New housing supply and price reactions: evidence from Spanish markets

2014 ◽  
Vol 7 (1) ◽  
pp. 4-28 ◽  
Author(s):  
Paloma Taltavull de la Paz
Keyword(s):  
Housing Market ◽  
Explanatory Power ◽  
Housing Prices ◽  
Model Parameters ◽  
Credit Crunch ◽  
Housing Supply ◽  
Recursive Procedure ◽  
Content Type ◽  
Spanish Regions ◽  
The Impact

Purpose – The paper develops a housing model equation for Spain and selected regions to estimate new supply elasticity. The aim of the paper is to assess the role of housing supply on price evolution and explain the fall in housing starts since the start of the credit crunch. Design/methodology/approach – The paper uses a pooled EGLS specification controlling for the presence of cross-section heteroskedasticity. Fixed effect estimators are calculated to capture regional heterogeneity. The model uses secondary data (quarterly) for 17 Spanish regions over the period 1990-2012. A recursive procedure is applied to estimate model parameters starting with a baseline model (1990-1999) and successively adding one-year time information. Elasticities, as well as explanatory power from models, are reported and jointly analyzed. Elasticity is interpreted as the extent to which market mechanisms drive developer responses. Findings – Elasticities of new supply are shown to be very stable during all periods but characterized by differences in response at a regional level. Elasticity ranges from 0.8 to 1.3 across regions. The model reports a non-market-oriented mechanism that guides building decisions. The credit crunch and debt crisis have had a double negative effect capturing the cumulative effect of exogenous shocks. Research limitations/implications – Elastic responses restrained the effects of over-pricing in the period of strong demand pressures in the early 2000s. Changes in elasticity parameters over time suggest that long-term elasticity in housing supply depends on the specific region analyzed. The results show that the credit crunch shock had varying degrees of severity in Spanish regions, dramatically reducing house-building because of the high sensitivity to changes in prices. Practical implications – Estimated elasticity may be used to forecast responses to changes in housing prices. The results add to the understanding of the equilibrium mechanism in the housing market across regions. Originality/value – This is the first article that analyses housing supply, calculates supply elasticities and measures the impact of the credit crunch on the housing market from the supply side in Spain. The paper adds evidence to the debate concerning the equilibrium mechanism in the housing market.

scholarly journals Housing prices in peninsular Malaysia: supported by income, foreign inflow or speculation?

2019 ◽  
Vol 12 (3) ◽  
pp. 424-441 ◽  
Author(s):  
Wang Li Wong ◽  
Chin Lee ◽  
Seow Shin Koong
Keyword(s):  
Housing Market ◽  
Low Income ◽  
House Prices ◽  
Correction Term ◽  
Housing Prices ◽  
House Price ◽  
Peninsular Malaysia ◽  
Financial Asset ◽  
Content Type ◽  
The Impact

Purpose This paper is motivated by a concern about the ability of the average Malaysian income to catch up with the rapidly increasing house prices in Peninsular Malaysia. Financial innovation in financial system now regards houses as a financial asset and speculation vehicle. Therefore, a house purchase is made to acquire not merely a necessity but also a financial asset which can generate future returns. Given the problems in the housing market, this paper aims to examine the determinants of house prices in Malaysia, including those such as income, population, foreign inflow and speculation. Design/methodology/approach This study adopts panel data analyses, namely, the fixed effect model (FEM) and the pooled mean group (PMG), and uses data at state level in quarterly frequency, spanning from 2005Q1 to 2013Q4. Findings Based on the results of FEM, these determinants influence house prices significantly. Moreover, the PMG results suggest that there is convergence in the model, which are indicated by the significant and negative sign of the error correction term. In conclusion, the rapidly increasing house price is not caused by speculation activities in the housing market. More precisely, Malaysian income is capable of catching up with the increasing house prices. Practical implications As income remains to be one of the major drivers in influencing Malaysian house price, Malaysian Government shall continue the policies of supply low cost houses to the low-income groups and My First Home Scheme (SRP) by offering less stringent rules in applying house loan for the first-time house buyers. Originality/value This study used the actual data of foreign housing purchase obtained from Malaysia Valuation and Property Services Department to represent foreign inflow; therefore, the results will reflect the impact of foreign inflow in a better manner.

