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

2020 ◽  
Vol 3 (2) ◽  
pp. 259-283
Author(s):  
Chen Yang ◽  
Tongliang An

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.

2015 ◽  
Vol 8 (1) ◽  
pp. 118-134 ◽  
Author(s):  
Martin Hinch ◽  
Jim Berry ◽  
William McGreal ◽  
Terry Grissom

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.


2018 ◽  
Vol 11 (2) ◽  
pp. 263-289 ◽  
Author(s):  
Michael James McCord ◽  
Peadar Thomas Davis ◽  
Paul Bidanset ◽  
William McCluskey ◽  
John McCord ◽  
...  

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.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Woei Chyuan Wong ◽  
Jan-Jan Soon

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.


2019 ◽  
Vol 38 (4) ◽  
pp. 271-290
Author(s):  
Patrick Lecomte

Purpose As smart technologies become an integral part of real estate in smart cities, the purpose of this paper is to explore the impact of ubiquitous computing on space users in smart real estate. Design/methodology/approach The analysis builds on two fields of knowledge rarely referenced in real estate studies: computer sciences and social sciences. The paper starts by analysing the idiosyncrasies of a new type of space user in smart real estate, known as the Cyber-dasein in reference to Heidegger’s phenomenology. The Cyber-dasein serves as an archetypical space user in smart environments. Findings The paper introduces digital-time as a new realm of real estate, and discusses the use of “experienced utility” in hedonic pricing models of smart real estate. It concludes by advocating a multidisciplinary collaborative approach for future research on real estate in smart environments. Practical implications There is a need for the real estate sector to decide on a metric for the new digital dimension of real estate owing to the implementation of smart technologies in the built environment. Originality/value This is the first research paper on this important topic. It is totally original and new.


2019 ◽  
Vol 37 (5) ◽  
pp. 455-469
Author(s):  
Tanu Aggarwal ◽  
Priya Solomon

Purpose The purpose of this paper is to examine the impact of residential and commercial loans on total real estate sector loans by using partial least square–structured equation modelling (PL–SEM) method. The residential loans as a mediator have been used to know the mediation effect between commercial and total real estate loans of banks in India. The residential loans as a mediator govern the relationship between commercial loans and total real estate loans in India. Real estate sector development is a lucrative opportunity for India. The real estate sector plays a major role in shaping economic conditions of the individuals, firms and family. Design/methodology/approach The research is descriptive in nature. The study on residential loans, commercial loans and total real estate loans has been taken into consideration, and on the other hand the measurement and structural model have been employed to the study the impact of residential loans and commercial loans on total real estate loans in India by using PL–SEM. The residential loans as a mediator have been taken to study the mediation effect of the relationship between commercial loans and total real estate loans in India. Findings The outcome of the structural model that is bootstrapping technique shows that there is an impact of residential and commercial loans by public and private sector banks on total real estate sector development in India. The residential loans show the full mediation effect between commercial loans and total real estate loans as the value of variation accounted for (VAF) is more than 1.93 which shows residential loans govern the nature of variable between commercial loans and total real estate loans. Practical implications The public and private sector banks are contributing to the real estate sector development in India which increases the economic growth of the country. The mediation analysis shows that residential loans are an important aspect between commercial and total real estate loans in India as the demand for residential housing is more in India. The increasing role of banks in the real estate sector strengthens the financial capability in the real estate sector market, and the property buyers will able to purchase more property which leads to increasing demand for real estate sector. Originality/value The research paper is original, and PL–SEM has been used to find the results.


2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Changro Lee ◽  
Key-Ho Park

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.


2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Matthew Allen-Coghlan ◽  
Kieran Michael McQuinn

Purpose This paper aims to examine the implications for the Irish housing market of the economic slowdown due to the Covid-19 virus. Design/methodology/approach In this paper, an inverted demand function for housing is augmented to include a residential market activity variable and estimate the impact on house prices of the decline in economic activity due to the virus-related measures. The likely future path of house prices based on two different recovery scenarios is also examined. Under both scenarios house prices are forecast to decline in the near term. Findings The scenario analysis presented here indicates that Irish house prices are set to fall over the next 18 months as a result of the Covid-19 downturn. This contraction in prices is due to the decline in household disposable income and the sharp fall-off in mortgage market activity, which will inevitably result from the administrative closedown implemented by the Irish authorities. Originality/value As such the approach builds on several studies which have examined both house price movements in general and the relationship between house prices and mortgage credit availability. The paper also draws on the latest analysis of the implications for the Irish economy of Covid-19 and the related administrative closure methods introduced by the public authorities.


