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Book part
Publication date: 8 April 2024

Daniel Pakši and Aleš Melecký

In this chapter, we aim to analyze the housing market development in Czechia, in particular the development of housing prices over the last 25 years. We quantify and discuss three…

Abstract

In this chapter, we aim to analyze the housing market development in Czechia, in particular the development of housing prices over the last 25 years. We quantify and discuss three distinct periods of excessive growth of regional Czech housing prices, identified through the formation of large positive GAPs – (1) before the entrance of Czechia to the European Union (EU), (2) at the onset of the Global Financial Crisis GFC, (3) in 2021. In all these periods, we identify significant differences among regions. We find that GAPs above 15% may be considered an indication of unsustainable long-term housing price growth that will be followed by a correction.

We then employ fixed effect panel data model to determine the drivers of flat and house prices in 14 Czech regions. Our results show that wage growth, migration and crime rate are significant factors affecting the prices of both flats and houses. Nevertheless, the impact of GDP per capita and job market indicators differs between flats and houses. Moreover, we find that higher migration into the region increases the difference between the prices of houses and flats, while increasing GDP per capita growth and crime rate mitigate this difference significantly.

Details

Modeling Economic Growth in Contemporary Czechia
Type: Book
ISBN: 978-1-83753-841-6

Keywords

Article
Publication date: 8 March 2022

Li Yang, Asadullah Khaskheli, Syed Ali Raza and Nida Shah

The purpose of this study is twofold: first is to examine the nonlinear relationship between tourism development and housing prices, and secondly, the role of economic growth in…

Abstract

Purpose

The purpose of this study is twofold: first is to examine the nonlinear relationship between tourism development and housing prices, and secondly, the role of economic growth in facilitating the materialization of tourism development and housing prices nexus in G7 countries.

Design/methodology/approach

The authors used the newly introduced econometric technique panel smooth transition regression (PSTR) model with two regimes on annual panel data from 1995 to 2018.

Findings

Results confirmed that the nexus between the tourism development and housing prices is nonlinear and regime dependent. Moreover, the results showed that the threshold level of economic growth above which tourism development increases the housing prices is 2.63%. The relationship above the threshold value is positive and growth enhancing, while below the threshold, tourism development has a negative effect on housing prices. The economic growth and housing prices also showed the U-shape relationship implying that at a certain level increase in economic growth decreases the housing prices but after a certain level increase in economic growth increases the housing prices.

Originality/value

This paper makes a unique contribution to the literature with reference to developed economies, being a pioneering attempt to investigate the nonlinear relationship between tourism development and housing prices and applying more rigorous and advanced econometric techniques like PSTR.

Details

International Journal of Housing Markets and Analysis, vol. 16 no. 1
Type: Research Article
ISSN: 1753-8270

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Article
Publication date: 17 October 2016

Antti Tapio Kurvinen and Tanja Tyvimaa

Even as many countries are facing changes in demographic profile and new types of senior housing developments are becoming more important, there is limited evidence for the…

Abstract

Purpose

Even as many countries are facing changes in demographic profile and new types of senior housing developments are becoming more important, there is limited evidence for the development impact of a senior house on surrounding residential property values. The purpose of this paper is to address the void in knowledge, investigating the impact of senior house developments on apartment values in Tampere, Finland.

Design/methodology/approach

To specify valuation effects of proximate senior house development projects, advanced research design combining propensity score matching procedure and hedonic pricing models is used.

Findings

The results show that a senior house development has a significant positive impact on proximate residential property values within a 500 metre radius. The impact is found to be the highest in underdeveloped neighbourhoods. Nevertheless, in neighbourhoods where property values and demand for housing units are higher and senior house developments fall into the criteria of infill development, a premium is lower, but still statistically significant and notable in magnitude.

Research limitations/implications

This paper studies apartment values only in Tampere, Finland, and it is important to notice that local regulations and market conditions may have a notable impact on the outcomes from senior house developments.

Originality/value

This study is the first of its kind to address a number of empirical issues and provide with statistically significant evidence for positive impacts from senior house developments – encouraging investors and developers to build senior houses.

Article
Publication date: 6 August 2021

Zhijiang Wu, Yongxiang Wang and Wei Liu

Economic fundamentals are recognized as determining factors for housing on the city level, but the relationship between housing price and land supply has been disputed. This study…

Abstract

Purpose

Economic fundamentals are recognized as determining factors for housing on the city level, but the relationship between housing price and land supply has been disputed. This study aims to examine what kind of impact housing prices have on land supply and whether there is heterogeneity in different regional spaces.

Design/methodology/approach

This study collects the relevant data of land supply and housing prices in Nanchang from 2010 to 2018, constructs a vector autoregression (VAR) model, including one external factor and four internal factors of land supply to explore the dynamic effects and spatial heterogeneity of land supply on housing prices through regression analysis. Also, the authors use the geographic detector to analyze the spatial heterogeneity of housing prices in Nanchang.

