• Soft Computing and Machine Intelligence
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• v.1 no.1
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• pp.11-23
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• 2021

House price prediction is a significant financial decision for individuals working in the housing market as well as for potential buyers. From investment to buying a house for residence, a person investing in the housing market is interested in the potential gain. This paper presents machine learning algorithms to develop intelligent regressions models for House price prediction. The proposed research methodology consists of four stages, namely Data Collection, Pre Processing the data collected and transforming it to the best format, developing intelligent models using machine learning algorithms, training, testing, and validating the model on house prices of the housing market in the Capital, Islamabad. The data used for model validation and testing is the asking price from online property stores, which provide a reasonable estimate of the city housing market. The prediction model can significantly assist in the prediction of future housing prices in Pakistan. The regression results are encouraging and give promising directions for future prediction work on the collected dataset.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.44-48
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• 2015

Housing price is a key indicator of housing demand. Actual Transaction Price Index of Apartment (ATPIA) released by Korea Appraisal Board is useful to understand the current level of housing price, but it does not forecast future prices. Big data such as the frequency of internet search queries is more accessible and faster than ever. Forecasting future housing demand through big data will be very helpful in housing market. The objective of this study is to develop a forecasting model of ATPIA as a part of forecasting housing demand. For forecasting, a concept of time shift was applied in the model. As a result, the forecasting model with the time shift of 5 months shows the highest coefficient of determination, thus selected as the optimal model. The mean error rate is 2.95% which is a quite promising result.

• Journal of Cadastre & Land InformatiX
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• v.48 no.2
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• pp.197-211
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• 2018

We conducted this research to examine how well regional housing prices are suited to use as an alternative to conventional census-based regional deprivation indices in health and medical geography studies. To examine the relative performance of mean regional housing prices compared to conventional census-based regional deprivation indices, we compared several multilevel logistic regression models, where the first level was individuals and the second was health districts in the Seoul Metropolitan Area (SMA) in Korea, for the sake of adjusting the regional clustering tendency of unknown factors. In these models, we predicted two dichotomous variables that represented individuals' after-lunch tooth brushing behavior and use of dental floss by individual characteristics and regional indices. Then, we compared the relative predictive performance of the models using the Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC). The results from the estimations showed that mean regional housing prices and census-based deprivation indices were correlated with the two types of dental health behavior in a statistical sense. The results also revealed that the model with mean regional housing prices showed smaller AIC and BIC compared with other models with conventional census-based deprivation indices. These results imply that it is possible for housing prices summarized using aerial units to be used as an alternative to conventional census-based deprivation indices when the census variables employed cannot properly reflect the characteristics of the aerial units.

• Journal of the Korean housing association
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• v.19 no.5
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• pp.29-36
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• 2008

The objective of his study is to research the effect of the 'Dagagu' housing purchase and the public rental housing supply on the nearby community. In the case of public rental housing, many studies have demonstrated that the perception that a public rental house is a low income dwelling has an external effect on the residents immediately outside the area such as the perception of the lowering of house prices. However, an advanced research concerning the 'Dagagu' housing purchase and public rental housing has not been carried out because it has only recently been enforced. Through a survey conduced of residents who live nearby the 'Dagagu' housing purchase and public rental housing the aim of his study is to show how the residents perceive the renal houses and are influenced by them. At the same time, this study demonstrates the external effect of rental house supply by analyzing the housing price around the area. Most people who live in the near by 'Dagagu' housing purchase and public renal housing have a negative opinion of his housing because they believe that the residential prices will depreciate. However, only about 40% of the people felt that the residential price depreciation as a result of the 'Dagagu' housing purchase and public rental housing supply was not visible.

• Journal of Distribution Science
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• v.13 no.8
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• pp.61-71
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• 2015

Purpose - Before the year 2000, the housing prices in Korea were increasing every decade. After 2000, for the first time, Korea experienced a decrease in housing prices, and the repetitive cycle of price fluctuation started. Such a "boom and bust cycle" is a worldwide phenomenon. The current study proposes a mathematical model to explain price fluctuation cycles based on the theory of consumer psychology. Specifically, the model incorporates the effects of buyer expectations of future prices on actual price changes. Based on the model, this study investigates various independent variables affecting the amplitude of price fluctuations in housing markets. Research design, data, and methodology - The study provides theoretical analyses based on a mathematical model. The proposed model uses the following assumptions of the pricing mechanism in housing markets. First, the price of a house at a certain time is affected not only by its current price but also by its expected future price. Second, house investors or buyers cannot predict the exact future price but make a subjective prediction based on observed price changes up to the present. Third, the price is determined by demand changes made in previous time periods. The current study tries to explain the boom-bust cycle in housing markets with a mathematical model and several numerical examples. The model illustrates the effects of consumer price elasticity, consumer sensitivity to price changes, and the sensitivity of prices to demand changes on price fluctuation. Results - The analytical results imply that even without external effects, the boom-bust cycle can occur endogenously due to buyer psychological factors. The model supports the expectation of future price direction as the most important variable causing price fluctuation in housing market. Consumer tendency for making choices based on both the current and expected future price causes repetitive boom-bust cycles in housing markets. Such consumers who respond more sensitively to price changes are shown to make the market more volatile. Consumer price elasticity is shown to be irrelevant to price fluctuations. Conclusions - The mechanism of price fluctuation in the proposed model can be summarized as follows. If a certain external shock causes an initial price increase, consumers perceive it as an ongoing increasing price trend. If the demand increases due to the higher expected price, the price goes up further. However, too high a price cannot be sustained for long, thus the increasing price trend ceases at some point. Once the market loses the momentum of a price increase, the price starts to drop. A price decrease signals a further decrease in a future price, thus the demand decreases further. When the price is perceived as low enough, the direction of the price change is reversed again. Policy makers should be cognizant that the current increase in housing prices due to increased liquidity can pose a serious threat of a sudden price decrease in housing markets.

