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In the late 20th century, homeownership became entrenched in a wider societal project that sought to transform the economy and increase social inclusion. This project focused on mortgaged owner-occupation as a means not only to acquire a stable home, but also to realise greater economic security via asset accumulation. The underlying ideology featured an implicit promise that homeownership would be widespread, equalising and secure. Despite transformations in market conditions, such narratives have continued to underscore policy approaches and housing marketisation. This article directly confronts this promise. It first unpacks its key tenets before investigating their currency across three classic ‘homeowner societies’: the US, the UK and Australia. Our empirical findings reveal declining access to homeownership, increasing inequalities in concentrations of housing wealth and intensifying house-price volatility undermining asset security. The article contends that the imperative of homeownership that has sustained housing policy since the 1970s may be increasingly considered a ‘false promise’. Our analyses expose contemporary housing market dynamics that instead appear to enhance inequality and insecurity. 在20世纪后期，房屋所有权在一个更广泛的社会项目中变得根深蒂固，这个项目寻求经济转型和提升社会包容度。该项目强调抵押房主自住，这不仅作为获得稳定住房的一种手段，也作为通过资产积累提升经济安全的一种手段。这其中潜在的意识形态所强调的是这样一个期许：房屋所有权将是广泛的、平等的和安全的。尽管市场环境发生了变化，但这种论述继续强调政策方法和住房市场化。本文直接质疑这个期许。在对这些主要信条在美国、英国和澳大利亚这三个典型的“房主社会”的现实体现进行调查之前，我们首先对这些信条进行了解析。我们的经验研究结果显示，获得住房所有权的机会在减少，住房财富集中的不平等在加剧，而破坏资产安全的房价波动则在加剧。本文认为，自20世纪70年代以来一直作为住房政策基石的房屋所有权必要性理论可能会越来越被视为一种“错误的期许”。我们的分析揭示了当代住房市场的动态，而这种动态似乎加剧了不平等和不安全。

This article identifies proxies which account for the impacts that the Airbnb platform is having on housing in Greater London. We identify these by analysing the relationships between possible Airbnb misuse and the attributes of housing in the same locations. We assume misuse when listings of entire properties within the Airbnb platform do not conform with local regulations and where hosts who offer such housing have multiple listings. In particular, we examine (1) the dwelling type based on building typology; (2) the type of housing tenure, whether it is owned or rented; and (3) the spatial distribution of changes in rent payable. Three important findings emerge from our analysis. First, based on 2018 data, we estimate that more than 2% of all properties in London, and up to 7% in some local areas are being misused through Airbnb as short-term holiday rentals. Second, the location of these particular Airbnb rentals is negatively correlated with the diversity of dwelling types and positively correlated with dwelling type such as an apartment (or flat) in areas of high private rental stock. Last, we show that a 100% increase in the density of possible Airbnb misuse can be associated with up to an 8% increase in unit rental price per-bedroom per-week, an equivalent to up to an average of £90 price increase per year. Finally, we discuss how this type of analysis can help build instruments to inform policies associated with the platform economy in relation to increasing polarisation in the London housing market. 本文识别了一些指标，这些指标说明了爱彼迎 (Airbnb) 平台对大伦敦住房市场的影响。我们通过分析同一地段可能的爱彼迎误用与住房市场特征之间的关系来识别这些指标。当爱彼迎平台内的整体房产放租信息不符合当地法规，并且放租者有多个放租信息时，我们推定存在误用。具体而言，我们研究（1）住宅的建筑类型学分类；（2）住房使用权的类型，是自有的还是租赁的；（3）应付租金变化的空间分布。我们的分析得出了三个重要发现。首先，根据2018年的数据，我们估计伦敦超过2%的房产和一些分区高达7%的房产作为短期度假出租物业而发生了爱彼迎误用。第二，这些特定爱彼迎出租物业的位置与住宅类型的多样性负相关，与住宅类型（例如私人出租房屋存量高的地区的公寓）正相关。最后，我们表明可能的爱彼迎误用的密度增加100%可能会导致每间卧室每周的单位租赁价格增加8%，相当于每年平均增加90英镑。最后，我们讨论这种类型的分析如何有助于建立一些工具，面对伦敦住房市场日益严重的两极分化，这些工具能为与平台经济相关的政策的制定提供参考。

