Do demographic changes affect house prices?

2019 ◽  
Vol 85 (4) ◽  
pp. 305-320
Author(s):  
Kristine Gevorgyan
Keyword(s):  
House Prices ◽  
Housing Prices ◽  
House Price ◽  
Demographic Variables ◽  
Generation Model ◽  
Overlapping Generation ◽  
Lower House ◽  
Price Growth ◽  
Demographic Shifts ◽  
Using Data

AbstractThe paper tests the idea that major demographic shifts can affect housing prices. We first build an overlapping generation model and analytically solve for the equilibrium price of the asset. The model predicts that economies with a higher fraction of old people in the overall population have lower house prices. We empirically test this hypothesis using data on house prices and demographic variables from the Organization for Economic Co-operation and Development (OECD). We find that if population growth increases by one percentage point, house price growth increases by 1.4 percentage points.

scholarly journals The role and significance of planning in the determination of house prices in Australia: Recent policy debates

2021 ◽  
pp. 0308518X2198894
Author(s):  
Peter Phibbs ◽  
Nicole Gurran
Keyword(s):  
Land Use ◽  
Housing Market ◽  
Land Use Planning ◽  
House Prices ◽  
Housing Prices ◽  
House Price ◽  
Evidence Base ◽  
Urban Housing ◽  
Price Inflation ◽  
Depth Analysis

On the world stage, Australian cities have been punching above their weight in global indexes of housing prices, sparking heated debates about the causes of and remedies for, sustained house price inflation. This paper examines the evidence base underpinning such debates, and the policy claims made by key commentators and stakeholders. With reference to the wider context of Australia’s housing market over a 20 year period, as well as an in depth analysis of a research paper by Australia’s central Reserve Bank, we show how economic theories commonly position land use planning as a primary driver of new supply constraints but overlook other explanations for housing market behavior. In doing so, we offer an alternative understanding of urban housing markets and land use planning interventions as a basis for more effective policy intervention in Australian and other world cities.

scholarly journals Assessing the impacts of Airbnb listings on London house prices

2021 ◽  
pp. 239980832110018
Author(s):  
James Todd ◽  
Anwar Musah ◽  
James Cheshire
Keyword(s):  
Random Effects ◽  
Rapid Growth ◽  
House Prices ◽  
Housing Prices ◽  
House Price ◽  
Positive Association ◽  
Sharing Economy ◽  
Local Context ◽  
Fixed And Random Effects ◽  
The World

Over the course of the last decade, sharing economy platforms have experienced significant growth within cities around the world. Airbnb, which is one of the largest and best-known platforms, provides the focus for this paper and offers a service that allows users to rent properties or spare rooms to guests. Its rapid growth has led to a growing discourse around the consequences of Airbnb rentals within the local context. The research within this paper focuses on determining impact on local housing prices within the inner London boroughs by constructing a longitudinal panel dataset, on which a fixed and random effects regression was conducted. The results indicate that there is a significant and modest positive association between the frequency of Airbnb and the house price per square metre in these boroughs.

scholarly journals Liquidity, interest rates and house prices in the euro area: a DSGE analysis

2016 ◽  
Vol 9 (1) ◽  
pp. 4-25 ◽  
Author(s):  
Margarita Rubio ◽  
José A. Carrasco-Gallego
Keyword(s):  
Interest Rates ◽  
Monetary Union ◽  
Euro Area ◽  
House Prices ◽  
Housing Prices ◽  
House Price ◽  
Dsge Model ◽  
Content Type ◽  
The Core ◽  
Dynamic Stochastic

Purpose This study aims to build a two-country monetary union dynamic stochastic general equilibrium (DSGE) model with housing to assess how different shocks contributed to the increase in housing prices and credit in the European Economic and Monetary Union. One of the countries is calibrated to represent the core group in the euro area, while the other one corresponds to the periphery. Design/methodology/approach In this paper, the authors explore how a liquidity shock (or a decrease in the interest rate) affects house prices and the real economy through the asset price and the collateral channel. Then, they analyze how a house price shock in the periphery and a technology shock in the core countries are transmitted to both economies. Findings The authors find that a combination of an increase in liquidity in the euro area coming from the common monetary policy, together with asymmetric house price and technology shocks, contributed to an increase in house prices in the euro area and a stronger credit growth in the peripheral economies. Originality/value This paper represents the theoretical counterpart to empirical studies that show, through macroeconometric models, the interrelation between liquidity and other shocks with house prices. Using a DSGE model with housing, the authors disentangle the mechanisms behind these empirical findings.

