The Impact of Urban Land Reserve System on House Prices

2013 ◽  
Vol 438-439 ◽  
pp. 1816-1819
Author(s):  
Rui Jun Yan ◽  
He Fang Xu
Keyword(s):  
House Prices ◽  
House Price ◽  
Urban Land ◽  
System Reform ◽  
Land System ◽  
The Impact ◽  
Land Reserve ◽  
Reserve System ◽  
Real State ◽  
State Territory

In recent years of China, land reserve system has become a vital measure of urban land system reform, it also has been a hotspot of the reform for real state territory. Starting from the land reserve, this paper will research the changes of house prices after land reserve occurs, and reveal how the land reserve makes effect on house price.

scholarly journals Are House Prices Driven by Capital Flows? Evidence from Singapore

2016 ◽  
Vol 07 (01) ◽  
pp. 1650006 ◽  
Author(s):  
Hwee Kwan Chow ◽  
Taojun Xie
Keyword(s):  
Capital Flows ◽  
Price Index ◽  
House Prices ◽  
House Price ◽  
Capital Inflows ◽  
Residential Property ◽  
Foreign Direct Investments ◽  
Short Term ◽  
Property Price ◽  
The Impact

This paper investigates whether real house price appreciations can be attributed to the surge in real capital inflows into Singapore. We proxy capital flows by using the amount of Foreign Direct Investments (FDI) to real estate capturing the foreign purchases of property in Singapore which we deflate by the private residential property price index. Notwithstanding the absence of a cointegrating relationship, our results support the hypothesis that lagged short term fluctuations in capital inflows are positively associated with the growth rates of house prices over the last decade. We also provide evidence that macroprudential measures implemented by Singapore reduced the impact of capital inflows on house price appreciation by more than half, suggesting the effectiveness of such market cooling measures in weakening the credit growth channel.

The Internet reshapes China's economic geography: micromechanisms and macro effects

2020 ◽  
Vol 3 (2) ◽  
pp. 259-283
Author(s):  
Chen Yang ◽  
Tongliang An
Keyword(s):  
Economic Geography ◽  
House Prices ◽  
House Price ◽  
The Internet ◽  
Dispersion Force ◽  
Content Type ◽  
The Real Estate ◽  
Real Estate Sector ◽  
Spatial Panel Data ◽  
The Impact

PurposeBy observing facts of the “reversal of agglomeration” of Chinese enterprises during the period of rapid Internet development and using a new economic geography model combined with the data of the real estate sector, this paper deduces the influence of the “reshaping mechanisms” of the Internet on China's economic geography based on the “gravitation mechanism” of the Internet that affects the enterprises and the “amplification mechanism” of the Internet that amplifies the dispersion force of house prices.Design/methodology/approachIn the empirical aspect, the dynamic spatial panel data model is used to test the micromechanisms of the impact of the Internet on enterprises' choice of location and the instrumental variable method is used to verify the macro effects of the Internet in reshaping economic geography.FindingsIt is found that in the era of the network economy, the Internet has become a source of regional competitive advantage and is extremely attractive to enterprises. The rapidly rising house price has greatly increased the congestion cost and has become the force behind the dispersion of enterprises. China's infrastructure miracle has closed the access gap which gives full play to network externalities and promotes the movement of enterprises from areas with high house prices to areas with low house prices.Originality/valueThe Internet is amplifying the dispersion force of congestion costs manifested as house prices and is reshaping China's economic geography. This paper further proposes policy suggestions such as taking the Internet economy as the new momentum of China's economic development and implementing the strategy of regional coordinated development.

scholarly journals MODELLING THE IMPACT OF WIND FARMS ON HOUSE PRICES IN THE UK

2008 ◽  
Vol 12 (4) ◽  
pp. 251-269 ◽  
Author(s):  
Sally Sims ◽  
Peter Dent ◽  
G. Reza Oskrochi
Keyword(s):  
Wind Farm ◽  
Negative Impact ◽  
House Prices ◽  
Turbine Blades ◽  
House Price ◽  
Wind Farms ◽  
Causal Link ◽  
Hedonic Pricing ◽  
The Uk ◽  
The Impact

