This study investigates the impact of social integration on immigrants' housing behaviours from a temporal perspective, using Singapore's differential public housing policies on immigrants as a quasi-natural experiment. With the support of a local town council, we conducted a survey on social integration among 1128 immigrant and local households living in public housing estates. In the public open rental housing market—primarily accommodating yet-to-integrate immigrants—we find immigrant renters live up to 3.04% farther from their workplace and pay lower rents up to 0.67% per additional year of residency. Such impacts are more substantial among minority ethnic groups. The results remain robust when using alternative subjective or objective measures of social integration. However, in the public resale housing market—primarily accommodating native and well-integrated naturalised citizens—we find that naturalised citizens face no price premiums relative to native homebuyers, implying no further effect of integration on housing prices after well-integration. This study extends the literature of spatial assimilation focusing on ethnic residential segregations and is generalizable to cities with few ethnic enclaves.

Over the past decade, governments around the world have made significant investments in creating elderly-friendly urban environments within local neighborhoods. However, the lack of a standardized evaluation framework for Ageing-in-Place (AIP) practices makes it challenging to generalize these experiences. First, we compare the AIP models of the U.S.-San Francisco, Japan-Tokyo, and Singapore using a cost-benefit analysis, demonstrating the comparative advantage of the Singapore model in terms of low cost and high accessibility for the independent ageing population. Second, we propose a spatial analytics framework to visualize and quantify the degree of alignment between a basket of ageing facilities and the active ageing population, enabling a data-driven, timely evaluation of the effectiveness of Singapore's AIP policies. Singapore's AIP model, either in its entirety or as a hybrid with other models, can be generalized to other global cities, providing valuable insights for optimal elderly-friendly urban planning.

Racial and ethnic discrimination represents a structural cause of payment disparities across groups. However, most studies focus on Western contexts and may overlook the distinctive sociohistorical dynamics that shape discriminatory behaviors. In Malaysia, where racial and ethnic relations have been influenced by a distinct colonial legacy and multicultural social fabric, landlords' discriminatory practices have manifested differently. This study reveals two novel mechanisms explaining racial and ethnic rent disparities in the Malaysian rental housing market: (i) taste-based discrimination, where landlords offer lower rents to tenants of the same race and ethnicity, and (ii) statistical discrimination, evidenced by Chinese tenants paying higher rents than tenants of other races and ethnicities, regardless of a landlord's race and ethnicity. These results highlight the need for greater policy attention to racial and ethnic disparities in the rental housing market and to the broader socio-economic inequalities that underpin them. By examining Malaysia's unique context, this study contributes to a more nuanced understanding of racial and ethnic rent disparities and provides valuable insights to inform more inclusive and equitable housing policies.

The high efficacy of metro network services not only enhances residents’ travel quality but also brings significant socio-economic benefits, thus is of great importance to urban land use and city development. Existing methods for measuring metro service efficacy often overlook metro network connectivity and rely heavily on subjective questionnaire data analysis from the user experience perspective. This paper proposes a method to measure metro network service efficacy from the user’s perspective. The approach first calculates the connectivity index of metro network and estimates the housing premium brought by metro network connectivity, which reveals users’ willingness to pay for metro network connectivity. This method objectively measures metro network service efficacy from the user’s perspective. Based on this, efficacy optimization methods are proposed, providing quantitative simulation methods for metro expansion, site selection, operation quality adjustments, etc., which are of great reference value to metro management departments and even urban sustainable development.

We identify three interrelated behavioral outcomes of the duration-dependent seller's stamp duty (SSD) implemented in the Singaporean private housing market and examine how it reduces market liquidity. An SSD lowers lock-in home sellers' opportunity cost of holding their properties through the lock-in period thresholds. Consequently, their selling prices are higher than non-lock-in home sellers. An SSD lowers their probability of home sales; the magnitude of this effect depends on the SSD's tax rate and tax rate deduction across a threshold. Moreover, an SSD drives some lock-in home sellers to lease out the properties at lowerents.

Understanding the intracity heterogeneities in housing market dynamics across microgeographic areas is important but challenging due to infrequent transactions. Unlike traditional methods that use trend-based clustering to improve the accuracy of local housing price and rent indices, we propose a novel hybrid model that combines the state-space model and the Bayesian nonparametric clustering approach to cluster neighbourhoods according to their temporal price volatility. We show that our methods improve the performance of traditional methods by 10-40%, using over 889,428 housing transactions in Singapore between 2006 and 2018. We also demonstrate a practical application of our method - monitoring neighbourhoods' distinct market reactions to macroeconomic or policy shocks, which has important implications for urban planning and housing investment.