Bankruptcy filings, flooding, real estate prices and Leading Index

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Billie Ann Brotman
Keyword(s):  
Housing Prices ◽  
The United States ◽  
Flood Insurance ◽  
Single Family ◽  
Personal Bankruptcy ◽  
Content Type ◽  
Independent Variables ◽  
Flooding Event ◽  
Flooding Events ◽  
The Impact

PurposeFlood damage to uninsured single-family homes shifts the entire burden of costly repairs onto the homeowner. Homeowners in the United States and in much of Europe can purchase flood insurance. The Netherlands and Asian countries generally do not offer flood insurance protection to homeowners. Uninsured households incur the entire cost of repairing/replacing properties damaged due to flooding. Homeowners’ policies do not cover damage caused by flooding. The paper examines the link between personal bankruptcy and the severity of flooding events, property prices and financial condition levels.Design/methodology/approachA fully modified ordinary least squares (FMOLS) regression model is developed which uses personal bankruptcy filings as its dependent variable during the years 2000 through 2018. This time-series model considers the association between personal bankruptcy court filings and costly, widespread flooding events. Independent variables were selected that potentially act as mitigating factors reducing bankruptcy filings.FindingsThe FMOLS regression results found a significant, positive association between flooding events and the total number of personal bankruptcy filings. Higher flooding costs were associated with higher bankruptcy filings. The Home Price Index is inversely related to the bankruptcy dependent variable. The R-squared results indicate that 0.65% of the movement in the dependent variable personal bankruptcy filings is explained by the severity of a flooding event and other independent variables.Research limitations/implicationsThe severity of the flooding event is measured using dollar losses incurred by the National Flood Insurance program. A macro-case study was undertaken, but the research results would have been enhanced by examining local areas and demographic factors that may have made bankruptcy filing following a flooding event more or less likely.Practical implicationsThe paper considers the impact of the natural disaster flooding on bankruptcy rates filings. The findings may have implications for multi-family properties as well as single-family housing. Purchasing flood insurance generally mitigates the likelihood of severe financial risk to the property owner.Social implicationsNatural flood insurance is underwritten by the federal government and/or by private insurers. The financial health of private property insurers that underwrite flooding and their ability to meet losses incurred needs to be carefully scrutinized by the insured.Originality/valuePrior studies analyzing the linkages existing between housing prices, natural disasters and bankruptcy used descriptive data, mostly percentages, when considering this association. The study herein posits the same questions as these prior studies but used regression analysis to analyze the linkages. The methodology enables additional independent variables to be added to the analysis.

Assessing the impact of Covid-19 pandemic in Turkey with a novel economic uncertainty index

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Erhan Mugaloglu ◽  
Ali Yavuz Polat ◽  
Hasan Tekin ◽  
Edanur Kılıç
Keyword(s):  
Industrial Production ◽  
Explanatory Power ◽  
Principal Component ◽  
Intermediate Goods ◽  
Economic Uncertainty ◽  
Content Type ◽  
Uncertainty Shocks ◽  
Political Events ◽  
Uncertainty Index ◽  
The Impact

PurposeThis study aims to measure economic uncertainty in Turkey by a novel economic uncertainty index (EUI) employing principal component analysis (PCA). We assess the impact of Covid-19 pandemic in Turkey with our constructed uncertainty index.Design/methodology/approachIn order to obtain the EUI, this study employs a dimension reduction method of PCA using 14 macroeconomic indicators that spans from January 2011 to July 2020. The first principal component is picked as a proxy for the economic uncertainty in Turkey which explains 52% of total variation in entire sample. In the second part of our analysis, with our constructed EUI we conduct a structural vector autoregressions (SVAR) analysis simulating the Covid-19-induced uncertainty shock to the real economy.FindingsOur EUI sensitively detects important economic/political events in Turkey as well as Covid-19-induced uncertainty rising to extremely high levels during the outbreak. Our SVAR results imply a significant decline in economic activity and in the sub-indices as well. Namely, industrial production drops immediately by 8.2% and cumulative loss over 8 months will be 15% on average. The losses in the capital and intermediate goods are estimated to be 18 and 25% respectively. Forecast error variance decomposition results imply that uncertainty shocks preserve its explanatory power in the long run, and intermediate goods production is more vulnerable to uncertainty shocks than overall industrial production and capital goods production.Practical implicationsThe results indicate that monetary and fiscal policy should aim to decrease uncertainty during Covid-19. Moreover, since investment expenditures are affected severely during the outbreak, policymakers should impose investment subsidies.Originality/valueThis is the first study constructing a novel EUI which sensitively captures the critical economic/political events in Turkey. Moreover, we assess the impact of Covid-19-driven uncertainty on Turkish Economy with a SVAR model.