This paper discusses the findings from a UK study to determine the likely impact of a wind farm on house prices using a hedonic pricing model. The Government's commitment to wind power has resulted in a massive increase in the number of wind farms sited in the UK. This has led to concerns that their visual and aural presence could have a negative impact on proximate house prices. This paper presents an analysis of 201sales transactions from houses situated within half a mile of a 16 turbine wind farm in Cornwall, UK. Whilst no causal link was established between the presence of the wind farm and house price, there was some evidence to suggest that both noise and flicker from the turbine blades could blight certain property and that the view of countryside enjoyed by the occupier had some value which may be affected by a wind farm. Santrauka Šiame darbe aptariami JK atlikto tyrimo rezultatai, kuriuo, taikant hedonistinį kainų modelį, siekta nustatyti galimą vėjo jėgainių poveikį namų kainoms. Vyriausybės parama vėjo energijai paskatino naujo elemento, vėjo jėgainės, atsiradimą aplinkoje; susirūpinta, ar vėjo jėgainių vaizdas ir garsas galėtų neigiamai paveikti namų kainas. Šiame darbe nagrinėjamas 201 prekybinis sandoris, susijęs su namais, pusę mylios nutolusiais nuo Bears Down, Kornvalyje (JK), esančio 16 vėjo jėgainių ūkio. Nors priežastinis ryšys tarp vėjo jėgainių ir namų kainos nepastebėtas, yra įrodymų, kad jėgainės keliamas triukšmas ir menčių mirgėjimas kai kuriems nekilnojamojo turto objektams galėtų pakenkti ir kad gyventojui patikęs kaimo vaizdas gali tapti nebepatrauklus.

scholarly journals Estimating the Peace Dividend: The Impact of Violence on House Prices in Northern Ireland

2012 ◽  
Vol 102 (2) ◽  
pp. 810-833 ◽  
Author(s):  
Timothy Besley ◽  
Hannes Mueller
Keyword(s):  
Northern Ireland ◽  
Negative Correlation ◽  
House Prices ◽  
Markov Switching ◽  
House Price ◽  
Markov Switching Model ◽  
Switching Model ◽  
Peace Dividend ◽  
The Impact ◽  
Over Time

This article exploits data on the pattern of violence across regions and over time to estimate the impact of the peace process in Northern Ireland on house prices. After establishing a negative correlation between killings and house prices, we estimate the parameters of a Markov switching model with conflict and peace as latent states. We use the model to estimate the size of the peace dividend as captured in house price changes. (JEL D74, R23, R31)

LIBOR, base rate spreads and the UK housing market

2015 ◽  
Vol 8 (1) ◽  
pp. 118-134 ◽  
Author(s):  
Martin Hinch ◽  
Jim Berry ◽  
William McGreal ◽  
Terry Grissom
Keyword(s):  
Time Series ◽  
Interest Rates ◽  
House Prices ◽  
House Price ◽  
Base Rate ◽  
Percentage Change ◽  
Content Type ◽  
Change Models ◽  
The Uk ◽  
The Impact