We document racial payment disparities in the Malaysia rental market. Based on the unique historical context of Malaysia, we demonstrate a new mechanism that explains racial payment disparities in the Malaysian rental market: landlords are willing to offer a discount in rent to contract a tenant of the same ethnic background. The results also show that Chinese tenants pay significant highest rents among the three ethnic groups, regardless of the landlords' race. These results alert the Malaysian government to pay more attention to racial payment disparities in the rental housing market and the socioeconomic reasons behind them.

Imposing minimum green building (GB) standards is a regulatory tool for governments to engage the private sector in building green, but there is little evidence on policy outcomes. This paper looks at the details of minimum GB standards mandated in Singapore in 2008 and critically investigates whether, and to what extent, they affect GB adoption in the private housing market during 2005-2019 using data for 1078 projects and associated transactions. After the mandate, a new type of entry-level, low-performing GB that simply meets the minimum GB standards but is not Green Mark certified prevails in the private housing market. High-performing, certified GBs only slightly increase from 15 % of the market to 23 % in the years after the mandate. Further empirical analysis using logistic and hedonic regression methods shows that small and medium developers tend to build entry-level GBs for tradeoff between GB performance level and cost, while large developers are 7.8 times more likely to build and certify high-performing GBs. These results suggest that mandating minimum GB standards rather than GB certification can stimulate widespread adoption of GB practices in the private sector, but inadequately promotes high-performing GB development and offset the adverse effect of cost on developers' building green.

While mounting studies highlight the detrimental consequences of insufficient state governance on urban sprawl, there remains a scarcity of literature addressing the issue of robust state-led urban sprawl within the context of inadequate market discipline. This study investigates the institutional factors driving urban sprawl in China through a case study of Wuhan, exploring the impact of influential governmental bodies on the spatiotemporal characteristics of urban sprawl as reflected in stringent policy implementations and top-down planning institutions. By employing spatial measurements, statistical analysis, and policy interpretation based on extensive fieldwork data, we observed a marked intensification of leapfrogging urban land expansion accompanied by the encroachment of agricultural land between 1996 and 2014 in Wuhan. These transformations are predominantly attributable to a two-tiered institutional mechanism comprised of central-local and intra-city institutional changes. Temporal shifts in spatial expansion have been heavily influenced by the interplay between central transitional development policies and corresponding local planning responses. The choice of specific locations for land sprawl is governed by the interaction of different government levels, each focusing on local development strategies and land institutional arrangements. These findings offer novel insights into the global discourse surrounding the state-market relations in addressing urban sprawl and achieving sustainable urbanization.

Understanding the intracity heterogeneities in housing market dynamics across microgeographic areas is important but challenging due to infrequent transactions. Unlike traditional methods that use trend-based clustering to improve the accuracy of local housing price and rent indices, we propose a novel hybrid econometric and machine learning model that nonparametrically clusters neighbourhoods according to their temporal price volatility. We show that our methods improve the performance of traditional methods by 10-40%, using over 889,428 housing transactions in Singapore between 2006 and 2018. We also demonstrate a practical application of our method—monitoring neighbourhoods' distinct market reactions to macroeconomic or policy shocks, which has important implications for urban planning and housing investment.

We classify housing investors into flippers, rental housing investors and owner occupiers. We adopt the Singapore private housing transaction database between 2006 and 2010 to analyze their trading behaviors. The investigation period witnessed a full housing price cycle and had limited policy interventions. By comparing the trading behaviors of the three types of housing investors, we find that flippers can always buy at the highest price discounts and sell at the highest price premiums in housing transactions. Flippers show the highest propensity for trend chasing and act as momentum traders. When the housing market moves from its upward trend to a downward trend, flippers' price discounts at buying increases, but their likelihood of buying decreases, while flippers' price premiums at selling decrease, and their likelihood of selling increases. Rental housing investors show slightly higher price discounts at buying or price premiums at selling when trading with owner occupiers. However, they show a lower propensity for trend chasing than owner-occupiers. The findings have policy implications for anti-speculation policy designs.

