Housing Transactions Research Articles

Lifelong Property Price Prediction: A Case Study for the Toronto Real Estate Market

We present LUCE, the first life-long predictive model for automated property valuation. LUCE addresses two critical issues of property valuation: the lack of recent sold prices and the sparsity of house data. It is designed to operate on limited volume of recent house transaction. As a departure from prior work, LUCE organizes the house data in a HIN where graph nodes are house entities and attributes that are important for house price valuation. We employ GCN to extract the spatial information from the HIN, and then use LSTM network to model the temporal dependencies over time. Unlike prior work, LUCE makes effective use of the limited house transactions in the past few months to update valuation information for all house entities. By providing a complete and up-to-date house valuation dataset, LUCE thus massively simplifies the downstream valuation task for the targeting properties. We demonstrate the benefit of LUCE by applying it to large, real-life datasets obtained from the Toronto real estate market. Extensive experimental results show that LUCE not only significantly outperforms prior property valuation methods but also often reaches and sometimes exceeds the valuation accuracy given by independent experts when using the actual realization price as the ground truth.

Conflicts of Interest and Agent Heterogeneity in Buyer Brokerage

This paper investigates the incentives of agents working with buyers (buying agents) under the fixed percentage commission system (FPCS) and the implications on housing market outcomes. Our model shows that the FPCS without a binding contract between the buyer and the buying agent could produce outcomes that are more equitable for buyers. The reason is that the absence of a binding contract helps mitigate the conflict of interest between the buyer with her agent and ensures a more faithful behavior of the buying agent. Our model shows that agent heterogeneity plays an important role in determining the binding force of the FPCS in the absence of a binding contract. Results from simulations and empirical analyses using house transactions in Canada support our model predictions.

Housing externalities and expectation channel: A quasi-experiment using public housing upgrading programs

The paper examines differences in housing externalities across regions with different political affiliations. Using a merged dataset containing data on public housing upgrading, resale public housing transactions, electoral boundaries and election results from 2010 to 2016 and a differences-in-discontinuity approach, we find evidence that public housing programs are expedited in ruling-party-held wards in periods leading up to the general elections relative to contesting wards. We also find that the unbalanced provision of upgrading programs leads to higher housing externalities for housing blocks in ruling-party-held wards than those for otherwise similar blocks in contesting wards. This paper provides new evidence on the expectation channel through which housing externalities may be affected.

Climate policy and transition risk in the housing market

Public policies aimed at mitigating climate change can come with the transition risk of sudden adjustments of asset prices. We study the consequences of a policy intervention addressing greenhouse gas emissions in the housing market. Leveraging a unique data set of the population of all house transactions in England and Wales, we document novel evidence of transition risk. Prices of carbon-intensive properties affected by this policy decreased by about £5,000 to £9,000 relative to unaffected ones. We interpret this result as evidence in favour of semi-strong market efficiency in the housing market. We infer moderate implications for financial stability and for the wealth distribution among homeowners.

북한지역 토지자산 추정에 관한 연구: 프레임워크 개발 및 탐색적 적용 (Estimating Land Assets in North Korea: Framework Development & Exploratory Application)

