scholarly journals Is there a bubble in the Swedish housing market?

2019 ◽  
Vol 12 (1) ◽  
pp. 32-61 ◽  
Author(s):  
Maher Asal
Keyword(s):  
Interest Rates ◽  
Housing Market ◽  
House Prices ◽  
Test Procedure ◽  
Unit Root Test ◽  
Housing Price ◽  
User Cost ◽  
Return To Equilibrium ◽  
Content Type ◽  
Factors Affecting

Purpose This paper aims to investigate the presence of a housing bubble using Swedish data from 1986Q1-2016Q4 by using various methods. Design/methodology/approach First, the authors use affordability indicators and asset-pricing approaches, including the price-to-income ratio, price-to-rent ratio and user cost, supplemented by a qualitative discussion of other factors affecting house prices. Second, the authors use cointegration techniques to compute the fundamental (or long-run) price, which is then compared with the actual price to test the degree of Sweden’s housing price bubble during the studied period. Third, they apply the univariate right-tailed unit root test procedure to capture bursting bubbles and to date-stamp bubbles. Findings The authors find evidence for rational housing bubbles with explosive behavioral components beginning in 2004. These bubbles do not continuously diverge but instead periodically revert to their fundamental value. However, the deviation is persistent, and without any policy correction, it takes decades for real house prices to return to equilibrium. Originality/value The policy implication is that monetary policy designed to contain mortgage demand and thereby prevent burst episodes in the housing market must address external imbalances, as revealed in real exchange rate undervaluation. It is unlikely that current policies will stop the rise of house prices, as the growth of mortgage credit, improvement in Sweden’s international competitiveness and the path of interest rates are much more important factors.

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.

scholarly journals Cyclical and structural change in the UK housing market

2015 ◽  
Vol 8 (1) ◽  
pp. 85-103 ◽  
Author(s):  
Michael White
Keyword(s):  
Financial Crisis ◽  
Interest Rates ◽  
Housing Market ◽  
Money Supply ◽  
House Prices ◽  
Mortgage Lending ◽  
Market Liquidity ◽  
Content Type ◽  
Factors Affecting ◽  
Short Run

Purpose – This paper aims to examine factors affecting house prices separating cyclical and structural influences. In addition to considering the role of income and interest rates, it examines whether access to a key source of liquidity, mortgage finance, could affect the long-term behaviour of the market rather than being a short run impact. In addition, the paper considers whether the effects of mortgage funding and the financial crisis affect all regions equally or whether there exist particular differences across regions of the UK. Design/methodology/approach – Using quarterly time series data from 1983q1 to 2011q2, the paper employs a Johansen cointegration approach to identify the long-run (permanent) and short-run (transitory) factors affecting house prices both at national and regional levels. It identifies whether there is a separate influence for mortgage lending from interest rates and general money market liquidity, as captured by money supply M3, and whether these effects are permanent or temporary. The paper employs impulse response functions to examine house price evolution due to innovations in mortgage lending and quantifies these effects with and without the financial crisis. Findings – The findings indicate that real personal disposable income, mortgage market liquidity, interest rates and money supply as well as housing stock supply impact house prices permanently with the expected signs. The findings are broadly consistent at national and regional level, although there are some significant regional variations in results. The mean reversion of the housing markets is captured via the error correction term which is significant at the national level and in all but three regions. Impulse response functions show how house prices respond to shocks in mortgage lending and how this varies with and without a financial crisis. Research limitations/implications – The importance of mortgage lending to the housing market is a clear result from the research in addition to income, interest rate and money supply effects. One implication is that factors affecting mortgage lending supply can impact the housing market in both the short and long run. Practical implications – Given the significance of mortgage finance for house price evolution, the paper discusses how the Help-to-Buy policy may help to overcome the limitations created by the reaction of the mortgage lending sector to the financial crisis. Social implications – Access to homeownership has been limited by greater downpayment constraints introduced by lenders since 2008/2009. Policies that reduce these constraints may enable households to change to the type of tenure they prefer. Originality/value – The paper identifies the importance of mortgage lending for the housing market both nationally and regionally using an econometric approach that quantifies the role of fundamentals in both the long and short run.

scholarly journals The influence of a mortgage interest and capital deduction policy on house prices

