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style="font-size:.9rem"><span class="badge badge-info">1784</span> Factors Influencing the Housing Price: Developers’ Perspective</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ernawati%20Mustafa%20Kamal">Ernawati Mustafa Kamal</a>, <a href="https://publications.waset.org/abstracts/search?q=Hasnanywati%20Hassan"> Hasnanywati Hassan</a>, <a href="https://publications.waset.org/abstracts/search?q=Atasya%20Osmadi"> Atasya Osmadi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The housing industry is crucial for sustainable development of every country. Housing is a basic need that can enhance the quality of life. Owning a house is therefore the main aim of individuals. However, affordability has become a critical issue towards homeownership. In recent years, housing price in the main cities has increased tremendously to unaffordable level. This paper investigates factors influencing the housing price from developer’s perspective and provides recommendation on strategies to tackle this issue. Online and face-to-face survey was conducted on housing developers operating in Penang, Malaysia. The results indicate that (1) location; (2) macroeconomics factor; (3) demographic factors; (4) land/zoning and; (5) industry factors are the main factors influencing the housing price. This paper contributes towards better understanding on developers’ view on how the housing price is determined and form a basis for government to help tackle the housing affordability issue. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=factors%20influence" title="factors influence">factors influence</a>, <a href="https://publications.waset.org/abstracts/search?q=house%20price" title=" house price"> house price</a>, <a href="https://publications.waset.org/abstracts/search?q=housing%20developers" title=" housing developers"> housing developers</a>, <a href="https://publications.waset.org/abstracts/search?q=Malaysia" title=" Malaysia"> Malaysia</a> </p> <a href="https://publications.waset.org/abstracts/41899/factors-influencing-the-housing-price-developers-perspective" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/41899.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">396</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1783</span> Preference for Housing Services and Rational House Price Bubbles</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Stefanie%20Jeanette%20Huber">Stefanie Jeanette Huber</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper explores the relevance and implications of preferences for housing services on house price fluctuations through the lens of an overlapping generation’s model. The model implies that an economy whose agents have lower preferences for housing services is characterized with lower expenditure shares on housing services and will tend to experience more frequent and more volatile housing bubbles. These model predictions are tested empirically in the companion paper Housing Booms and Busts - Convergences and Divergences across OECD countries. Between 1970 - 2013, countries who spend less on housing services as a share of total income experienced significantly more housing cycles and the associated housing boom-bust cycles were more violent. Finally, the model is used to study the impact of rental subsidies and help-to-buy schemes on rational housing bubbles. Rental subsidies are found to contribute to the control of housing bubbles, whereas help-to- buy scheme makes the economy more bubble-prone. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=housing%20bubbles" title="housing bubbles">housing bubbles</a>, <a href="https://publications.waset.org/abstracts/search?q=housing%20booms%20and%20busts" title=" housing booms and busts"> housing booms and busts</a>, <a href="https://publications.waset.org/abstracts/search?q=preference%20for%20housing%20services" title=" preference for housing services"> preference for housing services</a>, <a href="https://publications.waset.org/abstracts/search?q=expenditure%20shares%20for%20housing%20services" title=" expenditure shares for housing services"> expenditure shares for housing services</a>, <a href="https://publications.waset.org/abstracts/search?q=rental%20and%20purchase%20subsidies" title=" rental and purchase subsidies"> rental and purchase subsidies</a> </p> <a href="https://publications.waset.org/abstracts/46437/preference-for-housing-services-and-rational-house-price-bubbles" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/46437.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">299</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1782</span> Prediction on Housing Price Based on Deep Learning</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Li%20Yu">Li Yu</a>, <a href="https://publications.waset.org/abstracts/search?q=Chenlu%20Jiao"> Chenlu Jiao</a>, <a href="https://publications.waset.org/abstracts/search?q=Hongrun%20Xin"> Hongrun Xin</a>, <a href="https://publications.waset.org/abstracts/search?q=Yan%20Wang"> Yan Wang</a>, <a href="https://publications.waset.org/abstracts/search?q=Kaiyang%20Wang"> Kaiyang Wang</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In order to study the impact of various factors on the housing price, we propose to build different prediction models based on deep learning to determine the existing data of the real estate in order to more accurately predict the housing price or its changing trend in the future. Considering that the factors which affect the housing price vary widely, the proposed prediction models include two categories. The first one is based on multiple characteristic factors of the real estate. We built Convolution Neural Network (CNN) prediction model and Long Short-Term Memory (LSTM) neural network prediction model based on deep learning, and logical regression model was implemented to make a comparison between these three models. Another prediction model is time series model. Based on deep learning, we proposed an LSTM-1 model purely regard to time series, then implementing and comparing the LSTM model and the Auto-Regressive and Moving Average (ARMA) model. In this paper, comprehensive study of the second-hand housing price in Beijing has been conducted from three aspects: crawling and analyzing, housing price predicting, and the result comparing. Ultimately the best model program was produced, which is of great significance to evaluation and prediction of the housing price in the real estate industry. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=deep%20learning" title="deep learning">deep learning</a>, <a href="https://publications.waset.org/abstracts/search?q=convolutional%20neural%20network" title=" convolutional neural network"> convolutional neural network</a>, <a href="https://publications.waset.org/abstracts/search?q=LSTM" title=" LSTM"> LSTM</a>, <a href="https://publications.waset.org/abstracts/search?q=housing%20prediction" title=" housing prediction"> housing prediction</a> </p> <a href="https://publications.waset.org/abstracts/84747/prediction-on-housing-price-based-on-deep-learning" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/84747.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">307</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1781</span> Estimation of Break Points of Housing Price Growth Rate for Top MSAs in Texas Area</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Hui%20Wu">Hui Wu</a>, <a href="https://publications.waset.org/abstracts/search?q=Ye%20Li"> Ye Li</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Applying the structural break estimation method proposed by Perron and Bai (1998) to the housing price growth rate of top 5 MSAs in the Texas area, this paper estimated the structural break date for the growth rate of housing prices index. As shown in the estimation results, the break dates for each region are quite different, which indicates the heterogeneity of the housing market in response to macroeconomic conditions. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=structural%20break" title="structural break">structural break</a>, <a href="https://publications.waset.org/abstracts/search?q=housing%20prices%20index" title=" housing prices index"> housing prices index</a>, <a href="https://publications.waset.org/abstracts/search?q=ADF%20test" title=" ADF test"> ADF test</a>, <a href="https://publications.waset.org/abstracts/search?q=linear%20model" title=" linear model"> linear model</a> </p> <a href="https://publications.waset.org/abstracts/145280/estimation-of-break-points-of-housing-price-growth-rate-for-top-msas-in-texas-area" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/145280.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">150</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1780</span> Beijing Xicheng District Housing Price Econometric Analysis: “Multi-School Zoning”Policy</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Haoxue%20Cui">Haoxue Cui</a>, <a href="https://publications.waset.org/abstracts/search?q=Sirui%20Zhang"> Sirui Zhang</a>, <a href="https://publications.waset.org/abstracts/search?q=Shanshan%20Gao"> Shanshan Gao</a>, <a href="https://publications.waset.org/abstracts/search?q=Weiyi%20Zhang"> Weiyi Zhang</a>, <a href="https://publications.waset.org/abstracts/search?q=Lantian%20Wang"> Lantian Wang</a>, <a href="https://publications.waset.org/abstracts/search?q=Xuanwen%20Zheng"> Xuanwen Zheng</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The 2020 "multi-school zoning" policy makes students ineligible for direct attendance in their district. To study whether the housing price trend of the school district is affected by the policy, This paper studies housing prices based on the school district division in Xicheng District, Beijing. In this paper, we collected housing prices and the basic situation of communities from "Anjuke", which were divided into two periods of 15 months before and after the 731 policy in the Xicheng District, Beijing. Then we used DID model and time fixed effect to investigate the DIFFERENTIAL statistics, that is, the overall net impact of the policy. The results show that the coefficient is negative at a certain statistical level. It indicates that the housing prices of school districts in the Xicheng district decreased after the "multi-school zoning" policy, which shows that the policy has effectively reduced the housing price of school districts in the Xicheng District and laid a foundation for the "double reduction" policy in 2022. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=%E2%80%9Cmulti-school%20zoning%E2%80%9Dpolicy" title="“multi-school zoning”policy">“multi-school zoning”policy</a>, <a href="https://publications.waset.org/abstracts/search?q=DID" title=" DID"> DID</a>, <a href="https://publications.waset.org/abstracts/search?q=time%20fixed%20effect" title=" time fixed effect"> time fixed effect</a>, <a href="https://publications.waset.org/abstracts/search?q=housing%20prices" title=" housing prices"> housing prices</a> </p> <a href="https://publications.waset.org/abstracts/149435/beijing-xicheng-district-housing-price-econometric-analysis-multi-school-zoningpolicy" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/149435.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">160</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1779</span> The Impact of Public Open Space System on Housing Price in Chicago</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Si%20Chen">Si Chen</a>, <a href="https://publications.waset.org/abstracts/search?q=Le%20Zhang"> Le Zhang</a>, <a href="https://publications.waset.org/abstracts/search?q=Xian%20He"> Xian He</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The research explored the influences of public open space system on housing price through hedonic models, in order to support better open space plans and economic policies. We have three initial hypotheses: 1) public open space system has an overall positive influence on surrounding housing prices. 2) Different public open space types have different levels of influence on motivating surrounding housing prices. 3) Walking and driving accessibilities from property to public open spaces have different statistical relation with housing prices. Cook County, Illinois, was chosen to be a study area since data availability, sufficient open space types, and long-term open space preservation strategies. We considered the housing attributes, driving and walking accessibility scores from houses to nearby public open spaces, and driving accessibility scores to hospitals as influential features and used real housing sales price in 2010 as a dependent variable in the built hedonic model. Through ordinary least squares (OLS) regression analysis, General Moran’s I analysis and geographically weighted regression analysis, we observed the statistical relations between public open spaces and housing sale prices in the three built hedonic models and confirmed all three hypotheses. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=hedonic%20model" title="hedonic model">hedonic model</a>, <a href="https://publications.waset.org/abstracts/search?q=public%20open%20space" title=" public open space"> public open space</a>, <a href="https://publications.waset.org/abstracts/search?q=housing%20sale%20price" title=" housing sale price"> housing sale price</a>, <a href="https://publications.waset.org/abstracts/search?q=regression%20analysis" title=" regression analysis"> regression analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=accessibility%20score" title=" accessibility score"> accessibility score</a> </p> <a href="https://publications.waset.org/abstracts/114572/the-impact-of-public-open-space-system-on-housing-price-in-chicago" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/114572.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">133</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1778</span> Imbalance on the Croatian Housing Market in the Aftermath of an Economic Crisis</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Tamara%20Sli%C5%A1kovi%C4%87">Tamara Slišković</a>, <a href="https://publications.waset.org/abstracts/search?q=Tomislav%20Sekur"> Tomislav Sekur</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This manuscript examines factors that affect demand and supply of the housing market in Croatia. The period from the beginning of this century, until 2008, was characterized by a strong expansion of construction, housing and real estate market in general. Demand for residential units was expanding, and this was supported by favorable lending conditions of banks. Indicators on the supply side, such as the number of newly built houses and the construction volume index were also increasing. Rapid growth of demand, along with the somewhat slower supply growth, led to the situation in which new apartments were sold before the completion of residential buildings. This resulted in a rise of housing price which was indication of a clear link between the housing prices with the supply and demand in the housing market. However, after 2008 general economic conditions in Croatia worsened and demand for housing has fallen dramatically, while supply descended at much slower pace. Given that there is a gap between supply and demand, it can be concluded that the housing market in Croatia is in imbalance. Such trend is accompanied by a relatively small decrease in housing price. The final result of such movements is the large number of unsold housing units at relatively high price levels. For this reason, it can be argued that housing prices are sticky and that, consequently, the price level in the aftermath of a crisis does not correspond to the discrepancy between supply and demand on the Croatian housing market. The degree of rigidity of the housing price can be determined by inclusion of the housing price as the explanatory variable in the housing demand function. Other independent variables are demographic variable (e.g. the number of households), the interest rate on housing loans, households' disposable income and rent. The equilibrium price is reached when the demand for housing equals its supply, and the speed of adjustment of actual prices to equilibrium prices reveals the extent to which the prices are rigid. The latter requires inclusion of the housing prices with time lag as an independent variable in estimating demand function. We also observe the supply side of the housing market, in order to explain to what extent housing prices explain the movement of new construction activity, and other variables that describe the supply. In this context, we test whether new construction on the Croatian market is dependent on current prices or prices with a time lag. Number of dwellings is used to approximate new construction (flow variable), while the housing prices (current or lagged), quantity of dwellings in the previous period (stock variable) and a series of costs related to new construction are independent variables. We conclude that the key reason for the imbalance in the Croatian housing market should be sought in the relative relationship of price elasticities of supply and demand. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Croatian%20housing%20market" title="Croatian housing market">Croatian housing market</a>, <a href="https://publications.waset.org/abstracts/search?q=economic%20crisis" title=" economic crisis"> economic crisis</a>, <a href="https://publications.waset.org/abstracts/search?q=housing%20prices" title=" housing prices"> housing prices</a>, <a href="https://publications.waset.org/abstracts/search?q=supply%20imbalance" title=" supply imbalance"> supply imbalance</a>, <a href="https://publications.waset.org/abstracts/search?q=demand%20imbalance" title=" demand imbalance"> demand imbalance</a> </p> <a href="https://publications.waset.org/abstracts/52032/imbalance-on-the-croatian-housing-market-in-the-aftermath-of-an-economic-crisis" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/52032.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">273</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1777</span> Role of Tourism in Increasing of Price of Land and Housing in Iran: Case Study of Shahmirzad City</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Hamidreza%20Joodaki">Hamidreza Joodaki</a>, <a href="https://publications.waset.org/abstracts/search?q=Sara%20Farzaneh"> Sara Farzaneh</a>, <a href="https://publications.waset.org/abstracts/search?q=Jaleh%20Afshar%20Qhazvin"> Jaleh Afshar Qhazvin </a> </p> <p class="card-text"><strong>Abstract:</strong></p> Tourism industry is considered as the greatest and most various industry in the world. Most of these countries know this dynamic industry as main source of income, occupation, growth of private sector and development of infrastructure. One of the old methods of investment in countries such as Iran have transitional economy, is buying land and house, sometimes is resulted to high profit and of course for this reason hustler's are very interested in this background. Nowadays buying and selling land in the areas with pleasant climate in our country is considered. Since, Shahmirzad is a city with fair and desired environmental attractions is located in the border of deserted cities, mainly has special climatic position and these conditions are resulted to attraction of passenger, tourist for passing their leisure hours from Semnan and other cities of the area and from other provinces in hot seasons and with regard to these suitable conditions in the city buying land and housing also have been considered by most of residents of Semnan and cities around Shahmirzad by now. The aim of present research is investigation the role of tourism in increasing price of land and housing in Shahmirzad city. By studying on price of land and housing especially in central area, that gardens of the city are located in this area, we have concluded that role of tourism have caused in price of land and housing specially these prices in central and old areas are more expensive than towns around the city. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=tourism" title="tourism">tourism</a>, <a href="https://publications.waset.org/abstracts/search?q=climate%20conditions" title=" climate conditions"> climate conditions</a>, <a href="https://publications.waset.org/abstracts/search?q=price%20of%20land%20and%20housing" title=" price of land and housing"> price of land and housing</a>, <a href="https://publications.waset.org/abstracts/search?q=Shahmirzad" title=" Shahmirzad "> Shahmirzad </a> </p> <a href="https://publications.waset.org/abstracts/11698/role-of-tourism-in-increasing-of-price-of-land-and-housing-in-iran-case-study-of-shahmirzad-city" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/11698.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">297</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1776</span> Estimating Housing Prices Using Automatic Linear Modeling in the Metropolis of Mashhad, Iran</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mohammad%20Rahim%20Rahnama">Mohammad Rahim Rahnama</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Market-transaction price for housing is the main criteria for determining municipality taxes and is determined and announced on an annual basis. Of course, there is a discrepancy between the actual value of transactions in the Bureau of Finance (P for short) or municipality (P´ for short) and the real price on the market (P˝). The present research aims to determine the real price of housing in the metropolis of Mashhad and to pinpoint the price gap with those of the aforementioned apparatuses and identify the factors affecting it. In order to reach this practical objective, Automatic Linear Modeling, which calls for an explanatory research, was utilized. The population of the research consisted of all the residential units in Mashhad, from which 317 residential units were randomly selected. Through cluster sampling, out of the 170 income blocks defined by the municipality, three blocks form high-income (Kosar), middle-income (Elahieh), and low-income (Seyyedi) strata were surveyed using questionnaires during February and March of 2015 and the information regarding the price and specifications of residential units were gathered. In order to estimate the effect of various factors on the price, the relationship between independent variables (8 variables) and the dependent variable of the housing price was calculated using Automatic Linear Modeling in SPSS. The results revealed that the average for housing price index is 788$ per square meter, compared to the Bureau of Finance’s prices which is 10$ and that of municipality’s which is 378$. Correlation coefficient among dependent and independent variables was calculated to be R²=0.81. Out of the eight initial variables, three were omitted. The most influential factor affecting the housing prices is the quality of Quality of construction (Ordinary, Full, Luxury). The least important factor influencing the housing prices is the variable of number of sides. The price gap between low-income (Seyyedi) and middle-income (Elahieh) districts was not confirmed via One-Way ANOVA but their gap with the high-income district (Kosar) was confirmed. It is suggested that city be divided into two low-income and high-income sections, as opposed three, in terms of housing prices. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=automatic%20linear%20modeling" title="automatic linear modeling">automatic linear modeling</a>, <a href="https://publications.waset.org/abstracts/search?q=housing%20prices" title=" housing prices"> housing prices</a>, <a href="https://publications.waset.org/abstracts/search?q=Mashhad" title=" Mashhad"> Mashhad</a>, <a href="https://publications.waset.org/abstracts/search?q=Iran" title=" Iran"> Iran</a> </p> <a href="https://publications.waset.org/abstracts/42519/estimating-housing-prices-using-automatic-linear-modeling-in-the-metropolis-of-mashhad-iran" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/42519.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">255</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1775</span> Microeconomic Consequences of the Housing Market Deformation in the Selected Region of the Czech Republic</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Hana%20Jan%C3%A1%C4%8Dkov%C3%A1">Hana Janáčková</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Housing can be sorted as basic needs of households. Purchase of acceptable ownership housing is important investments for most them. For rental housing households must consider the part of rent expenditure paid in the total household income. For this reason, financial considerations of households in this area depend on the government innervations (public administration) in housing - on housing policy. Market system of housing allocation, whether ownership or tenancy, is based on the fact that housing is a scarce good. The allocation of housing is based on demand and supply. The market system of housing can sometimes have a negative impact on some households, the market is unable to satisfy certain groups of the population that are not able or willing to accept market price. For these reasons, there is a more or less regulation of the market. Regulation is both on the demand and supply side, and the state determines the rules of behaviour for all economic entities of the housing market. This article submits results of analysis of selected regulatory interference of the state in the housing market and assesses their implications deforming the market in the selected region of the Czech Republic. The first part describes tools of supports and the second part discusses deformations and analyses their consequences on the demand side of housing market and on supply side. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=housing" title="housing">housing</a>, <a href="https://publications.waset.org/abstracts/search?q=housing%20market" title=" housing market"> housing market</a>, <a href="https://publications.waset.org/abstracts/search?q=microeconomic%20consequences" title=" microeconomic consequences"> microeconomic consequences</a>, <a href="https://publications.waset.org/abstracts/search?q=deformation" title=" deformation"> deformation</a> </p> <a href="https://publications.waset.org/abstracts/64218/microeconomic-consequences-of-the-housing-market-deformation-in-the-selected-region-of-the-czech-republic" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/64218.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">399</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1774</span> Identifying the Malaysian Perception on the Self-Build Home Concept: Provision of Affordable Housing for MIG </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=N.%20M.%20Tawil">N. M. Tawil</a>, <a href="https://publications.waset.org/abstracts/search?q=A.%20R.%20Musa"> A. R. Musa</a>, <a href="https://publications.waset.org/abstracts/search?q=A.%20I%20Che-Ani"> A. I Che-Ani</a>, <a href="https://publications.waset.org/abstracts/search?q=H.%20Basri"> H. Basri</a> </p> <p class="card-text"><strong>Abstract:</strong></p> It is known that rising of house prices recently has affected the home ownership, especially for the future. Hence to overcome the rose of housing prices, the self-build home or DIY concept is perceived as one of the solution. This concept is proposed to be implemented for the future housing design as a strategy in helping the government to provide affordable housing, especially for middle income group to own a landed housing property. This concept is expected to offer a lower housing price for middle-income buyers and provide an opportunity for buyers to design their dream’s home with the self-build home or 'Do It Yourself' (DIY) concept. In order to implement this concept as affordable housing for MIG, the public perceptions and acceptances on the self-build home/ DIY concept itself should be identified. To achieve this aim this study was conducted by using 2 method namely literature review and questionnaire survey. The questionnaire survey was distributed to 200 respondents randomly in Lembah Klang and were analysed through the SPSS program. The results show that respondents are very interested in buying a home that they can have with the appropriate size of the home. Average of them known about Do It Yourself (DIY) concept but none of respondent have implement this concept. Most of respondents were agreed that this DIY method suitable to be implemented in the housing industry in Malaysia and they were agreed that this concept can offer a cheaper housing price because the construction costs were reduced. Moreover by providing a basic home the owner can renovate their home according to their need and financial capability. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=affordable%20housing" title="affordable housing">affordable housing</a>, <a href="https://publications.waset.org/abstracts/search?q=Do%20It%20Yourself" title=" Do It Yourself"> Do It Yourself</a>, <a href="https://publications.waset.org/abstracts/search?q=self-Built%20home" title=" self-Built home"> self-Built home</a>, <a href="https://publications.waset.org/abstracts/search?q=perception" title=" perception"> perception</a>, <a href="https://publications.waset.org/abstracts/search?q=middle%20income%20group" title=" middle income group"> middle income group</a> </p> <a href="https://publications.waset.org/abstracts/24992/identifying-the-malaysian-perception-on-the-self-build-home-concept-provision-of-affordable-housing-for-mig" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/24992.