Findings

This study found that the interaction between land supply and housing price is extremely complex because of the significant differences in the study area; the variables of land supply have both positive and negative effects on housing price, and the actual effect varies with the region; and residential land and GDP are the two major factors leading to the spatial heterogeneity in housing price.

Research limitations/implications

The dynamic effects of land supply on housing price are mainly reflected in the center and edge of the city, the new development area, and the old town, which is consistent with the spatial pattern of the double core, three circles and five groups in Nanchang.

Originality/value

This is a novel work to analyze the dynamic effects of land supply on house prices, instead of a single amount of land supply or land prices. Furthermore, the authors also explore the spatial heterogeneity according to the regional characteristics, which is conducive to targeted policymaking.

Details

International Journal of Housing Markets and Analysis, vol. 15 no. 4
Type: Research Article
ISSN: 1753-8270

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Article
Publication date: 1 June 2015

Raden Aswin Rahadi, Sudarso Kaderi Wiryono, Deddy Priatmodjo Koesrindartoto and Indra Budiman Syamwil

– This study aims to address the factors or attributes that would influence the price of residential products in Jakarta Metropolitan Region.

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Abstract

Purpose

This study aims to address the factors or attributes that would influence the price of residential products in Jakarta Metropolitan Region.

Design/methodology/approach

In total, 202 respondents from all across Jakarta Metropolitan Region participated in the questionnaire for this study. Demographic questions are categorized into age, gender and preferences for real estate locations. The questionnaire was made based on the author’s previous studies. Of the total respondents, 127 were males and 75 were females with age ranging from 18 to 56 years old. For data analysis, the authors utilized factor analysis, Cronbach’ α test and analysis of correlation to reach the conclusion of this study.

Findings

The findings suggested that from the initial three factors groups, there are five new groups that emerge as influencing factors for housing prices. Cronbach’ α score were verified (α = 0.906). Correlation study result suggested that the initial three factors groups produce a significant correlation between each of them, except for the factor of “overall location” and “located near family.” After factor analysis, the research results show that there are two new additional groups of factors that emerge as influences to housing prices. There are significant scores of differences between gender and real estate location preference toward the groups of factors.

Research limitations/implications

This study shows how physical qualities, concept and location factors influence the housing price perception of their consumers. The result shows to be relatively reliable and valid.

Originality/value

The study is the first to analyze the relationship between the factors for preferences on residential products and housing price in Indonesia. This paper is also intended to be the first to pioneer the study on factors of preferences on residential products in Indonesia. The findings will be useful to develop pricing models for housing product in Indonesia.

Details

International Journal of Housing Markets and Analysis, vol. 8 no. 2
Type: Research Article
ISSN: 1753-8270

Keywords

Book part
Publication date: 26 August 2019

Kim Abildgren

Empirical studies on household-level inflation inequality have so far only focused on periods with positive inflation rates. However, the major concern on the policy agenda since…

Abstract

Empirical studies on household-level inflation inequality have so far only focused on periods with positive inflation rates. However, the major concern on the policy agenda since the most recent financial crisis has been deflation rather than inflation. This naturally raises the question regarding the effect of deflation on the distribution of real income when households spend their budget on different consumption bundles. This chapter compiles annual household-level inflation rates in Denmark from 1930 to 1935 based on microdata from the Expenditure and Saving Survey of 1931 and price data from the official Retail Price Index. The results indicate that lower-income households faced a larger decline in prices on their consumption of goods and services during the deflation years 1930–1932 than higher-income households did. The deflation thus contributed to narrowing the difference in real incomes between the top and bottom parts of the income distribution during the recession. In the years 1933–1935 with positive inflation rates, the lower-income households experienced higher inflation rates than higher-income households. Over the period 1930–1935 seen as a whole, the price development contributed slightly to reducing real income inequality. The low degree of medium-term persistence of differences in household-specific inflation rates is consistent with previous findings in various time periods from the 1960s to the 2000s without any persistent deflation events. The chapter at hand is the first empirical study of the direct distributional effects of price developments at the household level in a period with persistent deflation.

Article
Publication date: 28 July 2023

Vivek Agnihotri and Saikat Kumar Paul

This paper aims to understand the spatiotemporal influence of metro rail connectivity on housing prices in surrounding areas. The study assesses the average annual price shift for…

Abstract

Purpose

This paper aims to understand the spatiotemporal influence of metro rail connectivity on housing prices in surrounding areas. The study assesses the average annual price shift for apartments around metro stations in Delhi during the previous decade, specifically from 2010 to 2019. The authors examine the spatiotemporal extents to which housing prices are determined by the prominence of metro stations and spatial development around metro stations.

Design/methodology/approach

The authors perform the cross-tabulation analysis to calculate chi-square values to test the hypotheses concerning the responsiveness of the housing market in Delhi to the number of locational variables in the areas connected with the mass public transportation system.

