Affect Housing Prices Research Articles

Does immigration affect residential real estate prices? Evidence from Australia

PurposeThis study aims to investigate the effect of immigration on housing prices in Australia both at the national and regional levels.Design/methodology/approachData for eight Australian states on a quarterly basis from 2004–2017 is used. To study the possible dynamic and endogenous relationship between housing prices and immigration, a panel vector autoregressive error correction model (PVECM) is adopted.FindingsAnalysis of the results indicates that in the short run immigration positively and significantly affects housing prices, whereas in the long run no significant relationship was observed between the two variables. From the regional breakdown and analysis, it is discerned that in some states there is a significant and positive effect of immigration on residential real estate prices in the long run. Causality analysis confirms that the direction of causation is from immigration to housing prices.Practical implicationsThe study illustrates that immigration and interstate migration, as well as high salaries, have been causing a rise in housing demand and subsequently housing prices. To monitor exceedingly high housing prices, local authorities should be controlling migration and salary levels.Originality/valuePast research studies had highlighted the importance of native interstate migration in explaining the nexus between immigration – housing prices. In this study, it has been empirically verified how immigration has been affecting the locational decisions of natives and subsequently how this has been affecting housing prices.

Purchase Motivation, Landscape Preference, and Housing Prices: Quantile Hedonic Analysis in Guangzhou, China

Abstract Urban landscapes are important factors that affect housing prices, and significant differences between landscape preferences of various homebuyers may be observed because of the different ...

What Drives House Price Cycles? International Experience and Policy Issues

The role of real estate during the global financial and economic crisis has prompted efforts to better incorporate housing and financial channels into macro models, improve housing models, develop macroprudential tools, and reform the financial system. This article provides an overview of major, recent contributions to the literature in relation to earlier research on what drives housing prices and how they affect economic activity. Particularly emphasized are studies, both theoretical and more strongly evidence-based, that connect housing markets with credit markets, house price expectations, financial stability, and the wider economy. The literature reveals much diversity in the international and regional behavior of house prices and the need to improve data tracking key housing supply and demand influences. Also reviewed are studies examining how monetary, macroprudential, and other policies affect house prices and access to housing. This survey is designed to help readers navigate the plethora of recent studies and understand the unsettled issues and avenues for further research. The findings should be of interest to policy makers concerned with financial stability as well as those dealing with the role of housing in the wider economy (JEL E32, E44, E63, G01, G21, R31).

Does tourism affect house prices in Turkey? Evidence from smooth structural break tests

PurposeThe purpose of this study is to examine the impact of tourism activities on house prices in Turkey from January 2010 to March 2020.Design/methodology/approachIt is used newly developed cointegration and causality tests based on Fourier approximation. These methods consider smooth structural breaks and do not need to recognize a priori date number and/or form of breaks.FindingsEmpirical findings show that international tourism activities have a substantial role in the escalation of house prices in Turkey. Findings also indicate a rise in industrial production enhances house prices while the mortgage lending rate exhibits a negative influence on house prices. Additionally, the evidence from Fourier causality tests reveals the unilateral causal linkage from tourism to house prices. This situation also shows that the tourism sector has a substantial role in stabilizing house prices’ rapid rise as a policy implication.Originality/valueAlthough a large number of papers have been analyzing the link between house prices and macroeconomic variables, this study eliminates the lack of papers examining the link between tourism and house prices in Turkey by using the new cointegration and causality methods that consider smooth structural changes.

How does school district adjustment affect housing prices: An empirical investigation from Hangzhou, China

A quality promotion of neighborhood primary schools no doubt elevates nearby housing price. But which houses benefit from the public policy is important to improve educational equity. Accurate identification of such capitalization effects will help policymakers optimize the allocation of scarce public goods. Previous studies on this issue have been biased due to endogeneity and overlooking the impacts of facility quality change. Based on the Hangzhou's school district adjustment in 2012, the current work contributes to housing price effects of policies and education quality changes, rather than a static educational facility. The difference-in-differences model with quantile regression is constructed to obtain a more precise and detailed estimation among the different sub-markets. Results show that the average price effect estimated by the difference-in-differences is up to nearly 800 yuan/m2, higher than cross-sectional estimation. Only housing with better schools after reassignment witness a price premium. Low-priced and small houses earn more than 1000 yuan/m2, whereas high-priced and large houses are not significantly affected. The results demonstrate that future policies should ensure the rights of low-income groups to attend high quality primary school and guard against the gentrification of low-priced houses.

