House Sales Research Articles

HOUSING MARKET DISCOUNT RATES: EVIDENCE FROM BARGAINING AND BIDDING WARS

AbstractWhen selling a home, through the choice of the list price, sellers make a trade‐off between achieving a quick sale at a low price or waiting for higher bids. This list‐price setting decision is governed by a discount rate. Using data on housing sales in the Netherlands, we derive gross discount rates under bilateral bargaining and bidding wars. The estimated discount rates are 25%–35%, which are considerably higher than long‐run housing market discount rates and may result from the seller's unfamiliarity with the selling process. The rates are higher for sellers that already moved and have a low education.

Financing Brownfield Redevelopment and Housing Market Dynamics: Evidence from Connecticut

Brownfield redevelopment projects are often perceived as more risky than greenfield investment, and financing opportunities may be more limited and expensive. Different financial support projects have been developed to support regeneration projects, and empirical evidence has shown that all buildings near the intervention area may benefit from an increase in prices once the brownfield project is complete. The article considers the Connecticut market and evaluates the characteristics of the brownfield projects that had access to a financial support program (loan or grant), the impact of the regeneration process on the liquidity of the housing market, and the gap between the price and the appraisal value of the residential unit. Target areas for this type of financing program are mainly characterized by low income, a high density of population, a high incidence of homeowners, and a high crime rate. Once completed, the brownfield requalification has an impact on the housing market because the brownfield recovery reduces the number of house sales due to the increase in the average price in the surrounding area and makes the selling price more consistent with the appraisal valuation. The empirical evidence provided may be useful for public institutions that are suffering from budget constraints and have to prioritize areas for financial support solutions.

The Government Legal Warranty for Consumers in The Purchase of Property in Indonesia

Introduction: The sale and purchase of houses between developers and buyers often result default, which detrimental to consumers. The state has issued various policies regarding buying and selling houses and legal guarantees for buying and selling houses, but violations still occur and there is no legal guarantee from the state but must be resolved through litigation.Purposes of the Research: The purpose of this study is to analyze and find problems with house sale and purchase contracts based on the Sale and Purchase AgreementMethods of the Research: The method used in this research is normative juridical. The research used is library research. The basis used in this research is the juridical basis consisting of Law Number 1 of 2011, GovernmentRegulation Number 12 of 2021. Results of the Research: When the state issues permits to operate housing to developers, the state has provided a legal guarantee to protect its people. Due to the guarantees that have given by the Government through statutory regulations and consumers following the instructions, they are guaranteed to receive legal protection from the state, State Administrative Officials, in terms of granting permits they have gone through applicable legal procedures, if it is proven otherwise then the government must be responsible for the decision. State Administration. However, if there is a violation of the law by the developer, it will difficult for home buyers to claim losses. Experienced, meaning that at the implementation level there is no guarantee for buyers from the state.

The relationship of single-family detached house prices with neighborhood walkability and disaster risk.

People's preferences regarding their neighborhood environment can vary depending on their socioeconomic status and the cities where they live. This study aims to discern the relationship between neighborhood environment factors and single-family detached house sales by sale price and by central and noncentral cities. We analyzed sale prices in the Tokyo Metropolitan Area from 2015 to 2020. The neighborhood environment was assessed using flood/sediment risk and neighborhood walkability measured by net residential density, intersection density, and facility density (walking opportunity). Flood and sediment risk is a major concern that restricts the available land and is included as a negative aspect of the neighborhood environment, taking the topographic features into consideration. A comparison of the results showed that the preference for neighborhood walkability varies by socioeconomic status as well as by target cities. For most facility types, the number of walking opportunities within walking distance from houses was found to be positively related to the sale price of single-family detached houses in all quantiles. The relationship of house price with population and intersection density was found to vary depending on the price level, with a negative relationship with the sale price of relatively more expensive houses being exhibited. People who considered buying houses with relatively higher sale prices were found to devalue houses located in flood/sediment-hazardous areas more. However, it was also found that the negative relationship was slightly mitigated in the highest quantile of sale prices for houses in areas with a moderate flood risk (maximum flooding depth: 3-5 m). Plains near rivers with amenities offer high walkability but pose a flood risk, resulting in a trade-off between flood risk and neighborhood walkability. The findings suggest the use of indices representing diverse preferences in accordance with the target socioeconomic status when policymakers assess the neighborhood environment.