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">414</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1773</span> Housing Price Dynamics: Comparative Study of 1980-1999 and the New Millenium</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Janne%20Engblom">Janne Engblom</a>, <a href="https://publications.waset.org/abstracts/search?q=Elias%20Oikarinen"> Elias Oikarinen</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The understanding of housing price dynamics is of importance to a great number of agents: to portfolio investors, banks, real estate brokers and construction companies as well as to policy makers and households. A panel dataset is one that follows a given sample of individuals over time, and thus provides multiple observations on each individual in the sample. Panel data models include a variety of fixed and random effects models which form a wide range of linear models. A special case of panel data models is dynamic in nature. A complication regarding a dynamic panel data model that includes the lagged dependent variable is endogeneity bias of estimates. Several approaches have been developed to account for this problem. In this paper, the panel models were estimated using the Common Correlated Effects estimator (CCE) of dynamic panel data which also accounts for cross-sectional dependence which is caused by common structures of the economy. In presence of cross-sectional dependence standard OLS gives biased estimates. In this study, U.S housing price dynamics were examined empirically using the dynamic CCE estimator with first-difference of housing price as the dependent and first-differences of per capita income, interest rate, housing stock and lagged price together with deviation of housing prices from their long-run equilibrium level as independents. These deviations were also estimated from the data. The aim of the analysis was to provide estimates with comparisons of estimates between 1980-1999 and 2000-2012. Based on data of 50 U.S cities over 1980-2012 differences of short-run housing price dynamics estimates were mostly significant when two time periods were compared. Significance tests of differences were provided by the model containing interaction terms of independents and time dummy variable. Residual analysis showed very low cross-sectional correlation of the model residuals compared with the standard OLS approach. This means a good fit of CCE estimator model. Estimates of the dynamic panel data model were in line with the theory of housing price dynamics. Results also suggest that dynamics of a housing market is evolving over time. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=dynamic%20model" title="dynamic model">dynamic model</a>, <a href="https://publications.waset.org/abstracts/search?q=panel%20data" title=" panel data"> panel data</a>, <a href="https://publications.waset.org/abstracts/search?q=cross-sectional%20dependence" title=" cross-sectional dependence"> cross-sectional dependence</a>, <a href="https://publications.waset.org/abstracts/search?q=interaction%20model" title=" interaction model"> interaction model</a> </p> <a href="https://publications.waset.org/abstracts/50416/housing-price-dynamics-comparative-study-of-1980-1999-and-the-new-millenium" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/50416.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">251</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1772</span> Housing Price Prediction Using Machine Learning Algorithms: The Case of Melbourne City, Australia</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=The%20Danh%20Phan">The Danh Phan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> House price forecasting is a main topic in the real estate market research. Effective house price prediction models could not only allow home buyers and real estate agents to make better data-driven decisions but may also be beneficial for the property policymaking process. This study investigates the housing market by using machine learning techniques to analyze real historical house sale transactions in Australia. It seeks useful models which could be deployed as an application for house buyers and sellers. Data analytics show a high discrepancy between the house price in the most expensive suburbs and the most affordable suburbs in the city of Melbourne. In addition, experiments demonstrate that the combination of Stepwise and Support Vector Machine (SVM), based on the Mean Squared Error (MSE) measurement, consistently outperforms other models in terms of prediction accuracy. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=house%20price%20prediction" title="house price prediction">house price prediction</a>, <a href="https://publications.waset.org/abstracts/search?q=regression%20trees" title=" regression trees"> regression trees</a>, <a href="https://publications.waset.org/abstracts/search?q=neural%20network" title=" neural network"> neural network</a>, <a href="https://publications.waset.org/abstracts/search?q=support%20vector%20machine" title=" support vector machine"> support vector machine</a>, <a href="https://publications.waset.org/abstracts/search?q=stepwise" title=" stepwise"> stepwise</a> </p> <a href="https://publications.waset.org/abstracts/98230/housing-price-prediction-using-machine-learning-algorithms-the-case-of-melbourne-city-australia" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/98230.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">231</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1771</span> Housing Prices and Travel Costs: Insights from Origin-Destination Demand Estimation in Taiwan’s Science Parks</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Kai-Wei%20Ji">Kai-Wei Ji</a>, <a href="https://publications.waset.org/abstracts/search?q=Dung-Ying%20Lin"> Dung-Ying Lin</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This study investigates the impact of transportation on housing prices in regions surrounding Taiwan's science parks. As these parks evolve into crucial economic and population growth centers, they attract an increasing number of residents and workers, significantly influencing local housing markets. This demographic shift raises important questions about the role of transportation in shaping real estate values. Our research examines four major science parks in Taiwan, providing a comparative analysis of how transportation conditions and population dynamics interact to affect housing price premiums. We employ an origin-destination (OD) matrix derived from pervasive traffic data to model travel patterns and their effects on real estate values. The methodology utilizes a bi-level framework: a genetic algorithm optimizes OD demand estimation at the upper level, while a user equilibrium (UE) model simulates traffic flow at the lower level. This approach enables a nuanced exploration of how population growth impacts transportation conditions and housing price premiums. By analyzing the interplay between travel costs based on OD demand estimation and housing prices, we offer valuable insights for urban planners and policymakers. These findings are crucial for informed decision-making in rapidly developing areas, where understanding the relationship between mobility and real estate values is essential for sustainable urban development. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=demand%20estimation" title="demand estimation">demand estimation</a>, <a href="https://publications.waset.org/abstracts/search?q=genetic%20algorithm" title=" genetic algorithm"> genetic algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=housing%20price" title=" housing price"> housing price</a>, <a href="https://publications.waset.org/abstracts/search?q=transportation" title=" transportation"> transportation</a> </p> <a href="https://publications.waset.org/abstracts/191999/housing-prices-and-travel-costs-insights-from-origin-destination-demand-estimation-in-taiwans-science-parks" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/191999.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">21</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1770</span> A Study on Inference from Distance Variables in Hedonic Regression</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Yan%20Wang">Yan Wang</a>, <a href="https://publications.waset.org/abstracts/search?q=Yasushi%20Asami"> Yasushi Asami</a>, <a href="https://publications.waset.org/abstracts/search?q=Yukio%20Sadahiro"> Yukio Sadahiro</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In urban area, several landmarks may affect housing price and rents, hedonic analysis should employ distance variables corresponding to each landmarks. Unfortunately, the effects of distances to landmarks on housing prices are generally not consistent with the true price. These distance variables may cause magnitude error in regression, pointing a problem of spatial multicollinearity. In this paper, we provided some approaches for getting the samples with less bias and method on locating the specific sampling area to avoid the multicollinerity problem in two specific landmarks case. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=landmarks" title="landmarks">landmarks</a>, <a href="https://publications.waset.org/abstracts/search?q=hedonic%20regression" title=" hedonic regression"> hedonic regression</a>, <a href="https://publications.waset.org/abstracts/search?q=distance%20variables" title=" distance variables"> distance variables</a>, <a href="https://publications.waset.org/abstracts/search?q=collinearity" title=" collinearity"> collinearity</a>, <a href="https://publications.waset.org/abstracts/search?q=multicollinerity" title=" multicollinerity"> multicollinerity</a> </p> <a href="https://publications.waset.org/abstracts/17025/a-study-on-inference-from-distance-variables-in-hedonic-regression" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/17025.