Purpose – The purpose of this paper is to analyse how London Interbank Offered Rate Index (LIBOR) and the spread between LIBOR and the base rate of interest as set by the Bank of England (BoE) influences the variation in house prices in the UK. Design/methodology/approach – This paper uses monthly data over a long time series, since 1986, to investigate the relationships between house price and LIBOR. Data are drawn from several different sources to include housing, financial and macro-economic variables. The time series is sub-divided into a series of splines based on stages in the economic and property market cycle. Both value-based and percentage change models are developed. Findings – The results show that BoE base/LIBOR margin variable has a strong positive and significant effect on house price; however, the percentage change model infers a weaker and inverse relationship. The spline analysis re-emphasised the significance of the BoE base/LIBOR margin variable. Where variation between base rates and LIBOR is reduced, a significant positive effect can be observed in the average house price; however, where significant variation exists, the BoE base/LIBOR margin has little effect and LIBOR itself becomes a significant driver. Research limitations/implications – The results highlight that the predictive qualities of the BoE base/LIBOR margin, as the contribution of this margin to the explanation of house price, exceeds both the base rate and LIBOR variables individually. Also highlighted is the contribution of unemployment to the explanation of house price. In both the value and percentage change models, unemployment is shown as a negative and highly significant contributor. Originality/value – Previous papers have demonstrated the important linkage between house price and interest rates, the originality in this paper lies in examining the impact of LIBOR and the spreads between LIBOR and base rate as key variables influencing variation in UK house prices.

scholarly journals House prices and neighbourhood amenities: beyond the norm?

2018 ◽  
Vol 11 (2) ◽  
pp. 263-289 ◽  
Author(s):  
Michael James McCord ◽  
Peadar Thomas Davis ◽  
Paul Bidanset ◽  
William McCluskey ◽  
John McCord ◽  
...  
Keyword(s):  
Housing Market ◽  
House Prices ◽  
House Price ◽  
Ordinary Least Squares ◽  
Content Type ◽  
Conditional Quantiles ◽  
Price Distribution ◽  
Regression Techniques ◽  
High Level ◽  
The Impact

Purpose Understanding the key locational and neighbourhood determinants and their accessibility is a topic of great interest to policymakers, planners and property valuers. In Northern Ireland, the high level of market segregation means that it is problematic to understand the nature of the relationship between house prices and the accessibility to services and prominent neighbourhood landmarks and amenities. Therefore, this paper aims to quantify and measure the (dis)amenity effects on house pricing levels within particular geographic housing sub-markets. Design/methodology/approach Most hedonic models are estimated using regression techniques which produce one coefficient for the entirety of the pricing distribution, culminating in a single marginal implicit price. This paper uses a quantile regression (QR) approach that provides a “more complete” depiction of the marginal impacts for different quantiles of the price distribution using sales data obtained from 3,780 house sales transactions within the Belfast Housing market over 2014. Findings The findings emerging from this research demonstrate that housing and market characteristics are valued differently across the quantile values and that conditional quantiles are asymmetrical. Pertinently, the findings demonstrate that ordinary least squares (OLS) coefficient estimates have a tendency to over or under specify the marginal mean conditional pricing effects because of their inability to adequately capture and comprehend the complex spatial relationships which exist across the pricing distribution. Originality value Numerous studies have used OLS regression to measure the impact of key housing market externalities on house prices, providing a single estimate. This paper uses a QR approach to examine the impact of local amenities on house prices across the house price distribution.

Causal effects of immigration inflows on house prices in a traditionally non-destination country

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Woei Chyuan Wong ◽  
Jan-Jan Soon
Keyword(s):  
Fixed Effects ◽  
Positive Impact ◽  
House Prices ◽  
Housing Prices ◽  
House Price ◽  
Developed Countries ◽  
Annual Data ◽  
Content Type ◽  
Variable Approach ◽  
The Impact