Modelling the significance of social support and entrepreneurial skills for determining entrepreneurial behaviour of individuals

2018 ◽  
Vol 14 (3) ◽  
pp. 242-266 ◽  
Author(s):  
Muhammad Shoaib Farooq
Keyword(s):  
Social Support ◽  
Explanatory Power ◽  
Entrepreneurial Intention ◽  
Subjective Norms ◽  
Policy Makers ◽  
Content Type ◽  
Entrepreneurial Behaviour ◽  
Entrepreneurial Skills ◽  
Proposed Model ◽  
The Impact

Purpose Although entrepreneurial behaviour is considered a key element for economic development, yet very less is known about the determinants of factors leading towards entrepreneurial intention and behaviour. In order to bridge this gap, the purpose of this paper is to investigate the role of social support and entrepreneurial skills in determining entrepreneurial behaviour of individuals. Developing on the base of the theory of planned behaviour (TPB), this study investigates the relationship between social support, entrepreneurial skills and entrepreneurial behaviour along with existing constructs of the TPB (i.e. attitude, subjective norms, perceived behavioural control and entrepreneurial intention). Design/methodology/approach Data was collected from 281 respondents using a simple random sampling method, and the variance-based partial least-squares, structural equation modelling (PLS-SEM) approach was used for testing the proposed conceptual model. Findings Findings of this study have validated the proposed model, which have an explanatory power of 68.3 per cent. Moreover, findings reveal that social support and entrepreneurial skills have a significant impact on entrepreneurial intention of individuals. However, an unanticipated and non-significant relation between subjective norms and entrepreneurial intention is also found. Research limitations/implications Due to the limited scope of this study, a multi-group analysis is not possible, which is considered as a limitation of this study. Moreover, due to time constraints, this study is conducted within a specified time-frame; however, a longitudinal study over a period of three to six years can overcome this limitation. Practical implications Findings of this study are expected to have substantial implications for policy makers, future researchers and academicians. Outcomes of this study can help to better understand the cognitive phenomenon of nascent entrepreneurs. Moreover, it is expected that this study can serve as a torch-bearer for policy makers to develop better entrepreneurial development programmes, policies and initiatives for promoting self-employment behaviour. Originality/value Findings of this study are a unique step forward and offer new insights towards a better understanding of the determinants of entrepreneurial behaviour. Moreover, this study extends Ajzen’s (1991) TPB in the context of entrepreneurial behaviour. By introducing and investigating the impact of two new variables, i.e. social support and entrepreneurial skills in the TPB and by validating the proposed model with PLS-SEM approach, this study makes a sizeable theoretical, methodological and contextual contribution in the overall body of knowledge.

Property investor decisions using income and rental ratio signals

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Billie Ann Brotman
Keyword(s):  
Real Estate ◽  
Housing Market ◽  
Discount Rate ◽  
Price Index ◽  
Housing Prices ◽  
Housing Price ◽  
Consumer Sentiment ◽  
Content Type ◽  
Income Ratio ◽  
Real Estate Prices