Korean Abstract: 본 연구는 북한당국이 발표하는 지역별 토지가격이나 토지의 특성에 관한 자료들이 없는 조건에서 북한지역의 토지가격과 토지자산의 규모를 추정하는 방법론과 모형을 제시하고 이를 이용하여 북한 시가화지역 전체를 대상으로 시장가격 기준의 토지자산 규모를 실험적으로 추정하였다. 우선 관련 사회경제적 변수를 이용가능하면서 최근의 북한과 소득수준의 격차가 상대적으로 크지 않았던 것으로 평가되는 남한의 1970년대 중후반, 그리고 도시화 수준이 유사했던 1980년대 초반 남한의 시, 군, 구별 실거래가격을 기준으로 시가화지역 토지에 대한 지가결정함수를 도출하였다. 다음으로 북한지역에 대한 지리정보분석을 통해 도출되는 지가결정요인의 대리변수들을 대입하여 2015년경 북한 시가화지역 토지의 시, 군, 구역별 상대가격비율을 산출하였다. 더 나아가서 최근 북한지역 일부 도시들을 대상으로 조사된 주택거래가격과 본고에서 추정한 상대가격비율을 결합하여 북한전역을 대상으로 시가화지역의 토지자산 규모를 추정하였다. 추정결과 북한 시가화지역의 토지가격은 시, 군, 구역별 상대가격비율로 볼 때 평양시 동대원구역이 100으로 제일 높고 양강도 풍서군이 1.70으로 가장 낮은 것으로 평가되었다. 한편 시가화지역의 토지자산 규모는 2015년 기준 216억 달러로 추정되었는데, 이는 동년 북한GDP의 0.72~1.33배에 달하는 규모이다. 이 비율은 남한의 1974~1978년 또는 중국의 2016년과 비슷한 데, 해당시기의 경제성장률이 남한은 평균 10.8%, 중국은 6.7%인데 반해 북한은 1%대 수준인 것을 고려하면 상당히 높은 것으로 보인다. 본 연구는 제한된 정보와 강한 가정에 근거하여 북한의 토지자산을 추정한 것으로 향후 전력, 용수 등 주거환경요인이나 도시개발계획 같은 정책요인들이 반영되도록 보완할 필요가 있으며 또한 본고의 추정결과를 활용함에 있어서 유의할 필요가 있음을 밝힌다. English Abstract: In this study, we present a methodology and model to estimate land prices and the value of land assets in North Korea in the absence of any data about land characteristics from North Korean authorities. Using this framework, we experimentally make market price-based estimates for land assets across the entire urban area of North Korea. First, we estimate the determinants of land prices in South Korea using data on market prices of land from the late 1970s, when it was estimated that the income level gap between South Korea and North Korea wasn’t relatively large, and from the early 1980s, when urbanization levels in both of them were similar. Second, we calculate land prices and their relative ratios for each city and urban area in North Korea around 2015 by substituting proxy variables of determinants of land prices derived through a geographic information analysis of North Korea into the function of land prices that we have already estimated. Finally, we estimate the value of land assets in urban areas across North Korea by combining the ratio of housing transaction prices surveyed in several cities in North Korea with the relative prices estimated in this research. As a result, land prices in urban areas in North Korea, looking at the relative ratio of price by city, are estimated to be the highest, at 100.00, in the Dongdaewon district of Pyongyang, and to be the lowest, at 1.70, in Poongseo County, Yanggang-do Province. Meanwhile, the value of land assets in urbanized areas was estimated at $21.6 billion in 2015, which was 0.72 to 1.33 times the GDP of North Korea that year. This ratio is similar to South Korea's in the 1974-1978 period or to China's in 2016, with an average economic growth rate of 10.8% in South Korea and 6.7% in China. Considering about a 1% economic growth rate, the land assets to GDP ratio in North Korea seems to be very high.

Ownership incentives and housing affordability: Evidence from France

Are ownership incentive policies inevitably accompanied by detrimental inflationary effects? To address this issue, we develop a theoretical model in which owners of new housing benefit from a homeownership subsidy or a rental investment incentive. We show that while both incentives increase the price of the new housing, they reduce old housing prices and have an ambiguous impact on the average housing price. These effects result from residential spillovers from the old housing market to the new housing market. We test these findings empirically by exploiting a 2014 French reform in the metropolitan area of Lyon which intensified both incentives. Difference-in-difference estimates confirm our theoretical predictions: two years after the reform, the price of new housing increased by 30% and the price of old housing decreased by 7%. Taking both markets together, the overall effect is non-significant. The share of new housing transactions increased by 25%.

An Analysis on Effects of Living SOC Installation and Urban Regeneration Project on Housing Transactions and Prices: Focusing on the case of Single and Multi-detached Houses in Gyeonggi