Using the outbreak of COVID-19 in Singapore as a quasi-natural experiment, we investigate tenants' changing responses to road traffic noise in the rental housing market, using 46,980 transaction records between 2006 and 2022. Our difference-in-differences estimates show that road traffic noise decreases housing rents by 3.8% immediately after the pandemic outbreak and further declines by 12.7% in the subsequent year-equivalent to 186.7 US dollars per month. The results are robust to parallel trend analysis, permutation placebo tests, and tests using alternative distance thresholds or distance to the nearest main road. Then, we adopt a machine learning text analysis of 10,425 rental housing advertisements, showing that tenants' preference for quietness increases by approximately 10% from 2019 into 2020. The new work-from-home business model and rising traffic from delivery services can explain for this pattern. To the best of our knowledge, this is the first paper using a large volume of transaction records to quantify city dwellers' willingness to pay for quietness in the COVID-19 context. Our results have policy implications for other nations and post-pandemic era on the interaction among urban planning, transport networks, and human settlements, and shed light on the pathway to achieve sustainable development goals.

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Green building (GB) offers technical solutions to reduce the energy use in the building sector. Mandates have been widely used as a policy instrument for government to spur real estate developers to go green, and the implementation effect of mandates is a crucial concern to the government, scholars, and the public. But research on this issue remain understudied. Focusing on a mandatory GB regulation enacted in 2008 in Singapore, this paper investigates its implementation effect based on real estate developer behaviour and analyses how GB incremental costs affect the policy effectiveness in the hedonic regression and logistic regression analyses using the private housing market data. We find that by enforcing the minimum GB requirement, the regulation can effectively nudge developers to construct the lowest level of GBs, substantially accelerating GB development. But it can hardly motivate developers to proactively venture into greener certified buildings. The incremental costs of GBs significantly hinder developers from constructing greener certified buildings that are more costly than the lowest level of GBs. Our findings highlight the limitation of the mandatory regulation in promoting high-quality GB growth and the passive stance of private sector due to the cost barrier, generating important policy implications.

We identify four interrelated behavioral propositions after the implementation of a seller’s stamp duty (SSD) (a transaction tax on sellers who sell their properties within the SSD lock-in period) in the Singapore private housing market. First, SSD lock-in home sellers may sell their properties at a higher price than ordinary home sellers to cover the SSD tax (the price effect). Second, the SSD lowers the probability that a transaction takes place, prolonging SSD lock-in home sellers’ property holding period (the lock-in effect). The magnitude of this effect is determined by the strength of the SSD tax. Third, the lock-in effect drives some affected home sellers to become SSD lock-in landlords who lease out their properties at a lower rent (the rent effect). SSD lock-in landlords are forced to hold and rent out their properties, and thus, they may have lower search and bargaining power than ordinary landlords do, giving rise to a hidden tax benefit to tenants. Last, the price effect provokes ordinary home sellers to raise their reservation price (the contagion effect). This lowers their probability of finding a home buyer, which amplifies the lock-in effect on market-level illiquidity. Logical coherence and empirical identification of the intertwined behavioral outcomes after implementing an SSD are novel contributions to the literature. The findings have implications for policymakers in designing transaction taxes.

This paper incorporates environmental psychology insights into a well-being framework related to the built environment to predict the relations between green buildings and their residents in terms of pro-environmental behavior and well-being. To test our predictions, we apply a generalized structural equation modelling technique to a household survey dataset collected from the Singapore private housing market. We find that green building residents have a higher assessment of their residential environment. This increases the level of their residential satisfaction, which subsequently enhances their quality of life and reduces their intention to move. We demonstrate that green buildings provide a supportive and educational environment for motivating and educating their residents to behave in a pro-environmental manner. Residents' improved pro-environmental behavior and enhanced well-being are attributed to some, though not all, green features. We find that tangible green features (i.e., greenery, ventilation, indoor environments, and waste facilities) have greater impacts on residents than intangible ones (i.e., energy efficiency and accessibility to public transport). The findings contribute ideas and solutions to the future development of green buildings by taking a social perspective to pursue urban sustain ability. This paper also inspires future multi-disciplinary research at the intersection of urban studies, psychology, and behavioral science.