Comparison of House Price Analysis in DKI Jakarta and Surabaya with Minitab Software 17.0

This article discusses the comparative analysis of factors affecting the selling price of houses between the city of DKI Jaka rta and the city of Surabaya. The study uses quantitative methods through Minitab 17.0 software. Analysis of research uses hedonic prices with data obtained from home sale sites. The findings of this study are factors that affect housing prices in Surabaya, the distance between the house and the town hall and the main road, electrical, namely the amount of electric power, land area, distance between the house and public facilities, and information on the quality of housing materials. While the factor determining the selling price of houses in DKI Jakarta is the distance between the house and the main road, land area, PDAM water and road type or the type of road location of the house

Support Vector Regression with Gaussian kernel for Housing Prices Prediction

The housing sector is one of the main sources of economic growth in both developing and developed countries. It is reported that nearly half of people buy or sell houses at an inappropriate price. Based on the public data set of Boston housing prices, this essay analyzed the factors affecting house prices and selected the five most important factors based on the decision tree with the ID3 algorithm. Then, this essay developed the support vector regression (SVR) with Gaussian kernel to predict housing prices. Experimental results showed that our method achieves superior accuracy and effectiveness compared with the SVR with linear kernel, KNN, and decision tree. To verify the applicability of our model, this research applied this model in Beijing housing price data, and it also achieved satisfactory fitting results.

A causality on factors affecting housing prices: case of Turkey

A causality on factors affecting housing prices: case of Turkey

Equilibrium foreign currency mortgages

This paper proposes a novel explanation for why foreign currency denominated loans to households have become so popular in some emerging economies. Our argument is based on what we call the debt limit channel, which arises when multi-period contracts are offered against collateral that is established on newly acquired assets. Whenever the difference between domestic and foreign interest rates is positive, this effect allows financially constrained agents to backload the real payments on their loans if they choose to borrow in foreign currency. We demonstrate in a structural macroeconomic framework that the debt limit channel is quantitatively important and can result in dollarization of debt despite realistic and correctly perceived exchange rate risk. Comparing this outcome to allocations under constrained-optimal policy reveals that much of the identified bias towards foreign currency is due to a pecuniary externality, i.e. borrowers' failure to internalize how their currency choice affects house prices.

Real estate development in the city of Athens during the financial crisis

PurposeThis study aims to determine how the prices of residential properties in the Greek real estate sector are affected by their structural characteristics and by the prevailing economic factors during recession.Design/methodology/approachBased on 13,835 valuation reports for the city of Athens, covering a period of 11 years (2006–2016), this study develops a series of econometric models, taking into account both structural characteristics of the property market and the macroeconomic relevant variables. Finally, the city of Athens is divided into sub-regions and the different effects of the structural factors in each area are investigated via spatial analysis confirming the validity of the baseline model.FindingsFindings show that the size, age, level, parking and storage space can explain the property price movements. Moreover, the authors find evidence that it is primarily house demand variables (e.g. the annual average wage, the unemployment rate, the user cost of capital, financing constraints and expectations about the future course of the house market) that affect house prices in a statistically significant manner and with the correct sign. Finally, using a difference-in-differences approach, this study finds that an increase in house demand (on account of net migration) led to higher house prices in smaller and older than in larger and younger apartments in areas with high concentration of immigrants.Originality/valueThis study uses a novel data set to help entities, individuals and policy-makers to understand how the recent economic and financial crisis has affected the real estate market in Athens.

THE 2008 ECONOMIC STIMULUS PLAN AND HOUSING PRICE: THE ROLE OF SOES

How does China’s 2008 economic stimulus plan affect housing price through the channel of state-owned enterprises (SOEs)? Utilizing a sample of 206 Chinese cities and a different-in-difference approach, we show that the housing prices in cities with a higher prevalence of SOEs, tend to grow disproportionately faster than that in cities with lower prevalence of SOEs after the shock of 2008 China’s stimulus plan. The heterogeneity tests show that the SOE channel plays a more important role in cities with more city investment bonds, less financial development and lower level of marketization. Our conclusion is robust across a battery of sensitivity tests.

