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.

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 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.

High house prices may be global systemic risk

2016 ◽  
Keyword(s):  
Interest Rates ◽  
Household Income ◽  
House Prices ◽  
House Price ◽  
Content Type ◽  
Price Boom ◽  
Advanced Economies ◽  
The Us ◽  
Property Markets

Subject The rise in global house prices. Significance In the first quarter of 2015, the global house price index, aggregating prices in 52 countries, was at about the same level as in early 2007, according to IMF data. This recovery has occurred in a period of wage gains in most emerging markets (EMs), but little or no growth in household income across most advanced economies. Living costs excluding housing have stagnated and interest rates have been exceptionally low. Yet US interest rates are rising now and global prices are unlikely to keep falling beyond 2016, while many EMs have slumped into recession. As households are hit by more adverse trends, property markets and the related sectors will be affected. Impacts The EM house price boom will be curbed by slowing income growth and weaker economic prospects. High house-prices-to-household-income ratios and household debt might require the introduction of macroprudential tools. The US housing market will stay affordable compared to its long-term average and to Europe's.

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.

LIBOR, base rate spreads and the UK housing market

2015 ◽  
Vol 8 (1) ◽  
pp. 118-134 ◽  
Author(s):  
Martin Hinch ◽  
Jim Berry ◽  
William McGreal ◽  
Terry Grissom
Keyword(s):  
Time Series ◽  
Interest Rates ◽  
House Prices ◽  
House Price ◽  
Base Rate ◽  
Percentage Change ◽  
Content Type ◽  
Change Models ◽  
The Uk ◽  
The Impact

Purpose – The purpose of this paper is to analyse how London Interbank Offered Rate Index (LIBOR) and the spread between LIBOR and the base rate of interest as set by the Bank of England (BoE) influences the variation in house prices in the UK. Design/methodology/approach – This paper uses monthly data over a long time series, since 1986, to investigate the relationships between house price and LIBOR. Data are drawn from several different sources to include housing, financial and macro-economic variables. The time series is sub-divided into a series of splines based on stages in the economic and property market cycle. Both value-based and percentage change models are developed. Findings – The results show that BoE base/LIBOR margin variable has a strong positive and significant effect on house price; however, the percentage change model infers a weaker and inverse relationship. The spline analysis re-emphasised the significance of the BoE base/LIBOR margin variable. Where variation between base rates and LIBOR is reduced, a significant positive effect can be observed in the average house price; however, where significant variation exists, the BoE base/LIBOR margin has little effect and LIBOR itself becomes a significant driver. Research limitations/implications – The results highlight that the predictive qualities of the BoE base/LIBOR margin, as the contribution of this margin to the explanation of house price, exceeds both the base rate and LIBOR variables individually. Also highlighted is the contribution of unemployment to the explanation of house price. In both the value and percentage change models, unemployment is shown as a negative and highly significant contributor. Originality/value – Previous papers have demonstrated the important linkage between house price and interest rates, the originality in this paper lies in examining the impact of LIBOR and the spreads between LIBOR and base rate as key variables influencing variation in UK house prices.

Causal effects of immigration inflows on house prices in a traditionally non-destination country

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Woei Chyuan Wong ◽  
Jan-Jan Soon
Keyword(s):  
Fixed Effects ◽  
Positive Impact ◽  
House Prices ◽  
Housing Prices ◽  
House Price ◽  
Developed Countries ◽  
Annual Data ◽  
Content Type ◽  
Variable Approach ◽  
The Impact

Purpose The purpose of this study is to examine the causal impact of international immigration inflows on housing prices at the state level in Malaysia from 2007 to 2018. Design/methodology/approach Hedonic regressions using both fixed effects and first difference approaches are used to estimate the impact of immigration inflows on house prices in Malaysia. This study deals with potential endogeneity of immigrants’ choices of destination states in Malaysia by using a shift-share instrument variable approach. Specifically, historical shares of immigrants in a state are used to predict current immigrant inflows to a particular state. The predicted value of immigration flows is then inserted into the house price regression models in place of the actual immigration flows. Findings Using annual data for 14 states from 2007 to 2018, this study documents the positive impact of immigration inflows on house prices in Malaysia. The authors find that a 1% increase in immigration inflows is associated with an increase of 10.2% (first difference) and 13.4% (fixed effects) in house prices. The economic impact is larger in magnitude than that found in developed countries. Contrary to existing studies that find immigration inflows to be associated with native flight, the authors find support for the attraction effects hypothesis, where immigration inflow is positive and significantly related to net native flows. Research limitations/implications The effects of immigration inflows are economically significant, considering that the effects are 10 times larger than those documented in the USA. Policymakers in Malaysia ought to monitor house price trends in immigrant-popular states to ensure that natives are not priced out by new immigrants. Originality/value To the best of the authors’ knowledge, this is perhaps the first study to focus on the relationship between immigration inflows and house prices in Malaysia. Focusing on Malaysia has at least two originality aspects. First, Malaysia is relatively not an immigrant-popular destination. Second, Malaysia has a multiracial and heterogenous society among its natives. The findings, obtained within these two settings, would therefore provide a wider scope of result generalization, and natural experiment grounds for causal implications of our results.