Purpose The purpose of this study is to examine the causal impact of international immigration inflows on housing prices at the state level in Malaysia from 2007 to 2018. Design/methodology/approach Hedonic regressions using both fixed effects and first difference approaches are used to estimate the impact of immigration inflows on house prices in Malaysia. This study deals with potential endogeneity of immigrants’ choices of destination states in Malaysia by using a shift-share instrument variable approach. Specifically, historical shares of immigrants in a state are used to predict current immigrant inflows to a particular state. The predicted value of immigration flows is then inserted into the house price regression models in place of the actual immigration flows. Findings Using annual data for 14 states from 2007 to 2018, this study documents the positive impact of immigration inflows on house prices in Malaysia. The authors find that a 1% increase in immigration inflows is associated with an increase of 10.2% (first difference) and 13.4% (fixed effects) in house prices. The economic impact is larger in magnitude than that found in developed countries. Contrary to existing studies that find immigration inflows to be associated with native flight, the authors find support for the attraction effects hypothesis, where immigration inflow is positive and significantly related to net native flows. Research limitations/implications The effects of immigration inflows are economically significant, considering that the effects are 10 times larger than those documented in the USA. Policymakers in Malaysia ought to monitor house price trends in immigrant-popular states to ensure that natives are not priced out by new immigrants. Originality/value To the best of the authors’ knowledge, this is perhaps the first study to focus on the relationship between immigration inflows and house prices in Malaysia. Focusing on Malaysia has at least two originality aspects. First, Malaysia is relatively not an immigrant-popular destination. Second, Malaysia has a multiracial and heterogenous society among its natives. The findings, obtained within these two settings, would therefore provide a wider scope of result generalization, and natural experiment grounds for causal implications of our results.

Using photographs and metadata to estimate house prices in South Korea

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Changro Lee ◽  
Key-Ho Park
Keyword(s):  
Neural Network ◽  
South Korea ◽  
Visual Information ◽  
House Prices ◽  
House Price ◽  
Content Type ◽  
Real Estate Valuation ◽  
Valuation Process ◽  
Price Estimation ◽  
The Impact

PurposeMost prior attempts at real estate valuation have focused on the use of metadata such as size and property age, neglecting the fact that the building workmanship in the construction of a house is also a key factor for the estimation of house prices. Building workmanship, such as exterior walls and floor tiling correspond to the visual attributes of a house, and it is difficult to capture and evaluate such attributes efficiently through classical models like regression analysis. Deep learning approach is taken in the valuation process to utilize this visual information.Design/methodology/approachThe authors propose a two-input neural network comprising a multilayer perceptron and a convolutional neural network that can utilize both metadata and the visual information from images of the front view of the house.FindingsThe authors applied the two-input neural network to Guri City in Gyeonggi Province, South Korea, as a case study and found that the accuracy of house price estimations can be improved by employing image information along with metadata.Originality/valueFew studies considered the impact of the building workmanship in the valuation process. The authors revealed that it is useful to use both photographs and metadata for enhancing the accuracy of house price estimation.

Die Auswirkungen der Geldmenge und des Kreditvolumens auf die Immobilienpreise – Ein ARDL-Ansatz für Deutschland / Money, Credit and House Prices – An ARDL-Approach for Germany

2010 ◽  
Vol 230 (2) ◽  
Author(s):  
Ansgar Belke
Keyword(s):  
Structural Breaks ◽  
House Prices ◽  
German Economy ◽  
House Price ◽  
Money Growth ◽  
Federal States ◽  
Price Data ◽  
Ardl Approach ◽  
Starting Point ◽  
The Impact

SummaryThe current financial crisis is often said to be caused by excessive liquidity and distorted incentives in the US subprime real estate sector. Taking this as a starting point, this paper analyzes the relation between house prices and credit respectively money growth between 1992 and 2006 (West German price data) and from 1997 to 2006 (East German price data). We focus on the German economy which - due to the creation of excess capacities in the wake of reunification - did not experience a house price bubble in contrast to other euro area economies such as Ireland and Spain. Applying an Autoregressive Distributed Lag (ARDL) approach we test for cointegration among the relevant variables. After estimating the long-run coefficients, we derive the optimal specification of the corresponding error-correction models and estimate them. Our results suggest that both monetary and credit policy are responsible for house price development especially in Western Germany. We also check exhaustively for well-behaved estimated residuals and conduct some tests for structural breaks and robustness checks. For instance, we show that tax policies - specific depreciation possibilities in the new federal states - also have a significant impact on house prices but without dominating the impact of credit and money growth. Our results are also robust to the application of a more traditional cointegration testing procedure in the spirit of Johansen and Juselius.

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