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">452</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1769</span> Importance of Road Infrastructure on the People Live in Afghanistan</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mursal%20Ibrahim%20Zada">Mursal Ibrahim Zada</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Since 2001, the new Government of Afghanistan has put the improvement of transportation in rural area as one of the key issues for the development of the country. Since then, about 17,000 km of rural roads were planned to be constructed in the entire country. This thesis will assess the impact of rural road improvement on the development of rural communities and housing facilities. Specifically, this study aims to show that the improved road has leads to an improvement in the community, which in turn has a positive effect on the lives of rural people. To obtain this goal, a questionnaire survey was conducted in March 2015 to the residents of four different districts of Kabul province, Afghanistan, where the road projects were constructed in recent years. The collected data was analyzed using on a regression analysis considering different factors such as land price, waiting time at the station, travel time to the city, number of employed family members and so on. Three models are developed to demonstrate the relationship between different factors before and after the improvement of rural transportation. The results showed a significant change positively in the value of land price and housing facilities, travel time to the city, waiting time at the station, number of employed family members, fare per trip to the city, and number of trips to the city per month after the pavement of the road. The results indicated that the improvement of transportation has a significant impact on the improvement of the community in different parts, especially on the price of land and housing facility and travel time to the city. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=accessibility" title="accessibility">accessibility</a>, <a href="https://publications.waset.org/abstracts/search?q=Afghanistan" title=" Afghanistan"> Afghanistan</a>, <a href="https://publications.waset.org/abstracts/search?q=housing%20facility" title=" housing facility"> housing facility</a>, <a href="https://publications.waset.org/abstracts/search?q=rural%20area" title=" rural area"> rural area</a>, <a href="https://publications.waset.org/abstracts/search?q=land%20price" title=" land price"> land price</a> </p> <a href="https://publications.waset.org/abstracts/48003/importance-of-road-infrastructure-on-the-people-live-in-afghanistan" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/48003.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">263</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1768</span> The Effect of Oil Price Uncertainty on Food Price in South Africa</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Goodness%20C.%20Aye">Goodness C. Aye</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper examines the effect of the volatility of oil prices on food price in South Africa using monthly data covering the period 2002:01 to 2014:09. Food price is measured by the South African consumer price index for food while oil price is proxied by the Brent crude oil. The study employs the GARCH-in-mean VAR model, which allows the investigation of the effect of a negative and positive shock in oil price volatility on food price. The model also allows the oil price uncertainty to be measured as the conditional standard deviation of a one-step-ahead forecast error of the change in oil price. The results show that oil price uncertainty has a positive and significant effect on food price in South Africa. The responses of food price to a positive and negative oil price shocks is asymmetric. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=oil%20price%20volatility" title="oil price volatility">oil price volatility</a>, <a href="https://publications.waset.org/abstracts/search?q=food%20price" title=" food price"> food price</a>, <a href="https://publications.waset.org/abstracts/search?q=bivariate" title=" bivariate"> bivariate</a>, <a href="https://publications.waset.org/abstracts/search?q=GARCH-in-mean%20VAR" title=" GARCH-in-mean VAR"> GARCH-in-mean VAR</a>, <a href="https://publications.waset.org/abstracts/search?q=asymmetric" title=" asymmetric"> asymmetric</a> </p> <a href="https://publications.waset.org/abstracts/28399/the-effect-of-oil-price-uncertainty-on-food-price-in-south-africa" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/28399.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">478</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1767</span> The Development of Private Housing Schemes to Address the Housing Problem: A Case Study of Islamabad</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Zafar%20Iqbal%20Zafar">Zafar Iqbal Zafar</a>, <a href="https://publications.waset.org/abstracts/search?q=Abdul%20Waheed"> Abdul Waheed</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The Capital Development Authority (CDA) Ordinance 1960 requires CDA to acquire land for the provision of housing in Islamabad. However, the pace of residential development was slow and the demand for housing was increasing rapidly. To resolve the growing housing problem, CDA involved the private sector in the development of housing schemes. Detailed bye-laws for regulation of private housing schemes were prepared and these bylaws were called “Modalities & Procedures”. This paper explains how the Modalities and Procedures of CDA have been successful in regulating the development of private housing schemes in Islamabad. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=housing%20schemes" title="housing schemes">housing schemes</a>, <a href="https://publications.waset.org/abstracts/search?q=master%20plan" title=" master plan"> master plan</a>, <a href="https://publications.waset.org/abstracts/search?q=development%20works" title=" development works"> development works</a>, <a href="https://publications.waset.org/abstracts/search?q=zoning%20regulations" title=" zoning regulations"> zoning regulations</a> </p> <a href="https://publications.waset.org/abstracts/145778/the-development-of-private-housing-schemes-to-address-the-housing-problem-a-case-study-of-islamabad" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/145778.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">201</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1766</span> Resale Housing Development Board Price Prediction Considering Covid-19 through Sentiment Analysis</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Srinaath%20Anbu%20Durai">Srinaath Anbu Durai</a>, <a href="https://publications.waset.org/abstracts/search?q=Wang%20Zhaoxia"> Wang Zhaoxia</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Twitter sentiment has been used as a predictor to predict price values or trends in both the stock market and housing market. The pioneering works in this stream of research drew upon works in behavioural economics to show that sentiment or emotions impact economic decisions. Latest works in this stream focus on the algorithm used as opposed to the data used. A literature review of works in this stream through the lens of data used shows that there is a paucity of work that considers the impact of sentiments caused due to an external factor on either the stock or the housing market. This is despite an abundance of works in behavioural economics that show that sentiment or emotions caused due to an external factor impact economic decisions. To address this gap, this research studies the impact of Twitter sentiment pertaining to the Covid-19 pandemic on resale Housing Development Board (HDB) apartment prices in Singapore. It leverages SNSCRAPE to collect tweets pertaining to Covid-19 for sentiment analysis, lexicon based tools VADER and TextBlob are used for sentiment analysis, Granger Causality is used to examine the relationship between Covid-19 cases and the sentiment score, and neural networks are leveraged as prediction models. Twitter sentiment pertaining to Covid-19 as a predictor of HDB price in Singapore is studied in comparison with the traditional predictors of housing prices i.e., the structural and neighbourhood characteristics. The results indicate that using Twitter sentiment pertaining to Covid19 leads to better prediction than using only the traditional predictors and performs better as a predictor compared to two of the traditional predictors. Hence, Twitter sentiment pertaining to an external factor should be considered as important as traditional predictors. This paper demonstrates the real world economic applications of sentiment analysis of Twitter data. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=sentiment%20analysis" title="sentiment analysis">sentiment analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=Covid-19" title=" Covid-19"> Covid-19</a>, <a href="https://publications.waset.org/abstracts/search?q=housing%20price%20prediction" title=" housing price prediction"> housing price prediction</a>, <a href="https://publications.waset.org/abstracts/search?q=tweets" title=" tweets"> tweets</a>, <a href="https://publications.waset.org/abstracts/search?q=social%20media" title=" social media"> social media</a>, <a href="https://publications.waset.org/abstracts/search?q=Singapore%20HDB" title=" Singapore HDB"> Singapore HDB</a>, <a href="https://publications.waset.org/abstracts/search?q=behavioral%20economics" title=" behavioral economics"> behavioral economics</a>, <a href="https://publications.waset.org/abstracts/search?q=neural%20networks" title=" neural networks"> neural networks</a> </p> <a href="https://publications.waset.org/abstracts/158988/resale-housing-development-board-price-prediction-considering-covid-19-through-sentiment-analysis" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/158988.