Alternative strategies to change negative output gaps rate in China

2014 ◽  
Vol 52 (7) ◽  
pp. 1319-1329
Author(s):  
Bing Xu ◽  
Xiaowen Hu
Keyword(s):  
Interest Rates ◽  
House Prices ◽  
House Price ◽  
Output Gap ◽  
Control Variables ◽  
Alternative Strategies ◽  
Content Type ◽  
Price Adjustments ◽  
Output Gaps ◽  
Negative Output

Purpose – The purpose of this paper is to find alternative strategies to change negative output gaps in China. Design/methodology/approach – A path Philips curves approach is proposed to investigate output gaps, which develops hybrid Philips curves with the control variables of money, house prices and interest rates. Findings – An alternative strategy to stop the decline in output gaps rate is to perform interest rate, house price, and money growth rate about 3, 1 and 15 percent, respectively. The results also indicate that only one of monetary increase, changes in interest rates, and house price adjustments are difficult to change the negative output gap. Practical implications – Alternative strategies cannot only change the negative output gap, but also succeed in pushing the inflation rate down to 3 percent. Originality/value – This study provides a new path Philips curves to simulate how the macroscopic control variables influence output and inflation. It provides a useful insight for stopping the decline in output gaps.

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.

News shocks, government subsidies and housing prices in Brazil

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Cássio Besarria ◽  
Marcelo Silva ◽  
Diego Jesus
Keyword(s):  
Real Estate ◽  
Interest Rates ◽  
Housing Prices ◽  
Financial Sector ◽  
Government Policies ◽  
Housing Sector ◽  
Dsge Model ◽  
News Shocks ◽  
Content Type ◽  
Real Estate Prices

Purpose In recent years, housing prices in Brazil have shown a surprising growth. An important issue is trying to understand what elements can explain this behavior. This study aims to investigate the hypothesis that a generalized optimism associated with government policies directed to the housing sector may be behind the behavior of real estate prices. This study develops a dynamic stochastic general equilibrium (DSGE) model to investigate these issues. The results showed that subsidies combined with the easing of credit conditions were able to positively influence real estate prices. Moreover, unanticipated shocks had a greater impact on housing prices than anticipated shocks. Design/methodology/approach The DSGE model was developed to analyze the relationship between economic agents’ expectations about future economic developments, also known in the literature as “news shocks,” expansionary fiscal policy and housing prices in Brazil. The economy is composed of families, entrepreneurs, final goods firms, a financial sector and a fiscal authority. Families are divided into two groups: patients or savers and impatient or debtors. They differ in terms of their intertemporal discount factors. Both provide labor for firms producing non-durable goods. Impatient families are restricted in the amount of borrowing they can take. The production side of economy model is given by the consumer goods production sector. The financial sector is composed of a representative bank that pays the deposits made by patient families and channels resources for the granting of housing loans with the accumulation of assets subject to regulatory restrictions. Findings The results show that both price subsidies and subsidized interest rates exerted a positive influence on housing prices in Brazil. In response to a housing demand shock, housing prices display a greater increase the greater are the subsidies to low income families. The authors show that anticipated shocks have a larger impact on housing prices than unexpected shocks. Therefore, the results support the idea that the wave of good news, optimistic behavior and government policies aimed at the housing sector were behind the behavior of housing prices in Brazil. Originality/value There are some studies applied to the Brazilian economy that mention some of these stimuli. In this study, the authors focused on studies proposed by Mendonça et al. (2011), Mendonça (2013), Silva et al. (2014) and Besarria et al. (2016). In general, the authors show that there is a negative relationship between monetary policy instruments and real estate prices. This paper differs from these authors by considering the effects of government subsidies, subsidized interest rates and anticipated shocks from a DSGE model, thus explicitly addressing their effects on housing prices in Brazil.

Turkish Housing Market Dynamics: An Estimated DSGE Model

2021 ◽  
Vol 15 (2) ◽  
pp. 238-267
Author(s):  
Mustafa Ozan Yıldırım ◽  
Mehmet İvrendi
Keyword(s):  
Monetary Policy ◽  
Housing Market ◽  
House Prices ◽  
House Price ◽  
Policy Instrument ◽  
Dsge Model ◽  
Macroeconomic Variables ◽  
Dynamic Stochastic ◽  
Monetary Policy Reaction Function ◽  
The Impact

In this article, we investigate the underlying driving dynamics behind house price variations in Turkey by estimating a dynamic stochastic general equilibrium (DSGE) model in which the housing market and collateral constraints are included. The model also analyses the interaction between macroeconomic variables and the housing market by making policy simulations under different loan-to-value (LTV) ratios, which are used as a housing market-specific economic policy tool. The model is extended by including the traditional Taylor rule with house prices for representing monetary policy. Our findings show that house prices in Turkey are largely explained by housing preference shocks. Besides, we find that monetary policy shock plays a small role in determining the variables of the housing market in the short-term period. However, the magnitude of the impact of housing market shocks on the rest of the economy depends on the LTV ratios. The higher the LTV ratio, the higher are the effects of the government’s housing policy instrument for stabilising the housing market on real macroeconomic variables such as consumption and output in Turkey. Finally, our findings show that the fluctuations in house prices have not played a substantial role in the monetary policy reaction function of Turkey. JEL Codes: E32, E52, E44, E51, R31

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