PurposeThis paper, a case study, aims to consider whether the income ratio and rental ratio tracks the formation of residential housing price spikes and their collapse. The ratios are measuring the risk associated with house price stability. They may signal whether a real estate investor should consider purchasing real property, continue holding it or consider selling it. The Federal Reserve Bank of Dallas (Dallas Fed) calculates and publishes income ratios for Organization for Economic Cooperation and Development countries to measure “irrational exuberance,” which is a measure of housing price risk for a given country's housing market. The USA is a member of the organization. The income ratio idea is being repurposed to act as a buy/sell signal for real estate investors.Design/methodology/approachThe income ratio calculated by the Dallas Fed and this case study's ratio were date-stamped and graphed to determine whether the 2006–2008 housing “bubble and burst” could be visually detected. An ordinary least squares regression with the data transformed into logs and a regression with structural data breaks for the years 1990 through 2019 were modeled using the independent variables income ratio, rent ratio and the University of Michigan Consumer Sentiment Index. The descriptive statistics show a gradual increase in the ratios prior to exposure to an unexpected, exogenous financial shock, which took several months to grow and collapse. The regression analysis with breaks indicates that the income ratio can predict changes in housing prices using a lead of 2 months.FindingsThe gradual increases in the ratios with predetermine limits set by the real estate investor may trigger a sell decision when a specified rate is reached for the ratios even when housing prices are still rising. The independent variables were significant, but the rent ratio had the correct sign only with the regression with time breaks model was used. The housing spike using the Dallas Fed's income ratio and this study's income ratio indicated that the housing boom and collapse occurred rapidly. The boom does not appear to be a continuous housing price increase followed by a sudden price drop when ratio analysis is used. The income ratio is significant through time, but the rental ratio and Consumer Sentiment Index are insignificant for multiple-time breaks.Research limitations/implicationsInvestors should consider the relative prices of residential housing in a neighborhood when purchasing a property coupled with income and rental ratio trends that are taking place in the local market. High relative income ratios may signal that when an unexpected adverse event occurs the housing market may enter a state of crisis. The relative housing prices to income ratio indicates there is rising housing price stability risk. Aggregate data for the country are used, whereas real estate prices are also significantly impacted by local conditions.Practical implicationsRatio trends might enable real estate investors and homeowners to determine when to sell real estate investments prior to a price collapse and preserve wealth, which would otherwise result in the loss of equity. Higher exuberance ratios should result in an increase in the discount rate, which results in lower valuations as measured by the formula net operating income dividend by the discount rate. It can also signal when to start reinvesting in real estate, because real estate prices are rising, and the ratios are relative low compared to income.Social implicationsThe graphical descriptive depictions seem to suggest that government intervention into the housing market while a spike is forming may not be possible due to the speed with which a spike forms and collapses. Expected income declines would cause the income ratios to change and signal that housing prices will start declining. Both the income and rental ratios in the US housing market have continued to increase since 2008.Originality/valueA consumer sentiment variable was added to the analysis. Prior researchers have suggested adding a consumer sentiment explanatory variable to the model. The results generated for this variable were counterintuitive. The Federal Housing Finance Agency (FHFA) price index results signaled a change during a different year than when the S&P/Case–Shiller Home Price Index is used. Many prior studies used the FHFA price index. They emphasized regulatory issues associated with changing exuberance ratio levels. This case study applies these ideas to measure relative increases in risk, which should impact the discount rate used to estimate the intrinsic value of a residential property.

Are regional house prices stationary in Iran? New evidence using Fourier quantile unit root test

2019 ◽  
Vol 12 (5) ◽  
pp. 849-864
Author(s):  
Arash Hadizadeh
Keyword(s):  
Interest Rates ◽  
Housing Market ◽  
Unit Root ◽  
House Prices ◽  
Housing Prices ◽  
Unit Root Test ◽  
Generalized Least Squares ◽  
Main Concern ◽  
Content Type ◽  
Positive Effects

Purpose In the Iranian economy, investing in the housing market has been very important and beneficial for investors and households, because of inflationary environment, low real interest rates, underdeveloped financial and tax systems and economic sanctions. Hence, prediction of house prices is the main concern of housing market agents in the economy. The purpose of this paper is to test the stationary properties of Iran's provinces to improve the prediction of future housing prices. Design/methodology/approach In this paper, the authors have tested the stationary properties of 20 Iran’s province centers over the period from 1993 to 2017 using a novel Fourier quantile unit root test and conventional ordinary/generalized least squares (O/GLS) linear unit root/stationary tests. Findings According to conventional O/GLS linear unit root/stationary tests, most of the house prices series exhibit random walk behavior, whereas by applying the Fourier quantile unit root test, the null hypothesis of unit root is rejected for 15 out of 20 series. Other results indicated that house prices of cities responded differently to positive and negative shocks. Originality/value Previous studies only addressed conventional OLS or GLS linear unit root or stationary tests, but novel Fourier quantile unit root test was not used. New results were obtained based on this unit root test, that, as a priori knowledge, will help benefiting from the positive effects, or avoiding being victimized by the negative effects.

Subjective social class and individual preferences for redistribution

2019 ◽  
Vol 47 (2) ◽  
pp. 173-189
Author(s):  
Anil Duman
Keyword(s):  
Social Class ◽  
Multilevel Models ◽  
Explanatory Power ◽  
Policy Preferences ◽  
Content Type ◽  
Preferences For Redistribution ◽  
Class Status ◽  
The Individual ◽  
Subjective Social Class ◽  
The Impact