Housing markets display several correlations to multiple economic sectors of an economy. Their enormous impact on economies’ health, wealth, and stability is uncontroversial. Interestingly, the forms of financing residential property vary widely between the different countries in terms of both, the available product types and the institutions offering them. This research examines the implications of different financial intermediaries on housing market cycles with special emphasis on two institutional types, conventional banks and building and loan associations. Introducing a heterogeneous agent-based model, the interactions of buyers, sellers, and the two types of credit institutions are assessed. Heterogeneous economic principles and expectations of agents create endogenous market conditions which are strongly influenced by the lending practices of financial intermediaries.Focusing primarily on collateral values to decide about lending, conventional banks may contribute to volatile housing markets which are prone to recessions. Building and loan associations, on the other hand, rely to a greater extent on endogenously created borrower information. Thus, they are able to cushion the volatility of house prices caused by procyclical mortgage lending of conventional banks and increase the stability of the housing market. Simulations show that the most stable market conditions are attained if both types of financial intermediaries serve the mortgage lending market jointly. Furthermore, transaction and homeownership rates are the highest in this market setting. These findings advocate in favor of diversified financial markets.

Numerous efforts have over the last few years been devoted to studying spillovers (ripple effects) among cities as a means of evaluating overheated housing markets. What seems to be lacking, however, is the application of a rolling-window approach to further explore time-varying spillovers in a timely manner in order to look more closely at a housing market with Chinese characteristics; for example, a market with rapidly increasing prices and a sequence of policy recommendations. By focusing on total, directional and net spillovers, and using 2000–2017 monthly housing price data across six Chinese cities, this study’s results indicate that time-varying spillovers provide a better understanding of the interactions among first-tier cities. It is interesting to note that, following the downside risk faced by the economy in 2014, the spillovers among cities have been abruptly transformed into those exhibiting bilateral co-movements based on high total spillovers and low net spillovers, and these results are also confirmed by the frequency dynamics of spillovers. Based on the above, there is sufficient evidence to conclude that the housing frenzies in China, which have become a national-level issue, deserve a more explicit macrocontrol policy in relation to real estate assets. 在过去几年中，作为评估过热住房市场的一种方法，人们作出了诸多努力研究城市之间的溢出效应（涟漪效应）。然而，似乎缺失的是采用滚动窗口方法及时进一步研究时变溢出效应，以便更深入地研究中国住房市场的特征；例如，价格快速上涨的市场和一系列政策建议。通过关注总体、定向和净溢出效应，并使用中国六个城市2000-2017期间的月度房价数据，本项研究的结果表明，时变溢出效应可以让我们更好地理解一线城市之间的相互作用。值得注意的是，随着2014年经济面临下行风险，城市之间的溢出效应突然转为表现出高总溢出效应和低净溢出效应的双边共同运动，这些结果也得到了溢出效应频率动态的证实。综上，我们有充分的证据得出结论：中国疯狂的住房市场已成为国家层面的问题，应该对房地产资产采取更为明确的宏观调控政策。

The dynamics of neo-liberalised housing market skew distribution against low-income earners who have to be assisted with varying degrees of subsidies for equity. In Nigeria, this results in building public housing estates for low-Income earners. This group form the bulk of the society, running the wheels of economic and productive processes in any urbanisation.  As an indicator of the success of such subsidy regime, this study explored the extent to which the targeted poor had permanently benefited, taking Surulere Rehousing Estate (Scheme I) in Lagos, Nigeria as case study being typical of low-income Estates in Lagos. The study explored both primary and secondary data sources. A sample of 251 was systematically taken from the estate’s household population of 1,356 for service of structured questionnaire. The questions centred on identified variables of gentrification and related buyouts.  The data were processed with SPSS version 20.0 with the outcome in descriptive statistics. The study detected 53.4% buyout rate aside from 11.2% rental cases, especially because of locational advantages including central accessibility of the estate to most parts of Lagos City-State. Most historic low-income allottees, assisted with subsidy had largely yielded ownership and possession to other higher socio-economic class.  These confirm that the initial subsidy had largely ended up in the wrong pockets of a class which could ordinarily afford housing without it.  The study has highlighted the possible futility and therefore, non-sustainability of public policy efforts at subsidising low-income housing in its current form, in Lagos Nigeria.  Administrative, legal and possible taxation measures were proffered for sustainable subsidy practice in future projects.