Findings

The empirical findings verify the existence of a housing market overvaluation in Delhi around metro stations until 2013, which was eventually re-adjusted after 2014. The key findings of the study suggest the role of location variables concerning metro rails in the shooting up of the housing prices in the city. In addition, the research establishes the association of annual housing price shifts to the metro rails in the short-term, mid-term and long-term in conjunction with the distance from the metro station.

Originality/value

In the market, the prices are often overvalued by real estate agents due to better connectivity to the metro stations. The overvaluation eventually causes massive downfalls in housing markets and rollouts as a risk for the investors. However, the effect of mass transportation on housing prices is mixed in nature, limited to a certain extent only and not as influential as frequently portrayed by the market forces. This effect loses colour with time.

Details

International Journal of Housing Markets and Analysis, vol. 17 no. 1
Type: Research Article
ISSN: 1753-8270

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Open Access
Article
Publication date: 7 July 2020

Juho Valtiala

This study analyses agricultural land price dynamics in order to better understand price development and to improve forecast accuracy. Understanding the evolution of agricultural…

Abstract

Purpose

This study analyses agricultural land price dynamics in order to better understand price development and to improve forecast accuracy. Understanding the evolution of agricultural land prices is important when considering sound investment decisions.

Design/methodology/approach

This study applies threshold autoregression to model agricultural land prices. The data includes quarterly observations on Finnish agricultural land prices.

Findings

The study shows that Finnish agricultural land prices exhibit regime-switching behaviour when using past changes in prices as a threshold variable. The threshold autoregressive model not only fits the data better but also improves the accuracy of price forecasts compared to the linear autoregressive model.

Originality/value

The results show that a sharp fall in agricultural land prices temporarily changes the regular development of prices. This information significantly improves the accuracy of price predictions.

Details

Agricultural Finance Review, vol. 81 no. 2
Type: Research Article
ISSN: 0002-1466

Keywords

Article
Publication date: 3 January 2023

Chin Tiong Cheng and Gabriel Hoh Teck Ling

Increasing overhang of serviced apartments poses a serious concern to the national property market. This study aims to examine the impacts of macroeconomic determinants, namely…

Abstract

Purpose

Increasing overhang of serviced apartments poses a serious concern to the national property market. This study aims to examine the impacts of macroeconomic determinants, namely, gross domestic product (GDP), consumer confidence index (CF), existing stocks (ES), incoming supply (IS) and completed project (CP) on serviced apartment price changes.

Design/methodology/approach

To achieve more accurate, quality price changes, a serviced apartment price index (SAPI) was constructed through a self-developed hedonic price index model. This study has collected 1,567 transaction data in Kuala Lumpur, covering 2009Q1–2018Q4 for price index construction and data were analysed using the vector autoregressive model, the vector error correction model and the fully modified ordinary least squares (OLS) (FMOLS).

Findings

Results of the regression model show that only GDP, ES and IS were significantly associated with SAPI, with an R2 of 0.7, where both ES and IS have inverse relationships with SAPI. More precisely, it is predicted that the price of serviced apartments will be reduced by 0.56% and 0.21% for every 1% increase in ES and IS, respectively.

Practical implications

Therefore, government monitoring of serviced apartments’ future supply is crucial by enforcing land use-planning regulations via stricter development approval of serviced apartments to safeguard and achieve more stable property prices.

Originality/value

By adopting an innovative approach to estimating the response of price change to supply and demand in a situation where there is no price indicator for serviced apartments, the study addresses the knowledge gap, especially in terms of understanding what are the key determinants of, and to what extent they influence, the SAPI.

Details

International Journal of Housing Markets and Analysis, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1753-8270

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Article
Publication date: 20 November 2019

Daniel Hagemann and Monika Wohlmann

The global financial and economic crisis resulting from the US housing crisis has shown that house prices can have far-reaching consequences for the real economy. For…

Abstract

Purpose

The global financial and economic crisis resulting from the US housing crisis has shown that house prices can have far-reaching consequences for the real economy. For macroprudential supervision, it is, therefore, necessary to identify house price bubbles at an early stage to counteract speculative price developments and to ensure financial market stability. This paper aims to develop an early warning system to signal speculative price bubbles.

Design/methodology/approach

The results of explosivity tests are used to identify periods of excessive price increases in 18 industrialized countries. The early warning system is then based on a logit and an ordered logit regression, in which monetary, macroeconomic, regulatory, demographic and private factors are used as explanatory variables.

Findings

The empirical results show that monetary developments have the highest explanatory power for the existence of house price bubbles. Further, the study reveals currently emerging house price bubbles in Norway, Sweden and Switzerland.

Practical implications

The results implicate a new global housing boom, particularly in those countries that did not experience a major price correction during the global financial crisis.

Originality/value

The ordered logit model is an advanced approach that offers the advantage of being able to differentiate between different phases of a house price bubble, thereby allowing a multi-level assessment of the risk of speculative excesses in the housing market.

Details

Journal of European Real Estate Research , vol. 12 no. 3
Type: Research Article
ISSN: 1753-9269

Keywords

21 – 30 of over 134000