2019 ◽  
Vol 37 (5) ◽  
pp. 610-626 ◽  
Author(s):  
Colin Jones

Purpose The purpose of this paper is to consider the role of political risk in real estate and to specifically examine the implications in Scotland of continuing uncertainty caused by political events. Design/methodology/approach The primary research links the political timeline around the Scottish independence referendum in 2014 to time series of a combination of individual investment transactions, measures of sentiment from investment agents and yields. The analysis distinguishes between UK and overseas investors. Findings The political risk over six years ebbed and flowed with the changing probability of constitutional change but ultimately it has been a cumulative dampener on investment in Scotland. An element of the political risk can be deemed to be specific risk linked to UK institutional fund mandates that stems from concerns about possible forced sales with independence. In addition political risk is in the eye of the beholder with overseas investors in Scotland unfazed by the prospects of independence. Practical implications The short-term impact on investment of the Scottish “neverendum” is very similar to that for independence. The consequences are depressed investment and development that seem set to continue at least until the constitutional hiatus begins to be resolved. Originality/value This is the first study to explicitly examine the impact of political uncertainty on the real estate sector.


2016 ◽  
Vol 9 (4) ◽  
pp. 627-647 ◽  
Author(s):  
David McIlhatton ◽  
William McGreal ◽  
Paloma Taltavul de la Paz ◽  
Alastair Adair

Purpose There is a lack of understanding in the literature on the spatial relationships between crime and house price. This paper aims to test the impact of spatial effects in the housing market, how these are related to the incidence of crime and whether effects vary by the type of crime. Design/methodology/approach The analysis initially explores univariate and bivariate spatial patterns in crime and house price data for the Belfast Metropolitan Area using Moran’s I and Local Indicator Spatial Association (LISA) models, and secondly uses spatial autoregression models to estimate the role of crime on house prices. A spatially weighted two-stage least-squares model is specified to analyse the joint impact of crime variables. The analysis is cross sectional, based on a panel of data. Findings The paper illustrates that the pricing impact of crime is complex and varies by type of crime, property type and location. It is shown that burglary and theft are associated with higher-income neighbourhoods, whereas violence against persons, criminal damage and drugs offences are mainly associated with lower-priced neighbourhoods. Spatial error effects are reduced in models based on specific crime variables. Originality/value The originality of this paper is the application of spatial analysis in the study of the impact of crime upon house prices. Criticisms of hedonic price models are based on unexplained error effects; the significance of this paper is the reduction of spatial error effects achievable through the analysis of crime data.


2020 ◽  
Vol 13 (1) ◽  
pp. 5-16
Author(s):  
John V. Duca

Purpose The purpose of this paper is to provide perspective on whether and why global metro house prices have become more synchronized, and perspective on the limited implications of this for investing in international real estate. Design/methodology/approach This paper reviews main findings from the literature on house price determination, reviews the emerging literature on global synchronization, and provides graphs to illustrate main points and trends. Findings House prices have become somewhat more synchronized likely reflecting greater correlation in long-term interest rates and macroeconomic cycles related to trends in globalization and international portfolio diversification. Nevertheless, this trend has not been continuous, reflecting that house prices depend on other fundamentals, which are not uniform across areas. Theory and evidence indicate that the more common are fundamentals, the more synchronized are house price cycles and the more substitution effects may matter. Also, real estate markets that are open to immigration and foreign investment have become more sensitive to shifts in the international demand for property by migrants or investors. Research limitations/implications Changes in international house price synchronization stem from variation in two categories of key drivers of house prices. The first are traditional supply and demand fundamentals. The second include international capital flows and immigration. Both sets of factors are sensitive to the economic environment and public policy. Increased synchronization of business cycles, the Euro currency union, and more common monetary policy strategies and tactics have fostered greater correlation of real interest rates across countries, which tend to increase house price synchronization. These effects can be amplified by the tendency for property owners to use extrapolative expectations of future house prices. Practical implications Shifts in prospective returns and the synchronization of international property returns not only on arbitrage of general property price differentials but also on underlying factors driving those differentials. Investors need to be mindful of the risks that metro prices sometimes reflect bubble-builder dynamics that can give rise to over-shooting of house prices. Observing simple correlations and changes in those correlations does not do away with the need for careful analysis of property investment, and if anything, warrant analysis of both how and why one may observe changes in the extent to which international house prices is synchronized. Social implications Despite the rise of globalization and of new technologies, the author has seen substantial divergences in house prices emerge across gateway cities and metros in less vibrant areas within countries. These reflect not only the impact of stronger income and population in more tech, educated and global oriented cities but also changes in the demand for amenities toward more culturally appealing cities, often – but not exclusively in – warmer or coastal areas where the supply elasticity of housing is often limited. Further complicating investment decisions are potential shifts in housing or immigration policy that can notably affect the demand for housing. Originality/value The paper provides practical perspective on why different groups of international cities have seen their house prices become more sychronized. Nevertheless, increased synchronization has occurred within an elite set of major cities, but in an environment house prices have diverged across gateway cities and metros in less vibrant areas within countries. The paper helps investors make sense of some recent patterns and recent prospects for investing in international real estate.


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