• Land and Housing Review
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• v.14 no.3
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• pp.55-75
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• 2023

Based on prior studies on real estate policy, tax policy, and financial policy, this study examined how tax policy and financial policy affected real estate prices using monthly data from January 2014 to December 2021. We performed a VAR model using unit root tests, cointegration tests, as well as conducted impulse response analysis and variance decomposition analysis. The results are as follows. First, the tax regulation index and the financial regulation index had no discernible impact on housing prices. Specifically, a one-sided stabilizing regulatory policy was ineffective and, instead, led to unintended side effects, such as price increases resulting from reduced transaction volume. Secondly, mortgage rates had a negative impact on the housing sale price index. In other words, an increase in interest rates might led to a decrease in housing prices. Thirdly, an increase in the transfer difference, which involves capital gains tax, has a positive effect on housing prices. This led to rising housing prices because the transfer taxes were shifted to buyers, causing them to hesitate to make purchases due to the increased tax burden. Fourthly, both acquisition taxes and mortgage loans had relatively little impact on housing prices.

• Environmental and Resource Economics Review
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• v.21 no.4
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• pp.999-1024
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• 2012

The Purpose of this study was to assess the willingness to pay(WTP) for the new road construction plan(slip road of urban highway which was advertising extensively to reduce the time to the core of metropolitan area) on housing prices using contingent valuation method(CVM). And this study was an empirical study which was based on the consciousness of residents whose apartment was within the Suwon Si's new plan of 47th road construction zone. In this study, it was revealed that the resident's WTP for the plan of new road construction which was built on the neighborhood of apartment was within the 10 percent of housing prices that was similar to the standard declared price of MLTM(Ministry of Land, Transport and Maritime Affairs). And also revealed that the difference of sale prices of real estate company was 24 percent. The statistical assessment results show that both the resident's characteristic variables such as gender, incomes, size of apartment and the accessability variables such as distance to parks, schools, department stores, living facilities were positive effects on the prices of apartments significantly. Finally, the house has depreciated than that of MLTM and WTO since torpedoed the road construction plan. These results imply that, we have to take capital appreciation of the property into account due to road construction since the accessibility was very significantly positive internal effects on the apartment housing prices.

• Land and Housing Review
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• v.9 no.4
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• pp.1-9
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• 2018

Since year 2000, French housing and rent prices rose at a rapid rate and the housing market has been overheated. Face to this phenomena, the French government enacted a new law Alur which is a legislatif tool to control the private housing rent price for the cities, where the tension of the housing market is very high. This new law has impacted the housing market in two major ways. First, for the 38 cities designated by this law, the rent price's increase rate can not rise above the IRL, which is the rent reference index. Secondly, this law also permits local authorities to control the housing rent's price following the concrete price guidance. Especially in Paris, the city applicated this method for private rental housing since 2015. This city classified its own area by 14 zones. Based on the market surveys of each sector, local authority made a guidance for private housing rent's price. The guideline is consisted of average prices, maxima and minima price by types, which is classified by the construction year, number of rooms and furnished or not. Therefore, this study aims to understand french housing rent's price control system and draw implementation for korean housing rent policies. This research is meaningful for it introduces recent foreign regislations which could be helpful to control the housing market in Korea.

• International conference on construction engineering and project management
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• 2013.01a
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• pp.151-157
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• 2013

Since the sub-prime mortgage crisis from the US in 2008, the Korean housing market has plummeted. However, the deposit prices of the Korean local lease contract, Chonsei, had been increasing. This increase of Chonsei prices can be a threat to low-income people, most of whom prefer to live in houses with a Chonsei contract. In the housing and Chonsei market, there are many stakeholders with their own interest, hence, simple thoughts about housing and Chonsei market, such as more house supply, will decrease house price, would not work in a real complex housing market. In this research, we suggests system dynamics conceptual model which consists of causal-loop-diagrams for the Chonsei market as well as the housing market. In conclusion, the Chonsei price has its own homeostasis characteristics and different price behavior with housing price in the short and long term period. We found that unless government does not have a structural causation mind in implementing policies in the real estate market, the government may not attain their intended effectiveness on both markets.

• The Journal of Economics, Marketing and Management
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• v.12 no.2
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• pp.61-71
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• 2024

Purpose: This study explores the impact of discrimination experience on stress levels among Seoul's public housing complex residents, emphasizing the moderating role of social capital. Research design, data and methodology: Utilizing the 2019 Seoul public housing (PH) panel data and an ordered logit model, the research categorizes residents based on personal and environmental factors, contrasting them across different local housing price levels. Results: We find that public housing residents' experience of discrimination has a significant impact on stress, and local housing prices are positively related to stress. Interestingly, stress due to discrimination is more pronounced in high-priced neighborhoods, which are associated with real estate inequality. Conversely, this impact is less pronounced in lower-priced neighborhoods. Importantly, social capital not only has a significant moderating effect on stress for all residents, but in high-priced neighborhoods, it also moderates the stress caused by experiences of discrimination for social housing residents. Conclusions: These findings highlight the need for policy interventions to strengthen social capital and address socioeconomic disparities in public housing, and are significant for analyzing the nuanced relationship between neighborhood, housing affordability, discrimination, and stress in urban communities for public housing residents, which is a socially problematic issue.