This paper develops an artificial intelligence based automated valuation model (AI-AVM) using the boosting tree ensemble technique to predict housing prices in Singapore. We use more than 300,000 private and public housing transactions in Singapore for the period from 1995 to 2017 in the training of the AI-AVM models. The boosting model is the best predictive model that produce the most robust and accurate predictions for housing prices compared to the decision tree and multiple regression analysis (MRA) models. The boosting AI-AVM models explain 91.33% and 94.28% of the price variances, and keep the mean absolute percentage errors at 8.55% and 5.34% for the public housing market and the private housing market, respectively. When subject the AI-AVM to the out-of-sample forecasting using the 2018 housing sale samples, the prediction errors remain within a narrow range of between 5% and 9%.

Gangnam is a prime district in Korea known for its expensive real estate market due to convenient transportation, shopping and business centers, and elite schools and academies in the area. This paper examines spillovers and network connectedness in the Korean regional markets using the spillover index of Diebold and Yilmaz (J Econom 182:119–134, 2014). We use the quantile regression approach to investigate the macroeconomic factors driving the total spillover effects under low, normal, and high spillovers. We find that the 1997–1998 Asian currency crisis intensified regional spillovers in the Korean housing market. Moreover, Gangnam is the largest transmitter of spillovers across the regional housing markets in Korea. Our visual network illustrates that Gangnam is a hub of connectedness, implying that it is the most influential shock transmitter among the regional housing markets. Our study has an implication for investors: macroeconomic factors affect spillovers across regional housing sales and rental markets under different degrees of spillover.

Purpose In 2016, the Chinese central government decentralized the responsibilities of housing market regulation to the municipal level. This paper aims to assess whether the decentralized market regulation is effective. Design/methodology/approach This study first investigates the fundamental drivers of urban housing prices in China. Taking into consideration the factors driving housing prices, the authors further investigate the effectiveness of decentralized housing market regulation by a pre- and post-policy comparison test using a panel data set of 35 major cities for the years from 2014 to 2019. Findings The results reveal heterogenous policy effects on housing price growth among cities with a one-year lag in effectiveness. With the decentralized housing market regulation, cities with fast price growth are incentivized to implement tightening measures, while cities with relatively low housing prices and slow price growth are more likely to do nothing or deregulate the markets. The findings indicate that the shift from a centralized housing market regulation to a decentralized one is more appropriate and effective for the individual cities. Originality/value Few policy evaluation studies have been done to examine the effects of decentralized housing market regulation on the performance of urban housing markets in China. The authors devise a methodology to conduct a policy evaluation that is important to inform public policy and decisions. This study helps enhance the understanding of the fundamental factors in China’s urban housing markets and the effectiveness of municipal government interventions.

How does one tell when rapid growth in house prices is caused by fundamental factors of supply and demand and when it is an unsustainable bubble? In this paper, we explain how to assess the state of house prices—both whether there is a bubble and what underlying factors support housing demand—in a way that is grounded in economic theory. In doing so, we correct four common fallacies about the costliness of the housing market. For a number of reasons, conventional metrics for assessing pricing in the housing market such as price-to-rent ratios or price-to-income ratios generally fail to reflect accurately the state of housing costs. To the eyes of analysts employing such measures, housing markets can appear “exuberant” even when houses are in fact reasonably priced. We construct a measure for evaluating the cost of home owning that is standard for economists—the imputed annual rental cost of owning a home, a variant of the user cost of housing—and apply it to 25 years of history across a wide variety of housing markets. This calculation enables us to estimate the time pattern of housing costs within a market. As of the end of 2004, our analysis reveals little evidence of a housing bubble.

The cross-regional dependency in the UK housing market is analysed using regional house price indices. In this article, a network approach based on partial correlations is proposed, along with rolling-window analysis to consider potential time-varying dependency. The results show that house prices in the outer South East region have the strongest influence on regional housing market interactions in the UK. This influence is stronger when the markets are highly interconnected, whereas the house prices in London have the strongest influence when the UK regional housing markets are relatively less connected. 我们通过地区房价指数分析了英国住房市场的跨地区依赖性。本文提出了一种基于部分相关的网络方法，并结合滚动窗口分析来考察潜在的时变相关性。结果显示，在英国，东南部外围地区的房价对地区住房市场互动的影响最大。当市场高度关联时，这种影响更大，而当英国地区住房市场关联度相对较低时，伦敦房价的影响最大。