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">117</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1765</span> The Aspect of Urban Inequality after Urban Redevelopment Projects</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sungik%20Kang">Sungik Kang</a>, <a href="https://publications.waset.org/abstracts/search?q=Ja-Hoon%20Koo"> Ja-Hoon Koo</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Globally, urban environments have become unequal, and cities have been segmented by income class. It is predicted that urban inequality has arisen by urban redevelopment and reconstruction projects that improve the urban environment and innovate cities. This study aims to analyze the occurrence and characteristics of urban inequality by using the housing price and sale price and demonstrating the correlation with the urban redevelopment project. This study measures 14 years of urban inequality index for 25 autonomous districts in Seoul and analyzes the correlation between urban inequality with urban redevelopment projects. As a conclusion of this study, first, the urban inequality index of Seoul has been continuously rising since 2015. Trends from 2006 to 2019 have been in U-curved shape in between 2015. In 2019, Seoul's urban inequality index was 0.420, a level similar to that of the 2007 financial crisis. Second, the correlation between urban redevelopment and urban inequality was not statistically significant. Therefore, we judged that urban redevelopment's scale or project structure has nothing with urban inequality. Third, while district designation of urban reconstruction temporarily alleviates urban inequality, the completion of the project increases urban inequality. When designating a district, urban inequality is likely to decrease due to decreased outdated housing transactions. However, the correlation with urban inequality increases as expensive houses has been placed after project completion. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=urban%20inequality" title="urban inequality">urban inequality</a>, <a href="https://publications.waset.org/abstracts/search?q=urban%20redevelopment%20projects" title=" urban redevelopment projects"> urban redevelopment projects</a>, <a href="https://publications.waset.org/abstracts/search?q=urban%20reconstruction%20projects" title=" urban reconstruction projects"> urban reconstruction projects</a>, <a href="https://publications.waset.org/abstracts/search?q=housing%20price%20inequality" title=" housing price inequality"> housing price inequality</a>, <a href="https://publications.waset.org/abstracts/search?q=panel%20analysis" title=" panel analysis"> panel analysis</a> </p> <a href="https://publications.waset.org/abstracts/141883/the-aspect-of-urban-inequality-after-urban-redevelopment-projects" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/141883.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">207</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1764</span> The Pricing-Out Phenomenon in the U.S. Housing Market</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Francesco%20Berald">Francesco Berald</a>, <a href="https://publications.waset.org/abstracts/search?q=Yunhui%20Zhao"> Yunhui Zhao</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The COVID-19 pandemic further extended the multi-year housing boom in advanced economies and emerging markets alike against massive monetary easing during the pandemic. In this paper, we analyze the pricing-out phenomenon in the U.S. residential housing market due to higher house prices associated with monetary easing. We first set up a stylized general equilibrium model and show that although monetary easing decreases the mortgage payment burden, it would raise house prices and lower housing affordability for first-time homebuyers (through the initial housing wealth channel and the liquidity constraint channel that increases repeat buyers’ housing demand), and increase housing wealth inequality between first-time and repeat homebuyers. We then use the U.S. household-level data to quantify the effect of the house price change on housing affordability relative to that of the interest rate change. We find evidence of the pricing-out effect for all homebuyers; moreover, we find that the pricing-out effect is stronger for first-time homebuyers than for repeat homebuyers. The paper highlights the importance of accounting for general equilibrium effects and distributional implications of monetary policy while assessing housing affordability. It also calls for complementing monetary easing with well-targeted policy measures that can boost housing affordability, particularly for first-time and lower-income households. Such measures are also needed during aggressive monetary tightening, given that the fall in house prices may be insufficient or too slow to fully offset the immediate adverse impact of higher rates on housing affordability. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=pricing-out" title="pricing-out">pricing-out</a>, <a href="https://publications.waset.org/abstracts/search?q=U.S.%20housing%20market" title=" U.S. housing market"> U.S. housing market</a>, <a href="https://publications.waset.org/abstracts/search?q=housing%20affordability" title=" housing affordability"> housing affordability</a>, <a href="https://publications.waset.org/abstracts/search?q=distributional%20effects" title=" distributional effects"> distributional effects</a>, <a href="https://publications.waset.org/abstracts/search?q=monetary%20policy" title=" monetary policy"> monetary policy</a> </p> <a href="https://publications.waset.org/abstracts/186642/the-pricing-out-phenomenon-in-the-us-housing-market" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/186642.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">36</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1763</span> A Study on Characteristics of Hedonic Price Models in Korea Based on Meta-Regression Analysis</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Minseo%20Jo">Minseo Jo</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The purpose of this paper is to examine the factors in the hedonic price models, that has significance impact in determining the price of apartments. There are many variables employed in the hedonic price models and their effectiveness vary differently according to the researchers and the regions they are analysing. In order to consider various conditions, the meta-regression analysis has been selected for the study. In this paper, four meta-independent variables, from the 65 hedonic price models to analysis. The factors that influence the prices of apartments, as well as including factors that influence the prices of apartments, regions, which are divided into two of the research performed, years of research performed, the coefficients of the functions employed. The covariance between the four meta-variables and p-value of the coefficients and the four meta-variables and number of data used in the 65 hedonic price models have been analyzed in this study. The six factors that are most important in deciding the prices of apartments are positioning of apartments, the noise of the apartments, points of the compass and views from the apartments, proximity to the public transportations, companies that have constructed the apartments, social environments (such as schools etc.). <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=hedonic%20price%20model" title="hedonic price model">hedonic price model</a>, <a href="https://publications.waset.org/abstracts/search?q=housing%20price" title=" housing price"> housing price</a>, <a href="https://publications.waset.org/abstracts/search?q=meta-regression%20analysis" title=" meta-regression analysis"> meta-regression analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=characteristics" title=" characteristics"> characteristics</a> </p> <a href="https://publications.waset.org/abstracts/17128/a-study-on-characteristics-of-hedonic-price-models-in-korea-based-on-meta-regression-analysis" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/17128.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">402</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1762</span> Measuring Housing Quality Using Geographic Information System (GIS)</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Silvija%20%C5%A0Iljeg">Silvija ŠIljeg</a>, <a href="https://publications.waset.org/abstracts/search?q=Ante%20%C5%A0Iljeg"> Ante ŠIljeg</a>, <a href="https://publications.waset.org/abstracts/search?q=Ivan%20Mari%C4%87"> Ivan Marić</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Measuring housing quality is being done on objective and subjective level using different indicators. During the research 5 urban and housing indicators formed according to 58 variables from different housing, domains were used. The aims of the research were to measure housing quality based on GIS approach and to detect critical points of housing in the example of Croatian coastal Town Zadar. The purposes of GIS in the research are to generate models of housing quality indexes by standardisation and aggregation of variables and to examine accuracy model of housing quality index. Analysis of accuracy has been done on the example of variable referring to educational objects availability. By defining weighted coefficients and using different GIS methods high, middle and low housing quality zones were determined. Obtained results can be of use to town planners, spatial planners and town authorities in the process of generating decisions, guidelines, and spatial interventions. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=housing%20quality" title="housing quality">housing quality</a>, <a href="https://publications.waset.org/abstracts/search?q=GIS" title=" GIS"> GIS</a>, <a href="https://publications.waset.org/abstracts/search?q=housing%20quality%20index" title=" housing quality index"> housing quality index</a>, <a href="https://publications.waset.org/abstracts/search?q=indicators" title=" indicators"> indicators</a>, <a href="https://publications.waset.org/abstracts/search?q=models%20of%20housing%20quality" title=" models of housing quality"> models of housing quality</a> </p> <a href="https://publications.waset.org/abstracts/53181/measuring-housing-quality-using-geographic-information-system-gis" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/53181.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">300</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1761</span> Rental Housing May Address Affordable Housing Deficiency in India</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Meha%20Singla">Meha Singla</a>, <a href="https://publications.waset.org/abstracts/search?q=Shankhadeep%20Chaudhuri"> Shankhadeep Chaudhuri</a>, <a href="https://publications.waset.org/abstracts/search?q=Yadunandan%20Batchu"> Yadunandan Batchu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Rental Housing is a more cost effective and flexible housing solution for the low income families than home-ownership. While India is undergoing a new industrial metamorphosis with multiple government initiatives that emphasise on the growth of manufacturing sector through policy frameworks and corridor development proposals, there is going to be a huge influx of low-income working population to the upcoming urban centres. As per stats, about 70 per cent of the housing demand at these centres fall into the affordable segment. And in the midst of this rapid urbanisation and huge immigration of young population, there is a lack of proper rental housing framework in the country. A large number of immigrants will be unable to support home-ownership thereby leading to proliferation of slums in urban centres. As a result, there is a dire need for immediate articulation of a comprehensive rental housing policy and affordable housing initiatives. In this paper, CommonFloor attempts to analyse successful rental housing case studies of the world followed by establishing a correlation between the gap in urban rental housing stock and the per capita income statistics to devise rental housing affordability specific to major Indian cities (Delhi, Mumbai, Bangalore, Chennai). Further, with the corroboration of market price trends, it will try to locate feasible micro-markets for immediate rental housing action. Final research findings will provide key data points thereby helping to design the approach for efficient utilisation of unsold residential inventory in the country in order to compensate the rental housing deficiency. This data set is believed to express viable model(s) of the rental housing approach for the government and private participants. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=housing%20prices" title="housing prices">housing prices</a>, <a href="https://publications.waset.org/abstracts/search?q=migration%20of%20population" title=" migration of population"> migration of population</a>, <a href="https://publications.waset.org/abstracts/search?q=real%20estate" title=" real estate"> real estate</a>, <a href="https://publications.waset.org/abstracts/search?q=rental%20housing" title=" rental housing"> rental housing</a>, <a href="https://publications.waset.org/abstracts/search?q=rental%20markets" title=" rental markets"> rental markets</a>, <a href="https://publications.waset.org/abstracts/search?q=residential%20property%20market" title=" residential property market"> residential property market</a>, <a href="https://publications.waset.org/abstracts/search?q=urbanisation" title=" urbanisation"> urbanisation</a> </p> <a href="https://publications.waset.org/abstracts/46414/rental-housing-may-address-affordable-housing-deficiency-in-india" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/46414.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">308</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1760</span> Influence Analysis of Macroeconomic Parameters on Real Estate Price Variation in Taipei, Taiwan</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Li%20Li">Li Li</a>, <a href="https://publications.waset.org/abstracts/search?q=Kai-Hsuan%20Chu"> Kai-Hsuan Chu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> It is well known that the real estate price depends on a lot of factors. Each house current value is dependent on the location, room number, transportation, living convenience, year and surrounding environments. Although, there are different experienced models for housing agent to estimate the price, it is a case by case study without overall dynamic variation investigation. However, many economic parameters may more or less influence the real estate price variation. Here, the influences of most macroeconomic parameters on real estate price are investigated individually based on least-square scheme and grey correlation strategy. Then those parameters are classified into leading indices, simultaneous indices and laggard indices. In addition, the leading time period is evaluated based on least square method. The important leading and simultaneous indices can be used to establish an artificial intelligent neural network model for real estate price variation prediction. The real estate price variation of Taipei, Taiwan during 2005 ~ 2017 are chosen for this research data analysis and validation. The results show that the proposed method has reasonable prediction function for real estate business reference. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=real%20estate%20price" title="real estate price">real estate price</a>, <a href="https://publications.waset.org/abstracts/search?q=least-square" title=" least-square"> least-square</a>, <a href="https://publications.waset.org/abstracts/search?q=grey%20correlation" title=" grey correlation"> grey correlation</a>, <a href="https://publications.waset.org/abstracts/search?q=macroeconomics" title=" macroeconomics"> macroeconomics</a> </p> <a href="https://publications.waset.org/abstracts/100459/influence-analysis-of-macroeconomic-parameters-on-real-estate-price-variation-in-taipei-taiwan" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/100459.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">198</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1759</span> Principles of Sustainable and Affordable Housing Policy for Afghan Refugees Returning to Afghanistan</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mohammad%20Saraj%20Sharifzai">Mohammad Saraj Sharifzai</a>, <a href="https://publications.waset.org/abstracts/search?q=Keisuke%20Kitagawa"> Keisuke Kitagawa</a>, <a href="https://publications.waset.org/abstracts/search?q=Mohammad%20Kamil%20Halimee"> Mohammad Kamil Halimee</a>, <a href="https://publications.waset.org/abstracts/search?q=Javid%20Habib"> Javid Habib</a>, <a href="https://publications.waset.org/abstracts/search?q=Daishi%20Sakaguchi"> Daishi Sakaguchi </a> </p> <p class="card-text"><strong>Abstract:</strong></p> The overall goal of this paper is to examine the suitability and potential of the policies addressing the sustainability and affordability of housing for returnees, and to determine the impact of this policy on housing delivery for Afghan refugees. Housing is a central component of the settlement experience of refugees. A positive housing situation can facilitate many aspects of integration. Unaffordable, and unsafe housing, however, can cause disruptions in the entire settlement process. This paper aims to identify a suite of built forms for housing that is both affordable and environmentally sustainable for Afghan refugees. The result was the development of a framework that enables the assessment of the overall performance of various types of housing development in all zones of the country. There is very little evidence that the present approach of housing provision to the vagaries of market forces has provided affordable housing, especially for Afghan refugees. There is a need to incorporate social housing into the policy to assist people who cannot afford to have their own houses. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Afghan%20refugees" title="Afghan refugees">Afghan refugees</a>, <a href="https://publications.waset.org/abstracts/search?q=housing%20policy" title=" housing policy"> housing policy</a>, <a href="https://publications.waset.org/abstracts/search?q=affordability" title=" affordability"> affordability</a>, <a href="https://publications.waset.org/abstracts/search?q=social%20housing" title=" social housing"> social housing</a>, <a href="https://publications.waset.org/abstracts/search?q=housing%20provision" title=" housing provision"> housing provision</a>, <a href="https://publications.waset.org/abstracts/search?q=environmental%20sustainability%20principles" title=" environmental sustainability principles"> environmental sustainability principles</a>, <a href="https://publications.waset.org/abstracts/search?q=resettlement" title=" resettlement"> resettlement</a> </p> <a href="https://publications.waset.org/abstracts/41538/principles-of-sustainable-and-affordable-housing-policy-for-afghan-refugees-returning-to-afghanistan" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/41538.