis, MN, University of Minnesota, accessed 03/18/2013 at http://nhgis.org; abstract: This polygon shapefile provides county or county-equivalent boundaries for the conterminous United States and was created specifically for use with the data tables published as Selected Items from the Census of Agriculture for the Conterminous United States, 1950-2012 (LaMotte, 2015). This data layer is a modified version of Historic Counties for the 2000 Census of Population and Housing produced by the National Historical Geographic Information System (NHGIS) project, which is identical to the U.S. Census Bureau TIGER/Line Census 2000 file, with the exception of added shorelines. Excluded from the CAO_STCOFIPS boundary layer are Broomfield County, Colorado, Menominee County, Wisconsin, and the independent cities of Virginia with the exception of the 3 county-equivalent cities of Chesapeake City, Suffolk, and Virginia Beach. The census of agriculture was not taken in the District of Columbia for 1959, but available data indicate few if any farms in that area, the polygon was left in place to preserve the areas of the surrounding counties. Baltimore City, Maryland was combined with Baltimore County and the St. Louis City, Missouri, was combined with St. Louis County. La Paz County, Arizona was combined with Yuma County, Arizona and Cibola County, New Mexico was combined with Valencia County, New Mexico. Minor county border changes were at a level of precision beyond the scope of the data collection. A major objective of the census data tabulation is to maintain a reasonable degree of comparability of agricultural data from census to census. The tabular data collection is from 14 different censuses where definitions and data collection techniques may change over time and while the data are mostly comparable, a degree of caution should be exercised when using the data in analysis procedures. While the data are at a county-level resolution, a regional approach is more appropriate than a county-by-county analysis. The main purpose of this layer is to provide a base to generate a county raster for the allocation of agricultural census values to specific (agricultural) pixels. Vector format is provided so the raster pixel size can be user designated. References cited: LaMotte, A.E., 2015, Selected items from the Census of Agriculture at the county level for the conterminous United States, 1950-2012: U.S. Geological Survey data release, http://dx.doi.org/10.5066/F7H13016. National Historical Geographic Information System, Minnesota Population Center, 2004, Historic counties for the 2000 census of population and housing: Minneapolis, MN, University of Minnesota, accessed 03/18/2013 at http://nhgis.org

The available data show the development of total residential buildings, including mixed-use buildings (e.g. non-residential buildings, which also include dwellings or housing opportunities), emergency accommodation and dwellings. In addition, the number of households per dwelling and the population per dwelling are reported for 83 years. These data show the evolution of the quality of housing and the proportion of particularly precarious dwellings over time. The compilation is based on the comprehensive population and building censuses carried out since 1871. Due to the extensive territorial changes over the 83-year period covered, which thus also cover a period prior to the existence of the federal state North Rhine-Westphalia, the comments are of particular importance. Due to the considerable scope of the study description the comments are additionally offered via a downloadable PDF file.

The data on residential buildings are part of an extremely comprehensive data compilation of the primary researcher Harald Klaudat. This data compilation is divided into several sub-studies.

While the study ZA8682 focuses on population and therefore presents the distribution of the population according to age, sex, and marital status as well as the number of births and deaths, the study ZA8683 presents the development of religious affiliation of the population in North Rhine-Westphalia over 120 years. This study with the number ZA8706 is dedicated to the sub-area of residential buildings.

While the data of the studies ZA8682 and ZA8683 are under the online-database Histat topic ´Population´, this part of the study was imported under the topic ´Building´ in histat. The data refer to the following administrative districts with their urban districts, independent towns, and rural districts: 01. Regierungsbezirk (= county) Aachen 02. Regierungsbezirk (= county) Arnsberg 03. Regierungsbezirk (= county) Düsseldorf 04. Regierungsbezirk (= county) Cologne 05. Regierungsbezirk (= county) Minden resp. Detmold 06. Regierungsbezirk (= county) Münster 07. Gesamtgebiet NRW (whole territory or North Rhine-Westphalia in general)

The following topics are covered in the data tables for each administrative district:

• Area of the respective county or district
• Number of normal residential buildings
• Number of non-residential buildings containing apartments.
• Number of temporary dwellings and accommodation occupied.
• Total number of dwellings (= sum of ´normal residential buildings´ + ´non-residential buildings with dwellings´ + ´inhabited emergency dwellings and accommodation´) per square km
• Inhabitants per square km
• Inhabitants per dwelling
• Households per dwelling

This data is available for the following occupational and census data: - 1.12.1885 (territory of 1885) - 1.12.1900 (territory of 1900) - 1.12.1910 (territory of 1910/12) - 13.9.1950 (territory of 1950) - 6.6.1961 (territory of 1961) - 25.10.1968 (territory of 1970) - 31.12.1968 for inhabitants per sqkm and per dwelling and for households per dwelling (territory of 1.1.1970)

Datatables in HISTAT, Topic ´Bauen´

1 Reg-Bez. Aachen: Wohngebäude 1885-1968

2a Reg-Bez. Arnsberg, Stadtkreise: Wohngebäude 1885-1968

2b Reg-Bez. Arnsberg, Landkreise: Wohngebäude 1885-1968

3a Reg-Bez. Düsseldorf, Stadtkriese: Wohngebäude 1885-1968

3b Reg-Bez. Düsseldorf, Landkreise: Wohngebäude 1885-1968

4 Reg-Bez. Koeln: Wohngebäude 1885-1968

5 Reg-Bez. Minden bzw. Detmold/ Land Lippe bis 1947: Wohngebäude 1885-1968

6 Reg-Bez. Münster: Wohngebäude 1885-1968

7 Gesamtgebiet bzw. Nordrhein-Westfalen (NRW): Wohngebäude 1885-1968

Graph and download economic data for Residential Property Prices for Japan (QJPN628BIS) from Q1 1955 to Q3 2024 about Japan, residential, HPI, housing, price index, indexes, and price.