Kekeliruan Hakim dalam Memutus Perkara Penipuan pada Pangadilan Negeri Sidoarjo

This study aims to determine whether there are elements of fraud in the case contained in Decision Number 115/Pid.B/2021/PN.SDA. This research is based on the reality related to business in the housing industry which is currently growing rapidly but so many default cases are carried out by the developers themselves. As in the case that I am currently investigating, namely Decision Number 115/Pid.B/2021/PN.SDA. The method used in this study is a normative legal research method using a statutory approach by using primary legal materials consisting of statutory regulations and secondary legal materials obtained from several books, journals, and articles. The results of the study conclude that, there is a decision by the Panel of Judges in deciding the case on Decision Number 115/Pid.B/2021/PN.SDA because the elements that cannot be submitted to. Based on the comparison between the actions taken with the elements of error in the default, it was stated that as the director of PT. A has committed an act of default for not carrying out the performance according to what has been agreed with the Buyer as a victim in the sale and purchase of a residential house.

Citizenship by investment in Türkiye: Who buys citizenship and why?

ABSTRACT This study investigates the motives of those who want to acquire Turkish citizenship through investment. We conducted in-depth interviews with 45 people consisting of new citizens and intermediaries who assist foreigners in housing sales and citizenship applications in eight different provinces. Our study reveals that people from countries geographically close to Türkiye and global investors show significant interest in the citizenship program, which enables them to become Turkish citizens through investment. Importantly, we found that the tendency for investment is influenced by Türkiye’s bilateral relations with investors’ countries of origin, the relatively lower monetary barrier for investment encourages the migration of low-capital groups in search of a better life, and citizenship by investment facilitates capital transfer between countries.

Covid-19s Influence on the Sale of Chinese Commercial Residential HousingEvaluation Analysis Based on Multi Variable Linear Regression Model

In January 8th, 2023, Chinese government officially terminated its quarantine policies after the publication of The Overall Plan of Implementing Category B Management Measures to Covid-19 As a Category B Infectious Disease, since then, Chinese society entered into a brand new phase of the recovery of economic production. Next, in January 17th, 2023, the vice prime minister He Liu made a speech about his optimistic opinions about future Chinese Housing Market in the annual meeting of Davos Forum. This paper chooses the sale of Chinese commercial residential housing as the research object and acquires annual data of Chinese Housing Market since 1998 from Huibo terminal platform and Qianzhan database as the experimental data. This paper uses STATA to model experimental data and conducts research of the sale of Chinese commercial residential housing through the method of linear regression analysis. Bases on the analysis of the experimental data, this paper finds out the conclusion that covid-19 causes significant impacts toward the sale of Chinese commercial residential housing. Bases on the fitting result derived from the fitting analysis of the sale of Chinese commercial residential housing from 2022 to 2024 in the experimental model, it points out that there is going to be significant recovery in Chinese housing market from 2023 to 2024.

Sistem Informasi Pemasaran Perumahan Pusaka Bumi Menggunakan View 360 Berbasis WEB

Pusaka Bumi Housing which is under the auspices of PT. Istia Jaya Land is located at Jln. Parungkuda Scouts, Parungkuda District, Kab. Sukabumi, West Java Province. PT.Istia Jaya Land is a company engaged in the sale of houses. The housing marketing team still uses conventional methods in marketing the housing, such as still using brochures, which in general, the contents of the brochures are not in accordance, starting from the 3D house drawings, which are different from the unit designs of the original housing, and seem unrealistic, so it confuses many potential buyers. feel disinterested. so researchers designed a Housing Marketing Information System Using view 360. In making this website the aim is for housing marketing in order to increase the attractiveness of prospective buyers and also the competitiveness of the housing. Housing Marketing using View 360 Based on this website can provide unique experience benefits for prospective buyers and will also be more effective. First, by using View 360 Technology, prospective buyers can take a Virtual Tour through the housing website online, without having to physically visit the location. This allows them to view and explore every corner of the room, layout, and housing facilities from the comfort of their own home. The use of view 360 in housing marketing can increase the attractiveness of prospective buyers and the competitiveness of these housing. In a competitive environment, housing with a virtual 360 view tour has an advantage over one that only uses regular photos. This can attract potential buyers, increase the visibility of housing, and speed up the selling process. The results of this information system design are expected to be able to provide convenience in terms of promotion for Bumi Pusaka Housing.