International Real Estate Review

2009 ◽  
Vol 12 (3) ◽  
pp. 193-220
Author(s):  
Karol Jan Borowiecki ◽  
Keyword(s):  
Real Estate ◽  
Positive Impact ◽  
House Prices ◽  
House Price ◽  
Housing Price ◽  
Quality Improvements ◽  
Vector Autoregressive ◽  
Price Growth ◽  
Price Determinants ◽  
A Minor

This paper studies the Swiss housing price determinants. The Swiss housing economy is reproduced by employing a macro- series from the last seventeen years and constructing a vector-autoregressive model. Conditional on a comparatively broad set of fundamental determinants considered, i.e. wealth, banking, demographic and real estate specific variables, the following findings are made: 1) real house price growth and construction activity dynamics are most sensitive to changes in population and construction prices, whereas real GDP, in contrary to common empirical findings in other countries, turns out to have only a minor impact in the short-term, 2) exogenous house price shocks have no long-term impacts on housing supply and vice versa, and 3) despite the recent substantial price increases, worries of overvaluation are unfounded. Furthermore, based on a self-constructed quality index, evidence is provided for a positive impact of quality improvements in supplied dwellings on house prices.

scholarly journals Club convergence of house prices: Evidence from China’s ten key cities

2015 ◽  
Vol 29 (24) ◽  
pp. 1550181 ◽  
Author(s):  
Hao Meng ◽  
Wen-Jie Xie ◽  
Wei-Xing Zhou
Keyword(s):  
Housing Market ◽  
House Prices ◽  
House Price ◽  
Economic Recession ◽  
Housing Markets ◽  
Extensive Study ◽  
Ripple Effect ◽  
Chinese Stock Market ◽  
Price Growth ◽  
Chinese Housing Market

The latest global financial tsunami and its follow-up global economic recession has uncovered the crucial impact of housing markets on financial and economic systems. The Chinese stock market experienced a marked fall during the global financial tsunami and China’s economy has also slowed down by about 2%–3% when measured in GDP. Nevertheless, the housing markets in diverse Chinese cities seemed to continue the almost nonstop mania for more than 10 years. However, the structure and dynamics of the Chinese housing market are less studied. Here, we perform an extensive study of the Chinese housing market by analyzing 10 representative key cities based on both linear and nonlinear econophysical and econometric methods. We identify a common collective driving force which accounts for 96.5% of the house price growth, indicating very high systemic risk in the Chinese housing market. The 10 key cities can be categorized into clubs and the house prices of the cities in the same club exhibit an evident convergence. These findings from different methods are basically consistent with each other. The identified city clubs are also consistent with the conventional classification of city tiers. The house prices of the first-tier cities grow the fastest and those of the third- and fourth-tier cities rise the slowest, which illustrates the possible presence of a ripple effect in the diffusion of house prices among different cities.

scholarly journals A dynamic model for housing price spillovers with an evidence from the US and the UK markets

2018 ◽  
Vol 2 (1) ◽  
pp. 70-81 ◽  
Author(s):  
Alper Ozun ◽  
Hasan Murat Ertugrul ◽  
Yener Coskun
Keyword(s):  
New York ◽  
Real Estate ◽  
House Prices ◽  
Housing Prices ◽  
House Price ◽  
Housing Markets ◽  
Content Type ◽  
Real Estate Markets ◽  
Country Level ◽  
The Us

Purpose The purpose of this paper is to introduce an empirical model for house price spillovers between real estate markets. The model is presented by using data from the US-UK and London-New York housing markets over a period of 1975Q1-2016Q1 by employing both static and dynamic methodologies. Design/methodology/approach The research analyzes long-run static and dynamic spillover elasticity coefficients by employing three methods, namely, autoregressive distributed lag, the fully modified ordinary least square and dynamic ordinary least squares estimator under a Kalman filter approach. The empirical method also investigates dynamic correlation between the house prices by employing the dynamic control correlation method. Findings The paper shows how a dynamic spillover pricing analysis can be applied between real estate markets. On the empirical side, the results show that country-level causality in housing prices is running from the USA to UK, whereas city-level causality is running from London to New York. The model outcomes suggest that real estate portfolios involving US and UK assets require a dynamic risk management approach. Research limitations/implications One of the findings is that the dynamic conditional correlation between the US and the UK housing prices is broken during the crisis period. The paper does not discuss the reasons for that break, which requires further empirical tests by applying Markov switching regime shifts. The timing of the causality between the house prices is not empirically tested. It can be examined empirically by applying methods such as wavelets. Practical implications The authors observed a unidirectional causality from London to New York house prices, which is opposite to the aggregate country-level causality direction. This supports London’s specific power in the real estate markets. London has a leading role in the global urban economies residential housing markets and the behavior of its housing prices has a statistically significant causality impact on the house prices of New York City. Social implications The house price co-integration observed in this research at both country and city levels should be interpreted as a continuity of real estate and financial integration in practice. Originality/value The paper is the first research which applies a dynamic spillover analysis to examine the causality between housing prices in real estate markets. It also provides a long-term empirical evidence for a dynamic causal relationship for the global housing markets.

scholarly journals Homeownership Rate and Other House Price Determinants Impacts on New House Prices in Colombia

2020 ◽  
pp. 35-50
Author(s):  
Hector Botello-Peñaloza
Keyword(s):  
Real Estate ◽  
House Prices ◽  
Housing Prices ◽  
House Price ◽  
Real Estate Market ◽  
The Real Estate ◽  
Homeownership Rate ◽  
Colombian Government ◽  
Price Determinants ◽  
Price Instability