이 논문의 목적은 경기도를 사례로 읍면동 단위 생활SOC와 도시재생뉴딜 등 도시재생사업이 주택 거래 및 가격에 미친 영향을 분석하는데 있다. 이를 위하여 최소자승법(OLS), 공간종속모형, 공간오차모형, 지리적 가법모형 등 총 4개의 추정 모형을 활용하여 2017년 기준 경기도 읍면동별 단독다가구주택의 거래량 및 ㎡당 가격결정요인을 분석하였다. 실증분석 결과, 초등학교, 공공도서관이 많을수록 읍면동별 단독다가구주택 거래량이 많은 것으로 나타났고 도시재생 활성화구역이 지정된 구역이 있는 읍면동일수록 단독다가구주택 거래량이 많은 것으로 나타났다. 그리고 도시지역일수록, 시군구 인구가 많을수록, 시군구내 전입인구가 많을수록, 유아교육기관, 국공립어린이집, 약국 등 생활SOC가 많을수록 읍면동별 단독다가구주택의 ㎡당 가격이 높은 것으로 나타났다. 결론적으로, 주요 생활SOC 공급과 도시재생정책이 주택의 거래를 활성화시키고 가격을 상승시킴으로써 주민들의 자산가치 제고에 긍정적 영향을 주고 있음을 확인할 수 있었다. 분석모형 비교결과, 지리적 가법모형인 GGAM과 더불어 공간계량경제모형의 예측력이 OLS모형 보다 높은 것으로 나타났다. 이는 아파트단지 뿐만 아니라 단독다가구주택의 거래량과 가격 결정모형의 구축에 있어서도 공간적 종속성과 이질성을 고려하는 모형을 도입할 필요성이 있음을 의미한다.

Flood risk awareness and property values: evidences from Seoul, South Korea

ABSTRACT There is ongoing debate about flood risk discounts regarding property values. While some researchers claim that housing prices reflect flood risk, a growing body of literature has shown that flood risk is quickly forgotten after a flood event, and risk discounts are minimal in the long term. This study provides new evidence of flood risk discounts, with an emphasis on the role of flood risk awareness based on the case of Seoul, South Korea. This paper empirically examines how flood risk discounts vary depending on past flood experiences, and analyzes whether they are affected by the disclosure of inundation hazard maps. According to the results, flood risk discounts are disproportionally higher in districts with severe past flood experiences, but interestingly, there is no evidence that negative disclosure effects of hazard information on property values exist. These findings imply that home buyers carefully consider flood risk in their housing transactions in high flood risk areas, even before hazard maps become available, possibly because having flood insurance is rare in South Korea. Understanding the relationship between flood risk awareness and risk discounts in terms of property values has vital implications for disaster management policies as they relate to cities’ resilience. HIGHLIGHTS The flood risk discount in property values could be affected by the risk awareness. The risk discount is disproportionally high in areas with severe flooding experience. Negative disclosure effects of hazard map on property values do not exist in Seoul. Hazard disclosure could be actively used considering the level of the risk awareness.

Tax Evasion in the Housing Market: Identification and Exploration

The real estate market is recognized as a fertile ground for tax violations. Specifically, reporting a price lower than the true transaction price in order to avoid tax payments is a prevalent technique. We propose an empirical method for identifying housing transactions that are suspected of under-reporting. Based on all reported housing transactions in Israel over the period 1998–2015, we conclude that about 8% of the transactions are under-reported, with an average price report of 30% below the projected true price. Also, the likelihood to under-report is positively associated with the total tax liability and positively (negatively) associated with the crime rate in (the socioeconomic level of) the area in which the transaction occurs. Compared to single unit owners, real estate investors are less likely to engage in under-reporting. Our empirical approach may serve tax enforcement authorities in promoting tax collection in the real estate market.

Intrinsic Quasi-Periodicity in Hong Kong Housing Price and Its Prediction

Housing price time series is worth studying as it is closely related to the well-being of society. In the Hong Kong housing market from 1992 to 2010, signs of quasi-periodicity in housing price and transaction volume can be observed. We find that there is an overall periodicity of approximately 30 months in housing price changes and a strong lead–lag relationship between housing price and transaction volume. Analysis of the cross-covariance of the housing price, transaction volume and prime lending rate reveals that this quasi-periodicity is potentially driven by prime lending rates. Incorporation of quasi-periodicity into the kernel of Gaussian processes further enables us to construct a predictive model of the Hong Kong housing price trends that outperforms other traditional kernel functions.

Straw Purchase or Safe Haven? The Hidden Perils of Illicit Wealth in Property Markets

Real estate markets are highly vulnerable to inflows of illicit wealth, given the clandestine nature of dark money, making these activities difficult to detect and estimate. We exploit one of the largest offshore data leaks – the Panama Papers – to study how the associated individuals behave in housing transactions and quantify the effects of their housing market participation. We find that buyers linked to offshore secrecy purchase properties at a premium of 3.8%. Additional robustness and heterogeneity tests evidence that this premium is driven by these individuals’ secret funding and agenda to park money in properties as a safe haven. We further explore two policy shocks: the 2007 introduction of a cross-border cash movement policy and the 2010 implementation of the Estate Agents Regulations (EAW). After the former, the property selling prices of these individuals decreased by 5.5%, while their property purchase prices decreased by 2.7% after EAW. In addition, we document a negative externality of Panama-linked purchases on properties in the same projects and neighborhoods, revealing price increases of 5.1% and 7.3%, respectively. The back-of-the-envelope analysis further provides an aggregate estimate of illicit wealth in Singapore’s housing market, which is approximately S$0.65 billion to S$3.72 billion per year on average.