Purpose The recent increase in economic inequalities in many countries heightened the debates about policy preferences on income distribution. Attitudes toward inequality vary greatly across countries and numerous explanations are offered to clarify the factors leading to support for redistribution. The purpose of this paper is to examine the link between subjective social class and redistributive demands by jointly considering the individual and national factors. The author argues that subjective measures of social positions can be highly explanatory for preferences about redistribution policies. Design/methodology/approach The author uses data from 48 countries gathered by World Values Survey and empirically tests the impact of self-positioning into classes by multilevel ordered logit model. Several model specifications and estimation strategies have been employed to obtain consistent estimates and to check for the robustness of the results. Findings The findings show that, in addition to objective factors, subjective class status is highly explanatory for redistributive preferences across countries. The author also exhibits that there is interaction between self-ranking of social status and national context. The author’s estimations from the multilevel models verify that subjective social class has greater explanatory power in more equal societies. This is in contrast to the previous studies that establish a positive link between inequality and redistribution. Originality/value The paper contributes to the literature by introducing subjective social class as a determinant. Self-ranked positions can be very relieving about policy preferences given the information these categorizations encompass about individuals’ perceptions about their and others’ place in the society.

Analysis of housing prices in Petaling district, Malaysia using functional relationship model

2019 ◽  
Vol 12 (5) ◽  
pp. 884-905
Author(s):  
Yun Fah Chang ◽  
Wei Cheng Choong ◽  
Sing Yan Looi ◽  
Wei Yeing Pan ◽  
Hong Lip Goh
Keyword(s):  
Housing Market ◽  
Functional Relationship ◽  
Housing Prices ◽  
Hedonic Model ◽  
Analysis Tool ◽  
Content Type ◽  
Proposed Model ◽  
Relationship Model ◽  
Housing Attributes ◽  
House Buyers

Purpose The purpose of this paper is to analyse and predict the housing prices in Petaling district, Malaysia and its six sub-regions with a set of housing attributes using functional relationship model. Design/methodology/approach A new multiple unreplicated linear functional relationship model with both the response and explanatory variables are subject to errors is proposed. A total of 41,750 housing transacted records from November 2008 to February 2016 were used in this study. These data were divided into 70% training and 30% testing sets for each of the selected sub-regions. Individual housing price was regressed on nine housing attributes. Findings The results showed the proposed model has better fitting ability and prediction accuracy as compared to the hedonic model or multiple linear regression. The proposed model achieved at least 20% and 40% of predictions that have less than 5% and 10% deviations from the actual transacted housing prices, respectively. House buyers in these sub-regions showed similar preferences on most of the housing attributes, except for residents in Shah Alam who preferred to stay far away from shopping malls, and leasehold houses in Sri Kembangan are more valuable. From the h-nearest houses indicator, it is concluded that the housing market in Sungai Buloh is the most volatile in Petaling District. Research limitations/implications As the data used are the actual housing transaction records in Petaling District, it represents only a segment of Malaysian urban population. The result will not be generalized to the entire Malaysian population. Practical implications This study is expected to provide insights to policymakers, property developers and investors to understand the volatility of the housing market and the influence of determinants in different sub-regions. The potential house buyers could also use the model to determine if a house is overpriced. Originality/value This study introduces measurement errors into the housing attributes to provide a more reliable analysis tool for the housing market. This study is the first housing research in Malaysia that used a large number of actual housing transaction records. Previous studies relied on small survey samples.

The effects of political, economic and financial components of country risk on housing prices in South Africa

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Paul-Francois Muzindutsi ◽  
Sanelisiwe Jamile ◽  
Nqubeko Zibani ◽  
Adefemi A. Obalade
Keyword(s):  
Risk Factors ◽  
South Africa ◽  
Housing Market ◽  
Time Series Data ◽  
Housing Prices ◽  
Political Risk ◽  
Country Risk ◽  
Series Data ◽  
Content Type ◽  
Short Run

Purpose The housing market in South Africa has the potential to drive economic growth and attract foreign investment, but it can be affected by various risk factors. This paper aims to conduct an empirical analysis of the effect of country risk components on the housing market in South Africa. Design/methodology/approach Linear and nonlinear autoregressive distributed lag (ARDL) models were used to evaluate the effects of the economic, financial and political risk factors of country risk on the prices of different segments of houses based on 276 monthly time-series data from January1995 to December 2015. Findings First, the results established that the three housing indices were more sensitive to political risk in the long run. Second, short run results showed that the three housing indices were largely influenced by their own preceding adjustments in the short run albeit minimal influences from political risk. Third, large housing segments indicated a higher magnitude of the country risk effect in South Africa. Originality/value This paper concluded that the response of housing prices to changes in the country risk components differed across the three segments of the housing market in South Africa. Consequently, this study presented the first comparison of the reactions of different housing segments to different components country risk.

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.

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