scholarly journals International Real Estate Review

2015 ◽  
Vol 18 (4) ◽  
pp. 429-454
Author(s):  
Svein Olav Krakstad ◽  
Keyword(s):  
Real Estate ◽  
Housing Market ◽  
House Prices ◽  
Cost Price ◽  
Building Cost ◽  
Long Run ◽  
Cointegration Tests ◽  
Land Cost ◽  
Unique Dataset

This study analyzes the housing market by using four key ratios: price-rent, price-building cost, price-land cost and price-wage. We attempt to determine how they work together in order to explain the housing market. A unique dataset from Norway is used to investigate the long-run movements of the variables. In order to analyze these, we have created Norwegian hedonic indices for building and land costs. The cointegration tests confirm that there are long-term relationships between these ratios. The results show that these ratios affect future movement in house prices, rents, and building and land costs. Wages are weakly exogenous in the system and therefore drive house prices, rents, and building and land costs in the long run.

scholarly journals Financialization, real estate and COVID-19 in the UK

2020 ◽  
Author(s):  
Grace Blakeley
Keyword(s):  
Monetary Policy ◽  
Real Estate ◽  
Financial Markets ◽  
Housing Market ◽  
Negative Impact ◽  
House Prices ◽  
Wealth Inequality ◽  
The Uk

Abstract In the UK, financialization has transformed many areas of the economy, including the housing market. The deregulation of financial markets that took place from the 1980s onwards, combined with the privatization of social housing, has transformed UK real estate from an ordinary good, insulated to some extent from consumer and financial markets, into a valuable financial asset. The financialization of real estate has had a largely negative impact on the UK’s housing market, the wider economy and individual communities; wealth inequality, financial instability, gentrification and homelessness have all increased as the role of the financial sector in UK property has increased. The financial crisis only accelerated many of these trends as distressed real estate was bought up by investors in its wake, and as loose monetary policy pushed up house prices in the period after the crisis. The COVID-19 pandemic is only likely to exacerbate these issues; the UK is sleepwalking into a potential evictions crisis, and ongoing loose monetary policy is likely to prevent a significant and necessary correction in house prices over the long term.

Long-Term Equilibrium and Short-Term Dynamics between Metropolitan Housing Markets in China

2014 ◽  
Vol 905 ◽  
pp. 343-347
Author(s):  
Gao Lu Zou ◽  
K.W. Chau
Keyword(s):  
House Prices ◽  
Housing Markets ◽  
Small Sample ◽  
Short Term ◽  
Long Run ◽  
Regional Markets ◽  
Cointegration Tests ◽  
Causality Tests ◽  
Short Run

House prices across cities may form long-term relations. Geographic barriers could lead to lack of short-term dynamics. The paper aims to investigate the long-run equilibrium and/or short-run dynamics betweenmetropolitan house pricesin China. The study introduced two cointegration tests and various small-sample corrections. We conductedthe Toda-Yamamoto Granger causality tests. House prices betweencitiesin most regional markets did notshow long-term relations as well as short-term dynamics. Therefore, geographies andtransport costs between cities could reducethe centrifugal forces of city growth. Metropolitan housing markets are typically local.

A multifractal detrended fluctuation analysis of housing market: a role of financial crises in developed economies

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Syed Ali Raza ◽  
Nida Shah ◽  
Muhammad Tahir Suleman ◽  
Md Al Mamun
Keyword(s):  
Financial Crisis ◽  
Housing Market ◽  
Market Efficiency ◽  
House Price ◽  
Fluctuation Analysis ◽  
Content Type ◽  
Multifractal Detrended Fluctuation Analysis ◽  
Long Run ◽  
Before And After

Purpose This study aims to examine the house price fluctuations in G7 countries by using the multifractal detrended fluctuation analysis (MF-DFA) for the years 1970–2019. The study examined the market efficiency between the short-term and long-term in the full sample period, before and after the global financial crisis period. Design/methodology/approach This study uses the MF-DFA to analyze house price fluctuations. Findings The findings confirmed that the housing market series are multifractal. Furthermore, all the markets showed long-term persistence in both the short and long-term. The USA is identified as the most persistent house market in the short run and Japan in the long run. Moreover, in terms of efficiency, Canada is identified as the most efficient house market in the long run and the UK in the short run. Finally, the result of before and after the financial crisis period is consistent with the full sample result. Originality/value The contribution of this study in the literature is fourfold. This is the first study that has examined the house prices efficiency by using the MF-DFA technique given by Kantelhardt et al. (2002). Previously, the house market prices and efficiency has been investigated using generalized Hurst exponent (Liu et al., 2019), Quantile Regression Approach (Chae and Bera, 2019; Tiwari et al., 2019) but no study to the best of the knowledge has been done that has used the MF-DFA technique on the housing market. Second, this is the first study that has focused on the house markets of G7 countries. Third, this study explores the house market efficiency by dividing the market into two periods i.e. before and after the financial crisis. The study strives to investigate if the financial crisis determines the change in the degree of market efficiency or not. Finally, the study gives valuable insights to the investors that will help them in their investment decisions.