Homeownership remains a preferred form of tenancy in different parts of the world. The attractions of security, stability, investment potential and a sense of pride outweigh the fear of price instability. For this reason, the Colombian government has encouraged in recent years, various demand policies that have sought to promote the increase in the number of homeowners. However, these ideas could have a severe impact on prices in the real estate market. Therefore, this study seeks to examine the effect of homeownership rate on new house prices in an emerging country with low real estate ownership, credit restrictions and average per capita income. The study uses panel data model to examine the influence of housing tenancy and other variables on the variation of housing prices in Colombia. Data were obtained from various sources including the Central Bank of Colombia, Financial Superintendence of Colombia, and National Administrative Department of Statistics of Colombia. The results show that homeownership rates have a positive effect on the price of new homes, which supports the hypothesis of the research. The population growth of the cities is the factor that is most relevant when explaining the price variations.

scholarly journals House Price Convergence on the Primary and Secondary Markets: Evidence from Polish Provincial Capitals

2019 ◽  
Vol 27 (4) ◽  
pp. 62-73 ◽  
Author(s):  
Mateusz Tomal
Keyword(s):  
Driving Forces ◽  
House Prices ◽  
Housing Prices ◽  
House Price ◽  
Secondary Markets ◽  
Factors Affecting ◽  
Long Run ◽  
Convergence Clubs ◽  
Shape Pattern ◽  
Convergence Model

Abstract The aim of this study is to identify whether there is a common house price trend across provincial capitals in Poland. The log t regression is the main method of analysis. Additionally, traditional convergence tests based on the concepts of β- and σ-convergence are used. The obtained results indicate that the cities do not share a common price in the long-run. There are, however, convergence clubs on both primary and secondary markets. In each club, house prices across cities tend to converge to their own steady state. Moreover, research on the driving forces of convergence reports that factors affecting housing prices differ among the clubs. Therefore, policymakers should adjust housing policies in accordance with the characteristics of a given club. In turn, the σ-convergence model demonstrated a very interesting finding, namely, a U-shape pattern of convergence, both on the primary and secondary markets. This pattern is strictly correlated with the level of prices on the markets.

Housing Prices and Money Demand: Empirical Evidence in Selected MENA Countries

2019 ◽  
Vol 15 (1) ◽  
Author(s):  
Nadia Mbazia ◽  
Mouldi Djelassi
Keyword(s):  
Money Demand ◽  
House Prices ◽  
Housing Prices ◽  
House Price ◽  
Structural Features ◽  
Demand Model ◽  
Mena Countries ◽  
Long Run ◽  
Short Run ◽  
Dynamic Relationships

Abstract This paper examines the links between housing and money empirically in a money demand framework for a panel of five Middle East and North Africa (MENA) countries using quarterly data from 2007Q3 to 2014Q4 with the inclusion of house prices as a variable representing the developments in housing markets. We applied the Pool Mean Group Estimation technique to estimate the long-run and short-run dynamic relationships in money demand model. Empirical results provide the evidence that higher house prices lead to a rise in M2 demand in long-run and short-run estimations. This finding may explain the importance influence of the house price developments on monetary policy in MENA countries. The results confirm that the cross-country heterogeneity of money holdings is also connected with structural features of the housing market.

Asymmetric sensitivities of house prices to housing fundamentals: evidence from UK regions

2019 ◽  
Vol 12 (3) ◽  
pp. 442-455 ◽  
Author(s):  
Huthaifa Alqaralleh
Keyword(s):  
House Prices ◽  
Housing Prices ◽  
House Price ◽  
Housing Affordability ◽  
Star Model ◽  
Content Type ◽  
Macroeconomic Variables ◽  
North West ◽  
Country Level ◽  
The North

Purpose This paper aims to examine asymmetries in the house price cycle and to understand the dynamic of housing prices, incorporating macroeconomic variables at regional and country level, namely, housing affordability, the unemployment rate, mortgage rate and inflation rate. Design/methodology/approach To highlight significant differences in the asymmetric patterns of house prices between regions, the STAR model is adopted. Findings The authors highlight significant differences in the asymmetric patterns of house prices between regions, in which some areas showed asymmetric response over the housing cycle; here the LSTAR model outperforms other models. In contrast, some regions (the South West and the North West) showed symmetric properties in the tails of the cycle; therefore, the ESTAR model was adopted in their case. Practical implications Being limited to a few fundamentals, this study opens an avenue for further research to investigate this dynamic using in addition such demand-supply factors as land supply, construction cost and loans made for housing. These findings can also be used to examine whether other models such as ARIMA, exponential smoothing or artificial neural networks can more accurately forecast housing prices. Originality/value The present paper aims to highlight housing affordability as a cause of asymmetric behaviour in house prices. Put differently, the authors seek to understand the dynamics of housing prices with other fundamentals incorporating macroeconomic variables in regions and country level data as a means of achieving a more concise result.

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