2020 ◽  
Vol 38 (6) ◽  
pp. 563-577
Author(s):  
Wouter Vangeel ◽  
Laurens Defau ◽  
Lieven De Moor
Keyword(s):  
Interest Rates ◽  
Fixed Effects ◽  
Design Methodology ◽  
House Prices ◽  
Housing Prices ◽  
Housing Price ◽  
Content Type ◽  
Mortgage Interest ◽  
Price Determinants ◽  
Fixed Effects Regression

PurposeSince 2005, Belgian housing prices have strongly increased. As the timing coincides with the implementation of a new fiscal package in order to stimulate homeownership, our study attempts to provide an understanding whether the mortgage interest and capital deduction (MICPD) policy has had the side-effect of increasing housing prices while, at the same time, controlling for key housing price determinants.Design/methodology/approachA fixed-effects regression model is used on a panel dataset of the three Belgian regions over the period 1995–2015.FindingsEstimations are carried out separately for different house types, being useful as our empirical analysis ascertains a significant price-increasing effect for ordinary houses and apartments but a significant price-reducing effect for villas. In addition, we find, among other things, that interest rates' influence has been less substantial than commonly thought.Originality/valueThese results are relevant for all governments willing to stimulate homeownership through fiscal stimuli.

scholarly journals Is the Australian housing market in a bubble?

2018 ◽  
Vol 13 (1) ◽  
pp. 77-95 ◽  
Author(s):  
Justine Wang ◽  
Alla Koblyakova ◽  
Piyush Tiwari ◽  
John S. Croucher
Keyword(s):  
Interest Rates ◽  
Housing Market ◽  
House Prices ◽  
National Level ◽  
Policy Implications ◽  
Data Set ◽  
Content Type ◽  
Housing Boom ◽  
Housing Bubbles

Purpose This paper aims to explore principal drivers affecting prices in the Australian housing market, aiming to detect the presence of housing bubbles within it. The data set analyzed covers the past two decades, thereby including the period of the most recent housing boom between 2012 and 2015. Design/methodology/approach The paper describes the application of combined enhanced rigorous econometric frameworks, such as ordinary least square (OLS), Granger causality and the Vector Error Correction Model (VECM) framework, to provide an in-depth understanding of house price dynamics and bubbles in Australia. Findings The empirical results presented reveal that Australian house prices are driven primarily by four key factors: mortgage interest rates, consumer sentiment, the Australian S&P/ASX 200 stock market index and unemployment rates. It finds that these four key drivers have long-term equilibrium in relation to house prices, and any short-term disequilibrium always self-corrects over the long term because of economic forces. The existence of long-term equilibrium in the housing market suggests it is unlikely to be in a bubble (Diba and Grossman, 1988; Flood and Hodrick, 1986). Originality/value The foremost contribution of this paper is that it is the first rigorous study of housing bubbles in Australia at the national level. Additionally, the data set renders the study of particular interest because it incorporates an analysis of the most recent housing boom (2012-2015). The policy implications from the study arise from the discussion of how best to balance monetary policy, fiscal policy and macroeconomic policy to optimize the steady and stable growth of the Australian housing market, and from its reconsideration of affordability schemes and related policies designed to incentivize construction and the involvement of complementary industries associated with property.

scholarly journals Are There Any Housing Bubbles in Turkey?

2021 ◽  
Author(s):  
Özge Korkmaz ◽  
Ebru Çağlayan Akay ◽  
Hoşeng Bülbül
Keyword(s):  
Housing Market ◽  
House Prices ◽  
Housing Prices ◽  
Housing Price ◽  
Economic Fundamentals ◽  
The Past ◽  
Price Increases ◽  
Long Time ◽  
Housing Bubbles ◽  
Turkish Lira

It is very important that the housing market, which meets the most basic need of people is needed for shelter from the past to the present, has a stable structure. The instability structure of the housing market is generally associated with the presence of housing bubbles. The deviation of housing prices from their basic value and not being able to be explained by economic fundamentals leads to the formation of housing bubbles. Housing bubbles can lead to permanent losses, as it may take a long time to return to normal prices. For Turkey as a developing country, it is important to identify an unstable structure in house prices discuss the basic economic factors related to this. After the global increases in housing prices, inflation, and depreciation in the Turkish lira, Turkey has become the country with the highest housing price increases globally in 2020. In the study, the presence of bubbles in the housing market for Ankara, Izmir, Istanbul, and Turkey in general, was investigated by SADF and GSADF unit root tests for the period 2010:01-2021:02. In this context, the study examines the presence of bubbles in housing prices for Ankara, Izmir, Istanbul, and Turkey in general, which are the three cities with the highest price increases. As a result of the study, the presence of bubbles in the housing market has been determined for Ankara, Istanbul, Izmir, and Turkey in general.