scholarly journals Untangling the nonlinear “knots” of UK’s housing prices

2019 ◽  
Vol 46 (5) ◽  
pp. 1083-1103
Author(s):  
Constantinos Alexiou ◽  
Sofoklis Vogiazas
Keyword(s):  
Housing Market ◽  
House Prices ◽  
Housing Prices ◽  
Positive Association ◽  
Research Area ◽  
Content Type ◽  
Nonlinear Ardl ◽  
Long Run ◽  
Short Run ◽  
The Uk

Purpose Housing prices in the UK offer an inspiring, yet a complex and under-explored research area. The purpose of this paper is to investigate the critical factors that affect UK’s housing prices. Design/methodology/approach The authors utilize the recently developed nonlinear ARDL approach of Shin et al. (2014) over the period 1969–2016. Findings The authors find that both the long-run and short-run impact of the price-to-rent (PTR) ratio and credit-to-GDP ratio on house prices (HP) is asymmetric whilst ambiguous results are established for mortgage rates, industrial production and equities. Apart from the novel framework of analysis, this study also establishes a positive association between HP and the PTR ratio which suggests a speculative behaviour and could imply the formation of a housing bubble. Originality/value It is the first study for the UK housing market that explores the underlying fundamental relationships by looking at nonlinearities hence, allowing HP to be tied by asymmetric relationships in the long as well as in the short run. Modelling the inherent nonlinearities enhances significantly the understanding of UK housing market which can prove useful for policymaking and forecasting purposes.

Germany will face long-term housing problems

2018 ◽  
Keyword(s):  
Young People ◽  
Real Estate ◽  
Housing Market ◽  
Social Housing ◽  
Large Scale ◽  
Content Type ◽  
Housing Investment ◽  
Will Force ◽  
German Cities

Subject Germany's housing dilemma. Significance Demographic changes and the shift from publicly to corporately owned housing have led to accommodation shortages and rising rents in West German cities. Despite the government's plans for large-scale social housing investment, these trends will have long-term implications for Germany's housing market. Impacts Over-priced real estate will force developers to invest overseas. Accommodation shortfalls and rising prices will result in mass mobilisation and protests of young people across Germany. Lack of social housing will increase rates of homelessness in German cities.

Are house prices in the Norwegian capital too high?

2015 ◽  
Vol 8 (2) ◽  
pp. 152-168 ◽  
Author(s):  
Svein Olav Krakstad ◽  
Are Oust
Keyword(s):  
House Prices ◽  
Construction Costs ◽  
Policy Makers ◽  
Correction Model ◽  
Content Type ◽  
Vector Error Correction ◽  
Vector Error ◽  
Long Run ◽  
Practical Implications

Purpose – This paper aims to investigate whether the homes in the Norwegian capital, Oslo, are overpriced. While house prices in many countries dropped after the financial crisis, those in Norway have continued to increase. Over the past 20 years, real house prices in Oslo have increased by around 7 per cent yearly. Design/methodology/approach – The authors use a vector error correction model to estimate the equilibrium between house prices, rents, construction costs and wages to examine whether house prices in Oslo are overpriced. Findings – Long-term relationships between house prices, rents, construction costs and wages are found and used to estimate equilibrium house prices in Oslo. The overpricing in Oslo compared to estimated equilibrium prices is around 35 per cent. Practical implications – Price–rent, price–construction cost and price–income ratios are often used, by practitioners to say something about over- or underpricing in the housing market. We test and find that house prices, rents and construction costs move toward constant ratios in the long run, while wages are found to be weakly exogenous in the system. Originality/value – Our estimate of overpricing gives households, investors and policy-makers a better understanding of the risk associated with owning dwellings.

scholarly journals Information Opportunities of Administrative Data on Residential Real Estate Transactions for Calculating the House Prices in Russia’s Housing Market

2021 ◽  
Vol 18 (6) ◽  
pp. 60-72
Author(s):  
A. B. Dukhon ◽  
O. I. Obraztsova ◽  
N. D. Epshtein
Keyword(s):  
Real Estate ◽  
Housing Market ◽  
House Prices ◽  
Information Source ◽  
Residential Property ◽  
National Accounts ◽  
System Of National Accounts ◽  
Registration Data ◽  
State Register ◽  
Property Price