Valuation Modeling within Thin Housing Markets Case Study: Arab Housing Market in Israel

The primary aim of this paper is to introduce valuation modeling applicable to thin housing markets, with a focus on the Arab housing sector in Israel. The estimation procedure utilizes two input values: transaction data and subjective valuations provided by property owners, the data for which are derived from the Israel Tax Authority (ITA) and the Household Expenditure Survey (HES). Average property values are also weighted and ranked according to location, size, and average income factors. The main contribution of these modeling techniques is that they can be employed to estimate the residential property values in markets that experience a low frequency of housing transactions and where information is limited, with the added benefit of understanding housing value movement and market dynamics. Housing policies could be influenced by this deeper understanding of house price behavior within localities and submarkets, potentially with the ability to monitor changes in dwelling values and segmentation and segregation effects.

Predicting property prices with machine learning algorithms

ABSTRACT This study uses three machine learning algorithms including, support vector machine (SVM), random forest (RF) and gradient boosting machine (GBM) in the appraisal of property prices. It applies these methods to examine a data sample of about 40,000 housing transactions in a period of over 18 years in Hong Kong, and then compares the results of these algorithms. In terms of predictive power, RF and GBM have achieved better performance when compared to SVM. The three performance metrics including mean squared error (MSE), root mean squared error (RMSE) and mean absolute percentage error (MAPE) associated with these two algorithms also unambiguously outperform those of SVM. However, our study has found that SVM is still a useful algorithm in data fitting because it can produce reasonably accurate predictions within a tight time constraint. Our conclusion is that machine learning offers a promising, alternative technique in property valuation and appraisal research especially in relation to property price prediction.

Adaptive Reuse of Religious Heritage and Its Impact on House Prices

Due to social demographic change and secularization, religious heritage sites in Europe are on the verge of losing their original functions. While the adaptive reuse seems to be a proactive strategy to preserve the historical and cultural value embedded in religious heritage sites, little is known concerning its external impact. This paper aims to fill this gap by investigating the external effect of reusing religious heritage on surrounding house prices. Employing both the parametric and non-parametric difference-in-differences hedonic model on a sample of 42 projects of reusing religious heritage and a rich dataset of housing transactions in the Netherlands, we find significant positive externality of reusing religious heritage on local house prices. The external effects are heterogeneous across differentiated project size and monumental status. Larger religious heritage reuse projects and those listed as national monuments exert greater influence on surrounding house prices.

Environmental Risk and the Anchoring Role of Mobility Rigidities

AbstractWe analyze the anchoring role of mobility rigidities following a news shock on environmental risk. Using an exhaustive registry of housing transactions in England between 2007 and 2014, we ...

International Real Estate Review

Constructing multimodal stations is one of the considered ways to implement transit-oriented development (TOD), with the goal of synergizing land use and transportation to promote both greater transit accessibility and sustainability in urban areas. Improvements in such accessibility have led to an uplift in land value and housing prices. These price changes have been primarily studied by analyzing the effects of proximity to stations of a single line or multi-line mass rapid transit (MRT) system. However, little attention has been paid to investigating the effects of different types of multimodal MRTs and railway joined stations. The aim of this study is to investigate the different types of multimodal stations in Kaohsiung City, Taiwan. We use publicly available housing transaction data to construct hedonic price models. The results show that in the Kaohsiung MRT stations, an increase of 100 m in distance from the stations results in a TWD 258,000 decrease in the average housing price. The housing price elasticity with respect to a 1% increase in distance from these stations is -0.067%.