Comparing simple and complex regression models in forecasting housing price: case study from Kenya

PurposeThe housing market in Kenya continues to experience an excessive imbalance between supply and demand. This imbalance renders the housing market volatile, and stakeholders lose repeatedly. The purpose of the study was to forecast housing prices (HPs) in Kenya using simple and complex regression models to assess the best model for projecting the HPs in Kenya.Design/methodology/approachThe study used time series data from 1975 to 2020 of the selected macroeconomic factors sourced from Kenya National Bureau of Statistics, Central Bank of Kenya and Hass Consult Limited. Linear regression, multiple regression, autoregressive integrated moving average (ARIMA) and autoregressive distributed lag (ARDL) models regression techniques were used to model HPs.FindingsThe study concludes that the performance of the housing market is very sensitive to changes in the economic indicators, and therefore, the key players in the housing market should consider the performance of the economy during the project feasibility studies and appraisals. From the results, it can be deduced that complex models outperform simple models in forecasting HPs in Kenya. The vector autoregressive (VAR) model performs the best in forecasting HPs considering its lowest root mean squared error (RMSE), mean absolute error (MAE), mean absolute percentage error (MAPE) and bias proportion coefficient. ARIMA models perform dismally in forecasting HPs, and therefore, we conclude that HP is not a self-projecting variable.Practical implicationsA model for projecting HPs could be a game changer if applied during the project appraisal stage by the developers and project managers. The study thoroughly compared the various regression models to ascertain the best model for forecasting the prices and revealed that complex models perform better than simple models in forecasting HPs. The study recommends a VAR model in forecasting HPs considering its lowest RMSE, MAE, MAPE and bias proportion coefficient compared to other models. The model, if used in collaboration with the already existing hedonic models, will ensure that the investments in the housing markets are well-informed, and hence, a reduction in economic losses arising from poor market forecasting techniques. However, these study findings are only applicable to the commercial housing market i.e. houses for sale and rent.Originality/valueWhile more research has been done on HP projections, this study was based on a comparison of simple and complex regression models of projecting HPs. A total of five models were compared in the study: the simple regression model, multiple regression model, ARIMA model, ARDL model and VAR model. The findings reveal that complex models outperform simple models in projecting HPs. Nonetheless, the study also used nine macroeconomic indicators in the model-building process. Granger causality test reveals that only household income (HHI), gross domestic product, interest rate, exchange rates (EXCR) and private capital inflows have a significant effect on the changes in HPs. Nonetheless, the study adds two little-known indicators in the projection of HPs, which are the EXCR and HHI.

Estimating proximity effects to wildfire fuels treatments on house prices in Cibola National Forest, New Mexico, USA

Forested landscapes in the Western United States are subject to growing size and severity of wildfires, in part due to historical management strategies focusing on wildfire suppression. Forest restoration treatments and fuels reductions, including thinning and prescribed burning, can reduce the frequency and intensity of wildfires. Extensive restoration and fuels treatment efforts are underway across many areas in the Southwestern United States, including New Mexico. The tradeoff between amenity values provided by forested landscapes and the wildfire risk associated with forested landscapes is becoming increasingly important to understand as development in the wildland-urban interface increases. Understanding how house proximity, relative to forest restoration or fuels treatments, is capitalized into home sale prices can provide useful information about how individuals value forested landscapes that have been altered to reduce wildfire risk or severity. We use a Hedonic Property Model to estimate the average treatment effect of proximity to forest restoration or fuel treatments in New Mexico, United States. We use matching methods to estimate the average treatment effect of proximity to forest restoration. We find that proximity to the forest has a positive amenity value; however, proximity to recent forest restoration or fuel treatments results in a decrease in house sale prices. We combine the results of our two models and calculate that homes not within one kilometer of a treated forest and within one kilometer of Cibola National Forest sell for an average $73,626 premium. The average premium drops to $22,996 for homes within one kilometer of a forest that has been recently treated and within one kilometer of Cibola National Forest.