Purpose of the study. Development, justification and testing of a methodology for improving statistical monitoring of average prices in the Russian housing market, based on the use of registration information of the Unified State Register of Real Estate (USRN) on transactions for the purchase of residential real estate, in accordance with international statistical standards for Residential Property Price statistics.Materials and methods. The theoretical basis of the study was the United Nations system of national accounts (version of 2008), including the European system of accounts as amended in 2010. The research methodological base was made up of official statistical sources: metadata and international statistics guidelines in the field of national accounting, Handbook on Residential Property Price Indices and related housing indicators, as well as methodological provisions and an album of Rosstat forms, and methodological materials of the administrative statistics of the Federal Service for State Registration, Cadastre and Cartography of the Russian Federation (Rosreestr). The depersonalized registration data on households’ market transactions of the Unified State Register of Property Rights and Transactions maintaining by Rosreestr were used as an information database of the research.Results. The main result of the study is the design and substantiation of a system of indicators for the construction of an integrated information source for Residential Property Price statistics, on the base on interdepartmental information interaction.Conclusion. The proposed system of indicators will provide a highquality database that could be used in order to construct constant quality House Prices for various types of homogeneous residential property in the housing market, complying with the concepts of international statistical standards.

scholarly journals The Time-Varying Nature of Reits

2018 ◽  
Vol 26 (1) ◽  
pp. 26-38
Author(s):  
Bing Zhu
Keyword(s):  
Real Estate ◽  
Time Varying ◽  
Property Market ◽  
True Nature ◽  
Optimal Weights ◽  
Long Run ◽  
Asset Portfolio ◽  
Asset Class ◽  
Informational Environment

Abstract This paper investigates changes in the nature of REITs by estimating the time-varying long-run relationship among securitized real estate, direct real estate, and stock performance. The informational environment of U.S. REITs has matured gradually since their introduction. As more information on this asset class has become available, the “true” nature of REITs has thus become more apparent. We find that the long-term elasticity of direct real estate total returns on REIT total returns has increased since 1980, and became significant at the beginning of the 1990s, while the elasticity of general equity total returns remained insignificant. During the 2000s, the underlying property market was able to predict nearly 30% of REIT variance in the long term. Consequently, ignoring changes in the “nature” of REITs may lead to an underestimation of the influence from the underlying property market, and misspecification of the optimal weights in the long-term inter-asset portfolio.

DAMPAK JANGKA PANJANG PERTUMBUHAN PENDUDUK TERHADAP INVESTASI AGREGAT PROVINSI DI INDONESIA

2019 ◽  
Vol 4 (1) ◽  
pp. 193-204
Author(s):  
Paulina Paulina
Keyword(s):  
Economic Growth ◽  
Population Growth ◽  
Secondary Data ◽  
Good Investment ◽  
Long Run ◽  
Cointegration Tests ◽  
Investment Rates ◽  
Growth Formation ◽  
Analysis Models

This study aims to determine the causality relationship between population growth of a country / region (PG)  which has an impact on the formation of investment (TINV) and economic growth (EG). This research was focused on 33 provinces in Indonesia on these 3 main variables. The data used are secondary data from 33 provinces, with observations between 2015-2017. The analysis models used are unit root and cointegration tests, VAR estimation and long-term VECM models, and panel data. The results of this study indicate: (1) there is no causal relationship between PG, TINV, and EG; (2) The cointegration test and the VAR model shows that there is a long-term relationship between endogenous and exogenous variables; (3) In the VECM model, there appears to be an influence between PG, EG on investment in the long run; (4) there are quite good investment provinces namely DKI Jakarta, and most of the eastern provinces of Indonesia experience positive investment rates. Keywords: population growth, formation of investmen, economic growth

Tourism, economic growth, energy consumption, and CO2 emissions in China

2020 ◽  
pp. 135481662091845 ◽  
Author(s):  
Jiekuan Zhang ◽  
Yan Zhang
Keyword(s):  
Economic Growth ◽  
Energy Consumption ◽  
Granger Causality ◽  
Policy Implications ◽  
Long Run ◽  
Cointegration Tests ◽  
Short Run ◽  
Vecm Granger Causality ◽  
Growth Energy

In this article, we for the first time applied the vector error correction model (VECM) Granger causality approach to investigate the short-run and long-run causal relationships among tourism, economic growth, energy consumption, and carbon dioxide (CO2) emissions for 30 Chinese provinces over the period 2000–2017. The results implied that the analyzed variables became stationary at their first differences. The panel cointegration tests indicated the presence of a long-term equilibrium relationship among these four analyzed variables. Results from the VECM Granger causality tests suggested that the bidirectional short-term causalities were statistically confirmed between gross domestic product (GDP) and tourism. Additionally, we found that some unidirectional short-run causalities existed running from energy consumption to other analyzed variables and bidirectional long-run causalities existed between CO2 emissions and GDP, CO2 emissions and tourism, and GDP and tourism. Moreover, we also found the existence of unidirectional long-term causalities running from energy consumption to other analyzed variables. Based on these findings, we highlighted some key policy implications to develop China’s sustainable tourism.

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