The political economy of historic districts: The private, the public, and the collective

This paper studies the political economy of historic district designation, with a focus on how historic district designation influences housing prices. I provide transaction-level empirical evidence from Denver, Colorado from 1990 to 2016 using hedonic price models with multiple fixed-effects. Results suggest that being in a historic district generates a 12–23% premium for house transactions after designation. Given the institutional context of Denver, I argue that one possible mechanism of the premium is the collective action problem in the historic district designation process. Meanwhile, a 10–20% positive spillover to the neighboring homes of historic districts is found, and the specific characteristics of historic districts influence the spillovers.

The Effect of the Reduction in the Interest Rate Due to COVID-19 on the Transaction Prices and the Rental Prices of the House

Purpose: This study uses 'Autoregressive Integrated Moving Average Model' to predict the impact of a sharp drop in the base rate due to COVID-19 at the present time when government policies for stabilizing house prices are in progress. The purpose of this study is to predict implications for the direction of the government's house policy by predicting changes in house transaction prices and house rental prices after a sharp cut in the base rate. Research design, data, and methodology: The ARIMA intervention model can build a model without additional information with just one time series. Therefore, it is a time-series analysis method frequently used for short-term prediction. After the subprime mortgage, which had shocked since the global financial crisis in April 2007, the bank's interest rate in 2020 is set at a time point close to zero at 0.75%. After that, the model was estimated using the interest rate fluctuations for the Bank of Korea base interest rate, the house transaction price index, and the house rental price index as event variables. Results: In predicting the change in house transaction price due to interest rate intervention, the house transaction price index due to the fall in interest rates was predicted to change after 3 months. As a result, it was 102.47 in April 2020, 102.87 in May 2020, and 103.21 in June 2020. It was expected to rise in the short term. In forecasting the change in house rental price due to interest rate intervention, the house rental price index due to the drop in interest rate was predicted to change after 3 months. As a result, it was 97.76 in April 2020, 97.85 in May 2020, and 97.97 in June 2020. It was expected to rise in the short term. Conclusions: If low interest rates continue to stimulate the contracted economy caused by COVID-19, it seems that there is ample room for house transaction and rental prices to rise amid low growth. Therefore, In order to stabilize the house price due to the low interest rate situation, it is considered that additional measures are needed to suppress speculative demand.

Valuing shale gas development in resource-dependent communities

Technological advances in oil and gas drilling have enabled the productive extraction of natural gas in new regions. The benefits from employment and income opportunities can help stimulate economies and may be valued by local residents. At the same time, however, shale gas activity can alter natural landscapes and is associated with negative externalities, including potential groundwater contamination. While some previous research has examined the impact of shale development, our paper focuses on the local impacts in West Virginia, a state with a long history of resource-extraction and one whose economy has lagged the nation. Because of its history of resource extraction, communities in West Virginia who may have limited other economic prospects may value the activity differently. Additionally, most of the previous research used data during the initial boom, ignoring the slowdown that followed. Using the coarsened exact matching (CEM) technique, we match houses near producing wells with other similar houses, in order to examine how property values in West Virginia are affected by proximity to horizontal producing wells. This technique helps compensate for the relatively small number of housing transactions in West Virginia, ensuring we have a good counterfactual. After matching, we estimate the average capitalization effect of houses near producing shale wells. We find that the price of all houses (regardless of water source) decreases as the number of surrounding wells increases. However, we also find some evidence that this effect varies over time and that the negative capitalization effect attenuates over space.

Localized or Regional? Urban Housing Policy Spillover in China’s Urban Agglomerations 2010–2018

AbstractSpatio-temporal model and event analysis were integrated in this paper, with 156 prefecture level cities’ housing transaction data and 167 items policies proposed by 10 central cities between January, 2010 and December, 2018 as samples. This paper studied the regional and cross-regional spillover effects of central cities’ urban housing regulation policies to the peripheral cities in the scope of urban agglomerations, as well as the policy-driven interactions of different regional real estate markets. The results indicated that: China’s regional housing market has obvious characteristics of policy orientation, of which the regulation measures on some central cities can affect the residential market and produce certain spillover interference on the market fluctuations of peripheral cities in time and space dimension. When geographical factor was considered, the 10 central cities had different degree of policy spillover effects caused by distinct policy types in their respective urban agglomerations. When ignoring spatial factors, restrictive policies in Beijing, Shanghai, Zhengzhou, Xi’an, Wuhan and Shenzhen had significant cross-regional spillover effects and drove the surrounding housing markets to have geared interactions, which to a certain extent revealed the flowing way of population and wealth in China’s regional economy during the past dozen years.