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">567</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1758</span> The Impact of Biodiversity and Urban Ecosystem Services in Real Estate</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Carmen%20Cantuarias-Villessuzanne">Carmen Cantuarias-Villessuzanne</a>, <a href="https://publications.waset.org/abstracts/search?q=Jeffrey%20Blain"> Jeffrey Blain</a>, <a href="https://publications.waset.org/abstracts/search?q=Radmila%20Pineau"> Radmila Pineau</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Our research project aims at analyzing the sensitiveness of French households to urban biodiversity and urban ecosystem services (UES). Opinion surveys show that the French population is sensitive to biodiversity and ecosystem services loss, but the value given to these issues within urban fabric and real estate market lacks evidence. Using GIS data and economic evaluation, by hedonic price methods, weassess the isolated contribution of the explanatory variables of biodiversityand UES on the price of residential real estate. We analyze the variation of the valuefor three urban ecosystem services - flood control, proximity to green spaces, and refreshment - on the price of real estate whena property changes ownership. Our modeling and mapping focus on the price at theIRIS scale (statistical information unit) from 2014 to 2019. The main variables are internal characteristics of housing (area, kind of housing, heating), external characteristics(accessibility and infrastructure, economic, social, and physical environmentsuch as air pollution, noise), and biodiversity indicators and urban ecosystemservices for the Ile-de-France region. Moreover, we compare environmental values on the enhancement of greenspaces and their impact on residential choices. These studies are very useful for real estate developers because they enable them to promote green spaces, and municipalities to become more attractive. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=urban%20ecosystem%20services" title="urban ecosystem services">urban ecosystem services</a>, <a href="https://publications.waset.org/abstracts/search?q=sustainable%20real%20estate" title=" sustainable real estate"> sustainable real estate</a>, <a href="https://publications.waset.org/abstracts/search?q=urban%20biodiversity%20perception" title=" urban biodiversity perception"> urban biodiversity perception</a>, <a href="https://publications.waset.org/abstracts/search?q=hedonic%20price" title=" hedonic price"> hedonic price</a>, <a href="https://publications.waset.org/abstracts/search?q=environmental%20values" title=" environmental values"> environmental values</a> </p> <a href="https://publications.waset.org/abstracts/147354/the-impact-of-biodiversity-and-urban-ecosystem-services-in-real-estate" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/147354.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">132</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1757</span> The Influence of Housing Choice Vouchers on the Private Rental Market</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Randy%20D.%20Colon">Randy D. Colon</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Through a freedom of information request, data pertaining to Housing Choice Voucher (HCV) households has been obtained from the Chicago Housing Authority, including rent price and number of bedrooms per HCV household, community area, and zip code from 2013 to the first quarter of 2018. Similar data pertaining to the private rental market will be obtained through public records found through the United States Department of Housing and Urban Development. The datasets will be analyzed through statistical and mapping software to investigate the potential link between HCV households and distorted rent prices. Quantitative data will be supplemented by qualitative data to investigate the lived experience of Chicago residents. Qualitative data will be collected at community meetings in the Chicago Englewood neighborhood through participation in neighborhood meetings and informal interviews with residents and community leaders. The qualitative data will be used to gain insight on the lived experience of community leaders and residents of the Englewood neighborhood in relation to housing, the rental market, and HCV. While there is an abundance of quantitative data on this subject, this qualitative data is necessary to capture the lived experience of local residents effected by a changing rental market. This topic reflects concerns voiced by members of the Englewood community, and this study aims to keep the community relevant in its findings. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Chicago" title="Chicago">Chicago</a>, <a href="https://publications.waset.org/abstracts/search?q=housing" title=" housing"> housing</a>, <a href="https://publications.waset.org/abstracts/search?q=housing%20choice%20voucher%20program" title=" housing choice voucher program"> housing choice voucher program</a>, <a href="https://publications.waset.org/abstracts/search?q=housing%20subsidies" title=" housing subsidies"> housing subsidies</a>, <a href="https://publications.waset.org/abstracts/search?q=rental%20market" title=" rental market"> rental market</a> </p> <a href="https://publications.waset.org/abstracts/97346/the-influence-of-housing-choice-vouchers-on-the-private-rental-market" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/97346.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">118</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1756</span> Using Monte Carlo Model for Simulation of Rented Housing in Mashhad, Iran</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mohammad%20Rahim%20Rahnama">Mohammad Rahim Rahnama</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The study employs Monte Carlo method for simulation of rented housing in Mashhad second largest city in Iran. A total number of 334 rental residential units in Mashhad, including both apartments and houses (villa), were randomly selected from advertisements placed in Khorasan Newspapers during the months of July and August of 2015. In order to simulate the monthly rent price, the rent index was calculated through combining the mortgage and the rent price. In the next step, the relation between the variables of the floor area and that of the number of bedrooms for each unit, in both apartments and houses(villa), was calculated through multivariate regression using SPSS and was coded in XML. The initial model was called using simulation button in SPSS and was simulated using triangular and binominal algorithms. The findings revealed that the average simulated rental index was 548.5$ per month. Calculating the sensitivity of rental index to a number of bedrooms we found that firstly, 97% of units have three bedrooms, and secondly as the number of bedrooms increases from one to three, for the rent price of less than 200$, the percentage of units having one bedroom decreases from 10% to 0. Contrariwise, for units with the rent price of more than 571.4$, the percentage of bedrooms increases from 37% to 48%. In the light of these findings, it becomes clear that planning to build rental residential units, overseeing the rent prices, and granting subsidies to rental residential units, for apartments with two bedrooms, present a felicitous policy for regulating residential units in Mashhad. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mashhad" title="Mashhad">Mashhad</a>, <a href="https://publications.waset.org/abstracts/search?q=Monte%20Carlo" title=" Monte Carlo"> Monte Carlo</a>, <a href="https://publications.waset.org/abstracts/search?q=simulation" title=" simulation"> simulation</a>, <a href="https://publications.waset.org/abstracts/search?q=rent%20price" title=" rent price"> rent price</a>, <a href="https://publications.waset.org/abstracts/search?q=residential%20unit" title=" residential unit"> residential unit</a> </p> <a href="https://publications.waset.org/abstracts/62954/using-monte-carlo-model-for-simulation-of-rented-housing-in-mashhad-iran" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/62954.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">276</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1755</span> A Theory and Empirical Analysis on the Efficency of Chinese Electricity Pricing</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Jianlin%20Wang">Jianlin Wang</a>, <a href="https://publications.waset.org/abstracts/search?q=Jiajia%20Zhao"> Jiajia Zhao</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper applies the theory and empirical method to examine the relationship between electricity price and coal price, as well as electricity and industry output, for China during Jan 1999-Dec 2012. Our results indicate that there is no any causality between coal price and electricity price under other factors are controlled. However, we found a bi-directional causality between electricity consumption and industry output. Overall, the electricity price set by China’s NDRC is inefficient, which lead to the electricity supply shortage after 2004. It is time to reform electricity price system for China’s reformers. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=electricity%20price" title="electricity price">electricity price</a>, <a href="https://publications.waset.org/abstracts/search?q=coal%20price" title=" coal price"> coal price</a>, <a href="https://publications.waset.org/abstracts/search?q=power%20supply" title=" power supply"> power supply</a>, <a href="https://publications.waset.org/abstracts/search?q=China" title=" China"> China</a> </p> <a href="https://publications.waset.org/abstracts/9560/a-theory-and-empirical-analysis-on-the-efficency-of-chinese-electricity-pricing" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/9560.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">470</span> </span> </div> 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