Out‐of‐Town Home Buyers and City Welfare

ABSTRACTMany cities have attracted a flurry of out‐of‐town (OOT) home buyers. Such capital inflows affect house prices, rents, construction, labor income, wealth, and ultimately welfare. We develop an equilibrium model to quantify the welfare effects of OOT home buyers for the typical U.S. metropolitan area. When OOT investors buy 10% of the housing in the city center and 5% in the suburbs, welfare among residents falls by 0.61% in consumption‐equivalent units. House prices and rents rise substantially, resulting in welfare gains for owners and losses for renters. Policies that tax OOT buyers or mandate renting out vacant property mitigate welfare losses.

Drivers of Subregional Housing Markets in Poland

Purpose: The paper investigates how sustainable city development factors impact housing price levels in subregional cities, on basis of 14 thousand real transactions in three Polish cities in the years 2006–2014. Design/Methodology/Approach: The multiple regression analysis with hedonic approach was used. Findings: The three-equation model has proven that economic development factors affect housing price levels in subregional cities while social progress and environmental responsibility do not always explain the change in the housing prices. Additionally the analysis of data allowed to conclude that the smaller the local market is, the more it is responsive to changes in external conditions. Practical implications: The housing market in subregional cities is different to big cities, prices change slower and do not respond to changes in the macro-environment factors as quickly and strongly as in large cities. Moreover, the situation on the local housing markets depends largely on the scale of sustainable development of the city. The study outcomes can be readily used to help more accurately plan housing investments for real estate developers or planning authorities responsible for housing policy. Originality/ value: We indicated what types of sustainable development factors affect the level of housing prices in subregional cities.

Impact of land quota and land supply structure on China’s housing prices: Quasi-natural experiment based on land quota policy adjustment

From 2003 to 2019, housing prices in China jumped by 295%. Much of this growth can be attributed to the spatial and structural misallocation of land supply. Specifically, China’s government determines the urban land supply, using land quotas to allow for greater land supply in the country’s central and western regions, but less so in the eastern region. In addition, the government controls the land supply structure, whereby industrial lands take up a larger proportion than commercial and residential lands. This paper attempts to investigate how China’s land quota system and land supply structure impact the country’s housing prices. After setting up a theoretical framework, we construct a panel data set including land quota, land supply structure and housing prices for 282 prefecture-level cities from 2001 to 2016. We demonstrate that housing price growth in cities whose land quotas were lowered during the study period is about 10% higher than that in cities whose land quotas were raised, with the former being mostly big cities and coastal cities. We further find that land supply structure affects housing prices, whereby the lower the proportion of commercial and residential land supply, the higher the housing prices. We further find that land quotas and land supply structure have a mediating effect on housing prices through land prices.

The resilience and realignment of house prices in the era of Covid-19*

PurposeThe study aims to analyze the effects of the Covid-19 pandemic on house prices.Design/methodology/approachThe authors start by discussing the possibility that house price indexes may not fully incorporate the effects of the pandemic as of yet. Against the background of the pandemic, the authors then analyze economic and behavioral effects affecting house prices. The authors also discuss how the linkages between tourism and house prices have been affected. The authors further present evidence of an emerging shift in preferences from urban locations to more peripheral ones.FindingsThe authors report variance in the evolution of house prices across countries at the onset of the pandemic, with locations depending heavily on tourism showing slower price appreciation while appreciation has firmed in other places. The authors argue that the resilience of house prices is not only because of the low-interest rate environment and government efforts to support firms and households, but also behavioral factors. In some locations, the price of condominiums has declined relative to the price of detached houses. This could indicate that wealthier households are seeking more space and larger units as a result of the crisis. There is also evidence of a downward pressure on rents, leading to increased price–rent ratios in the USA.Originality/valueBy considering both economic and behavioral factors, this paper provides for a better understanding of the resilience and realignment of house prices at the onset of the Covid-19 pandemic.

How does urban renewal affect housing price? Evidence from Beijing shantytown renewal plan

ABSTRACT In this paper, we use the shantytown renewal project data in Beijing, China, to explain how the renewal type as restrictions has aheterogeneous effect on housing prices. Using the time-varying difference-in-differences approach, we found that refurbishment is ineffective and the interrupted renewal projects will have significantly negative expected effect. Only rebuilding can make positive impact on housing price both within and surrounding shantytowns.