Reaping the premium in urban redevelopment

IntroductionThis paper investigates new new-built premium in urban redevelopments. Constructing new homes on urban redevelopment sites entails additional investments in reshaped lay-out, refurbished infrastructure, and upgraded outdoor areas. These improvements are expected to yield new-build premiums when the new units are put on the market, with ‘premium’ defined as the extra price that a developer asks for, compared to similar units in the second-hand market, in nearby locations. We askDo urban redevelopment schemes create extra new-build premiums? Does the organisation of redevelopments affect the size of the premium and who harvests it? Method and dataIn focus here are redevelopment schemes in Oslo, Norway, 2002–2015. It distinguishes between four types of developments: greyfield, brownfield and two kinds of infill. This distinction is applied to compare new-build premiums in various redevelopments. As the value-added from upgraded redevelopment may spill over to adjacent neighbourhoods, we also analyse whether such neighbourhoods experience hikes in house-prices. Our dataset consists of sales transactions from approx. 90,000 second-hand house sales and 19,000 new house sales. Results/findingsThe premium for new-builds in relation to second-hand sales varies significantly among the types of development. Units in small infill developments entail significantly higher new-built premiums than units in large brownfield- or greyfield redevelopments. Moreover, some schemes show a negative new-build premium. Examination of existing houses nearby shows a hike in prices in the time-span in question. We conclude that the new-build premium is low, and that developers fail to harvest full new-build premiums in urban redevelopment schemes. DiscussionIn interpreting our findings, we revisit ‘rent-gap theory’ and its emphasis on attracting investment to rundown central areas. Concurrence in scale, design and time helps to explain the differences across types of redevelopments, and why what might be expected to be new-build premiums instead raise prices in existing neighbouring areas.

Analyzing Factors Influencing Purchase Intention for Residential Property Developer on Bandung Barat Regency : A Study on Advertisement, Sales Promotion, Online and Social Media Marketing, and Product Attributes

MSMEs is the most important pillar to the Indonesia economy because the contribution of this segment is 60,5% to the GDP of Indonesia. Also contribute 96,9% of total national absorption employment. One of the MSME sectors is residential construction. In 2020, the backlog of Indonesia is 12,75 million which means there are 12,75 million families that did not own the house so the demand for residential property is high. There are many residential property companies that serve the low income segment. One of them is a residential property developer that the author does research for and is one of the residential property companies that is now experiencing decline in sales. They sell the house in the low income segment in Bandung Barat regency in Indonesia. So when a pandemic hits, the buying power of this segment is getting lower. They focus on buying the essential daily needs such as food and drink, the plan for buying a house will be postponed until their economy gets better. To this scenario, the company must change the segment market to target new potential customers or adjust the product to still be affordable to this segment. Based on preliminary research, the author found that there is a shift on choosing the channel for seeking a house from offline to online. The purpose of this study is to identify the factors that influence residential property company house sales and to increase sales of house products. This study uses qualitative and quantitative methods. The qualitative method utilised in preliminary research by interviewing business owner and employee of the company. The quantitative method utilised by questionnaires that are distributed to potential customers. The sample of this research consists of 200 respondents taken by non-probability sampling. The questionnaire will use a likert scale with 5 levels, representing an interval scale. The data analysis methods used are validity test, reliability test, and hypothesis testing using SPSS. Based on the research result, advertising, sales promotion, online and social media marketing, and product attributes have a significant influence on purchase intention.

Real Estate Price Prediction Using Artificial Intelligence

The sales of houses are influenced by various factors such as location, area, population, and other relevant information. Predicting individual housing prices can be instrumental in estimating future real estate prices. This study employs the Random Forest algorithm, a machine learning technique, as the primary methodology for developing a housing price prediction model. By focusing on the Random Forest algorithm, this project aims to optimize prediction accuracy and consistency, considering it as the best model for price prediction. The implementation of this project involves using Python (AI/ML) for coding the Random Forest algorithm, while HTML, CSS, and JS are employed for designing the system's frontend. Ultimately, the House Price Prediction system proves to be a valuable tool for accurately assessing property prices and maintaining a record of price fluctuations, promoting transparency and discouraging fraudulent activities.