Green building (GB) offers technical solutions to reduce the energy use in the building sector. How to implement effective supply-side GB policies, such as the mandatory policies, to spur real estate developers to go green is meaningful for energy saving and sustainability in cities. However, few studies empirically examined the actual effects of the GB policies. This paper investigates real estate developers’ GB adoption under the mandatory GB policy in the Singapore context. Using data from the private housing market, our research design includes a hedonic regression analysis to examine the GB cost premiums and a logit model analysis to scrutinize the factors affecting a developer’s GB adoption and the impact changes before and after the mandatory policy. We find that the mandatory GB policy has limited effectiveness. It effectively promotes a large portion of developers to adopt GBs that merely meet the technical threshold prescribed by the policy but are not certified, but ineffectively motivates them to build certified greener buildings. GB cost premiums and weak corporate financial strength are found to negatively affect the policy effectiveness. The findings are helpful for policymakers to better understand developers’ behaviours in sustainable development and to improve the future government intervention schemes.

This study investigates impact of social integration on migrants’ economic behaviours from a new temporal perspective. We use Singapore’s unique differential public housing policies as a quasi-natural experiment, conducted a household survey on social integration among 1,128 migrants and local households living in public housing estates, and linked them with their nearest housing transaction records. In public open rental housing market, in which Singapore migrants in early post-migration years are permitted to reside, migrant renters select housing in areas up to 3.04% farther from their workplace with 1 more year of residency, physically and spatially making their way into the host society. Migrant renters also pay rents that are lower by up to 0.67% with 1 more year of post-migration residency. However, in public owner-occupied housing market, in which migrants are allowed to purchase their home after obtaining citizenship, there are no differences between local-born and converted-citizen homebuyers. Our results emphasize importance of integration policy at early stages of migration.

The housing market is thin. Buyers search and bargain in local housing markets, often paying different prices for nearly identical houses. Non-local homebuyers may have less information about the local housing market and may need to pay a higher search cost. Non-locals may also be anchored by housing prices in their original residential areas. Furthermore, homebuyers with different demographic characteristics, such as income, age, education, and occupation, may have different abilities and/or willingness to search and bargain for a good deal. Using a dataset from an emerging Chinese city, Tianjin, this study examines the impact of homebuyers’ heterogeneity on housing prices. The results show that non-locals pay more than locals and that an anchoring effect exists for non-locals from places with higher housing prices. We also find that buyers who are older and less educated, or who have a lower income or a lower rank in occupation, are likely to pay less. These findings have important policy implications.

We integrate a hedonic housing rent model (econometric approach) into a state-space model (reinforcement machine learning approach). We adopt the kalman filter and smoother recursive algorithm and the expectation maximization algorithm (statistical estimation methods) to estimate the proposed state-space housing rent hedonic model. The method is applied to the Singapore public open rental housing market to construct housing rent indexes. Compared with the conventional econometric methods in index construction, the proposed model has three advantages. Firstly, a state-space modeling approach technically allows us to construct neighborhood level housing rent indexes through a reinforcement learning process regardless the sample size in a neighborhood. Secondly, the expectation maximization algorithm effectively enhances the robustness of maximum likelihood estimation for a dataset being repleted with unobservable information, for example, fewer or zero transactions in certain time periods. Thirdly Kalman filter and smoother recursive algorithm optimizes the estimates by capturing all information (before and after a time point) to predict a housing rent at a time point. This helps reduce the bias caused by sticky rents. The paper empirically proves that the proposed model outperforms other types of index models in prediction accuracy, hence produces more accurate housnig rent indexes at neighborhood level. Accurately constructing neighborhood housing rent indexes are impotant in real estate valuation, real estate investment returns and risk analyses. This is because the spatial patterns of housing price distribution may change over time, which is resulted from urban developments. To illustrate it, we apply K-shape clustering algorithm in unsupervised machine learning literature to the neighborhood housing rent indexes to analyze the dynamic patterns of the spatial distribution of housing rents. We find the spatial discontinuity of housing rent dynamics. The housing rent indexes in some spatially disconnected neighborhoods appear to have similar dynamic pattern, while different dynamic patterns are found in some spatially adjacent neighbothoods. 1 School of Public Economics and Administration,Shanghai University of Finance and Economics,Shanghai, 200433,China 2 Department of Real Estate, School of Design and Environment, National University of Singapore, 4 Architecture Drive, Singapore 117566, Singapore. 2