A Time-Varying Hedonic Approach to quantifying the effects of loss aversion on house prices

Loss aversion is a widely-recognized cognitive bias that can affect house price determination. Existing empirical approaches to quantify its effects require hedonic methods to predict what prices would be in the absence of loss aversion. However, conventional methods for making this counterfactual prediction unrealistically preclude time variation in the hedonic values of housing attributes, thereby exacerbating specification error and reducing the accuracy of point estimates. We show how time-varying hedonic regression (TVHR) can overcome this deficiency by allowing hedonic values to change over time. Applying the method to a dataset of residential transactions from Auckland, New Zealand, that spans 2009 to 2018, we find that loss aversion significantly inflates transaction prices. However, by comparison, existing methods yield imprecise estimates of this premium that are implausibly large and sensitive to the sample period selected. Our findings suggest that THVR is an attractive alternative to conventional approaches to quantifying loss aversion.

Built environment, special economic zone, and housing prices in Shenzhen, China

Shenzhen's meteoric urban growth is unprecedented, and its housing prices position it among the world's top five most expensive cities. Commonly understood as a ‘miracle city,’ ‘instant city,’ and ‘model city’ orchestrated by the central state in modern experimental urban planning, the local context and the role of the SEZ are a neglected spatiality in housing studies focusing on Shenzhen. Drawing on open data (Lianjia.com), we examine Shenzhen's spatial patterns of residential apartment prices and their associated local attributes. Based on a hedonic model, our results affirm a dichotomous spatial structure shaped by the special economic zones' (SEZs') associated unbalanced distribution of both accessibility and public/private service amenities. Inside the original SEZ (INSEZ), cultural amenities, green space, shopping malls, and a central business district significantly affect housing prices. Outside the original SEZ (OUTSEZ), only proximity to metro stations positively affects housing prices. Urban redevelopment should concentrate more on collaborative redevelopment in urban villages and equity in private and public service provision to narrow the inequality between INSEZ and OUTSEZ.

Prediksi Harga Rumah Menggunakan Web Scrapping dan Machine Learning Dengan Algoritma Linear Regression

Tempat tinggal atau rumah merupakan salah satu dari banyaknya kebutuhan primer bagi manusia. Maka dari itu sangat penting untuk membuat perencanaan agar tiap keluarga dapat memiliki tempat tinggal pribadi. Dalam perencanaan tersebut dibutuhkan prediksi atau perkiraan harga di masa mendatang. Maka, tujuan penelitian ini bertujuan untuk membuat model prediksi harga rumah menggunakan metode machine learning adapun algoritmanya adalah linear regression. Dengan melakukan web scraping untuk mengumpulkan data, melalui beberapa website yang bergelut dibidang jual beli rumah. Adapun menurut developer rumah yang berhasil ditanyakan dilapangan terkait variabel yang mempengaruhi harga rumah diantaranya luas lahan, luas bangunan berdiri, banyaknya kamar tidur, banyaknya kamar mandi, dan ketersediaan tempat parkir mobil. Untuk mendapatkan nilai prediksi yang tinggi penelitian dilakukan secara berulang kali namun nilai prediksi terbesar dengan menggunakan 80% dataset untuk training dan 20% dataset digunakan untuk testing menghasilkan nilai output dengan tingkat akurasi dalam memprediksi sebesar 88%.

Factors affecting housing prices in Izmir, Turkey: a quantile regression approach

PurposeThe purpose of this paper is to investigate empirically the main factors that affect the house prices in Izmir, Turkey using the quantile regression and ordinary least square approaches.Design/methodology/approachSample data about the housing market for Izmir collected from the web pages of various real estate agencies during June 2018. Following this, the quantile regression method is used to estimate all possible effects of variables on each interested quantile to determine the factors that affect house prices to guide the potential consumers, house developers, city planners and the policymakers in Izmir, Turkey.FindingsResults show that the age of the house, central heating and parking have no significant effect on prices. The size of the house, the existence of an elevator, fire and security have a positive and significant effect on prices. The number of rooms has lower values for high-priced houses, while the floor, the number of balconies, air conditioning, proximity to schools have a higher value for high-priced houses. The number of toilets, the number of bathrooms and the distance to the hospital have a lower value on the high-priced housing. The value of the distance from the city center and the shopping center is almost uniform in all quantiles and lowers the value of the higher-priced houses. With the exception of the value of the houses in the 10th percentile in Balcova district, the value of the houses in Konak, Balcova and Narlidere is lower prices in Karsiyaka.Originality/valueThis is the first comprehensive research to determine the major factors that affect house prices in Izmir. The second contribution of this paper is that it includes all possible variables and accordingly derives adequate policy implications, which could be used both by the public housing authority and private housing constructing companies in designing and implementing effective housing policies.