El desajuste entre la oferta y la demanda de vivienda, y su relación con los precios

Rationale Analysis of recent housing supply and demand trends, and of the factors contributing to them, is extremely useful to detect the emergence or existence of imbalances in the housing market, which is characterised by long lead times for house building. Takeaways •After the initial impact of the pandemic, the recovery in demand for owner-occupied housing nationwide has outpaced the recovery in supply, which is less flexible in the short term. This has led to a certain mismatch between supply and demand and to upward pressures on house prices. •In recent years, there has also been a widespread supply shortage at the regional level. The prices of owner-occupied housing have risen more in regions where housing has been in relatively shorter supply. •Although the cost of credit has risen, house prices will foreseeably continue to show greater downward stickiness, in nominal terms, than residential housing market variables such as house sales or building permits, owing to the dearth of new construction work, the high costs of building materials and the favourable financial situation of the different housing market agents.

Housing affordability in the capital cities of three Northwestern China provinces

PurposePrevious studies on housing affordability in China were concentrated in China’s coastal and central regions. The purpose of this paper is to investigate housing affordability of urban residents in Northwest China. Moreover, this paper attempts to understand the consistency and influencing factors of various indicators on the evaluation of housing affordability.Design/methodology/approachThis paper uses multiyear data on house sales, residents’ incomes and living expenses from 2011 to 2022. House price-to-income ratio, housing affordability index and residual income approach were calculated by using these data and used as the measure of housing affordability.FindingsThe results show that there are obvious differences in the housing affordability among the Xi’an, Lanzhou and Yinchuan during 2011–2022, and the housing affordability of residents in cities with small population and economic scale is better. The ability of most urban residents to afford suitable housing is still poor, and the ability to afford small-sized housing is better. Most families with below-middle income have poor housing affordability. It is also observed that although various indicators had similarities in the evaluation of residents’ housing affordability, the comprehensive evaluation results of multiple indicators were more reliable.Social implicationsThe research results provide a basis for the decision-making of the government’s urban housing policy and improvement of residents’ housing conditions.Originality/valueThe results have a clear understanding of the housing affordability of urban residents in Northwest China. The study found that the geographical location and topography of the city is also a factor affecting the housing affordability.

Viewshed effects and house prices: Identifying the visibility value of the natural landscape

The visibility value of the natural landscape is a difficult concept to quantify. Using GIS techniques we create variables for measuring the visibility value of coasts and natural open areas in a spatial hedonic model of house prices. Data come from repeated house sales for the city of Haifa (Israel). As visibility of amenities often interacts with other variables such as location, we suggest approaches for dealing with this identification problem. We exploit the multi-level structure of the data to estimate spatial panel models with multi-level random effects for identifying the visibility value of natural landscapes. The estimated results show first, that visibility of coast and natural open space adds to the value of house prices regardless of their location. Second, the effect of proximity of natural landscapes on house prices is determined by the trade-off between positive and negative externalities generated by these amenities. Third, we find that viewshed effects are sensitive to different ranges of visibility.

Impact of demolitions on neighboring property values in Detroit

AbstractUrban blight is a complex problem that has been challenging for cities in the United States “Rust Belt” region for many decades. However, in the wake of the real estate and financial crisis, it is also a growing challenge for urban communities in many states such as California, Arizona, Nevada, and Texas. Detroit was particularly hit hard, where more than 40,000 blighted structures were identified in 2014. To curb blight, the city mobilized the most extensive demolition program in the country. Funded through the Federal Hardest Hit Fund (HHF), the Detroit Demolition Program began in 2014 and has demolished more than 20,800 properties at the cost of over $250 million. Furthermore, during 2009–2015, the city demolished 11,400 structures with hazardous materials such as asbestos. In this article, we assess the impacts of demolitions on the value of neighboring properties using a Repeat Sales (RS) regression approach. Specifically, we use housing sales price information from 2009 through 2019 to construct real estate price indices. We also rely on information from the 2009 Detroit Residential Survey to differentiate by dilapidation and blight levels before the start of the program. On average, blight removal through the demolition program does not appear to have been capitalized into the residential property prices. However, when considering the effect of ex‐ante program property characteristics, we find a modest positive effect of demolitions on property prices in areas with a low level of blight before the demolitions. Given the magnitude of the observed effect and the high costs associated with the demolition program, our results highlight the need for further research on alternative blight removal strategies that might provide a more cost‐effective solution to this urban challenge.