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.

Rent or buy, what are the odds? Analysing the price-to-rent ratio for housing types within the Northern Ireland housing market

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Daniel Lo ◽  
Michael James McCord ◽  
John McCord ◽  
Peadar Thomas Davis ◽  
Martin Haran
Keyword(s):  
Housing Market ◽  
House Prices ◽  
House Price ◽  
Main Property ◽  
Property Market ◽  
Important Indicator ◽  
Content Type ◽  
Rental Market ◽  
Price Series ◽  
The Relationship

Purpose The price-to-rent ratio is often regarded as an important indicator for measuring housing market imbalance and inefficiency. A central question is the extent to which house prices and rents form part of the same market and thus whether they respond similarly to parallel stimulus. If they are close proxies dynamically, then this provides valuable market intelligence, particularly where causal relationships are evident. Therefore, this paper aims to examine the relationship between market and rental pricing to uncover the price switching dynamics of residential real estate property types and whether the deviation between market rents and prices are integrated over both the long- and short-term. Design/methodology/approach This paper uses cointegration, Wald exogeneity tests and Granger causality models to determine the existence, if any, of cointegration and lead-lag relationships between prices and rents within the Belfast property market, as well as the price-to-rent ratios amongst its five main property sub-markets over the time period M4, 2014 to M12 2018. Findings The findings provide some novel insights in relation to the pricing dynamics within Belfast. Housing and rental prices are cointegrated suggesting that they tend to move in tandem in the long run. It is further evident that in the short-run, the price series Granger-causes that of rents inferring that sales price information unidirectionally diffuse to the rental market. Further, the findings on price-to-rent ratios reveal that the detached sector appears to Granger-cause those of other property types except apartments in both the short- and long-term, suggesting possible spill-over of pricing signals from the top-end to the lower strata of the market. Originality/value The importance of understanding the relationship between house prices and rental market performance has gathered momentum. Although the house price-rent ratio is widely used as an indicator of over and undervaluation in the housing market, surprisingly little is known about the theoretical relationship between the price-rent ratio across property types and their respective inter-relationships.

Dynamic effects and spatial heterogeneity of land supply on housing price: evidence from Nanchang, China

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Zhijiang Wu ◽  
Yongxiang Wang ◽  
Wei Liu
Keyword(s):  
Spatial Heterogeneity ◽  
House Prices ◽  
Housing Prices ◽  
Housing Price ◽  
Dynamic Effects ◽  
Negative Effects ◽  
Land Supply ◽  
Content Type ◽  
Major Factors ◽  
The City

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.

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.

Factors affecting Chinese farmers’ microcredit participation

2019 ◽  
Vol 79 (1) ◽  
pp. 48-59 ◽  
Author(s):  
Ming Qin ◽  
Cheryl Joy Wachenheim ◽  
Zhigang Wang ◽  
Shi Zheng
Keyword(s):  
Interest Rates ◽  
Group Membership ◽  
Group Identification ◽  
Northern China ◽  
Family Characteristics ◽  
Content Type ◽  
Heckman Model ◽  
Factors Affecting ◽  
Financial Exclusion ◽  
Loan Approval

Purpose The purpose of this paper is to investigate factors affecting use of microcredit among farmers in Northern China. Design/methodology/approach A two-stage Heckman model is used to estimate the effect of farmer and family characteristics and loan and lending environment on likelihood of farmer participation in microcredit and the value of loans taken. Data from 342 first-hand observations in Northern China were used. Findings Social capital, production cost, non-labor family members, income, guarantee group membership, village head loan guarantee, and messenger use were found to increase use of microcredit. The same factors were found to affect the value of loans among participating farmers except a guarantor requirement for the loan replaces membership in a guarantee group. Practical implications Results support that there is demand for microcredit among farmers and that they are willing to take steps to obtain it including seeking membership in a household guarantee group. Identification of faced constraints facilitates understanding of supply-side efforts with potential to decrease financial exclusion with a focus on external-to-market intervention. Originality/value Pivotal findings are the importance of guarantee group membership for loan approval and that this requirement hinders farmers’ ability to obtain credit. Three alternatives are suggested to overcome this constraint including excluding low-risk borrowers from a group guarantee requirement; charging higher interest rates on high risk loans not supported by a guarantee; and development of insurance options to replace the guarantee.

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