Keabsahan Transaksi Jual Beli Rumah Ditinjau Dari Kitab Undang-Undang Hukum Perdata

Buying and selling is a legal relationship that has rights and obligations between the parties, including house buying and selling transactions through a House Sale and Purchase Agreement (PPJB) and Sale and Purchase Deed (AJB) carried out in front of a notary. The study has a goal, namely to find out and analyze the validity of buying and selling transactions of houses in the perspective of the Civil Code. Juridical-normatic is used as a research method whose approach is in the form of laws and literature studies. The result of this study is a house sale and purchase agreement, namely a special agreement whose rules are contained in Article 1457 of the Civil Code. The validity of this sale and purchase refers to Article 1320 of the Civil Code concerning the legal terms of the agreement. Buying and selling houses is carried out through various stages, namely the preparation of PPJB, payment of seller and buyer taxes and the process of transferring the name in AJB before a notary. Legitimacy can occur if the making of this agreement is not because there is a forced withdrawal from any party,, does not violate the provisions of laws and regalutions, decency and the public interest.

Delineating Housing Submarkets Using Space–Time House Sales Data: Spatially Constrained Data-Driven Approaches

With the increasing availability of large volumes of space–time house data, delineating space–time housing submarkets is of interest to real estate agents, homebuyers, urban policymakers, and spatial researchers, among others. Appropriately delineated housing submarkets can help nurture submarket monitoring and housing policy developments. Although submarkets are often expected to represent areas with similar houses, neighborhoods, and amenities characteristics, delineating spatially contiguous areas with virtually no fragmented small areas remains challenging. Furthermore, housing submarkets can potentially change over time along with concomitant urban transformations, such as urban sprawl, gentrification, and infrastructure improvements, even in large metropolitan areas, which can complicate delineating submarkets with data for lengthy time periods. This study proposes a new method for integrating a random effects model with spatially constrained data-driven approaches in order to identify stable and reliable space–time housing submarkets, instead of their dynamic changes. This random effects model specification is expected to capture time-invariant spatial patterns, which can help identify stable submarkets over time. It highlights two spatially constrained data-driven approaches, ClustGeo and REDCAP, which perform equally well and produce similar space–time housing submarket structures. This proposed method is utilized for a case study of Franklin County, Ohio, using 19 years of space–time private house transaction data (2001–2019). A comparative analysis using a hedonic model demonstrates that the resulting submarkets generated by the proposed method perform better than popular alternative submarket creators in terms of model performances and house price predictions. Enhanced space–time housing delineation can furnish a way to better understand the sophisticated housing market structures, and to help enhance their modeling and housing policy. This paper contributes to the literature on space–time housing submarket delineations with enhanced approaches to effectively generate spatially constrained housing submarkets using data-driven methods.

청년층의 공공분양주택 선호 연구

In order to solve the housing problem of young people, the government announced a plan to supply public housing for sale that combine affordable housing prices and groundbreaking mortgage support. In this study, a survey was conducted to understand the young people's preference for the newly proposed public housing for sale, and the housing perception and demographic characteristics of young people who prefer public housing for sale were analyzed. In addition, through a survey on the policy direction and detailed conditions, it was intended to propose a model of public housing for sale that young people want. The results of analysis are summarized as follows. First, as a result of the survey, 49.8% of the respondents preferred public housing for sale, and such a high preference indicates the need to expand the supply of affordable public housing for sale. Second, since there are differences of opinion on the detailed conditions related to the benefits and restrictions of public housing for sale, it is necessary to set reasonable standards. Third, for young people with relatively lower assets, it is essential to provide cheonsei loans and public rental housing support to secure the current residential stability. Fourth, it is important to supply public housing with high-quality residential and educational environments for young people planning to marry and give birth. The results of the study are meaningful in that they clarify whether public housing for sale can serve as an alternative to solving the housing problem of young people, and present guidelines such as policy direction and detailed conditions.