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.

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 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.

How loan interest rate liberalization affects firms’ loan maturity structure

2014 ◽  
Vol 4 (2) ◽  
pp. 153-167 ◽  
Author(s):  
Jianfang Zhou ◽  
Jingjing Wang ◽  
Jianping Ding
Keyword(s):  
Interest Rate ◽  
Interest Rates ◽  
Manufacturing Companies ◽  
Short Term ◽  
Data Set ◽  
Content Type ◽  
Interest Rate Liberalization ◽  
Upper Limit ◽  
Maturity Structure

Purpose – After loan interest rate upper limit deregulation in October 2004, the financing environment in China changed dramatically, and the banks were eligible for risk compensation. The purpose of this paper is to focus on the influence of the loan interest rate liberalization on firms’ loan maturity structure. Design/methodology/approach – Based on Rajan's (1992) model, the authors constructed a trade-off model of how the banks choose long-term and short-term loans scales, and further analyzed banks’ loan term decisions under the loan interest rate upper limit deregulation or collateral cases. Then the authors used an unbalanced panel data set of 586 Chinese listed manufacturing companies and 9,376 observations during the period 1996-2011 to testify the theoretical conclusion. Furthermore, the authors studied the effect on firms with different characteristics of ownership or scale. Findings – The results show that the loan interest rate liberalization significantly decreases the private companies’ reliance on short-term loans and increases sensitivity to interest rates of state-owned companies’ long-term loans. But the results also show that the companies’ ownership still plays a key role on the long-term loans availability. When monetary policy tightened, small companies still have to borrow short-term loans for long-term purposes. As the bank industry is still dominated by state-owned banks and the deposit interest rate has upper limits, the effect of the loan interest rate liberalization on easing long-term credit constraints is limited. Originality/value – From a new perspective, the content and findings of this paper contribute to the study of the effect of the interest rate liberalization on China economy.

Australian PM challenge will hinder policy agenda

2015 ◽  
Keyword(s):  
Political Parties ◽  
Interest Rates ◽  
Prime Minister ◽  
Party Leader ◽  
Content Type ◽  
Developed Economies ◽  
Housing Bubbles ◽  
The Impact ◽  
The Eu

Significance Although a victory in the short term for Abbott, the narrow margin will only intensify doubts about his long-term prospects as party leader and as prime minister. The challenge continues a trend of instability across Australia's main political parties. The country is poised to enter a record 25th year of uninterrupted economic growth, yet has changed prime minister four times since 2007. Impacts Australia will remain one of the most robust developed economies throughout 2015, with growth rates far above those of the EU. The Reserve Bank's decision to cut interest rates indicates that there are worries of the impact of the China-induced mining slowdown. Concerns in state capitals about housing bubbles will grow and may be an issue in the next federal election.

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.

Public investment in agricultural R&D and extension

2015 ◽  
Vol 7 (1) ◽  
pp. 86-101 ◽  
Author(s):  
Dandan Zhang ◽  
Chunlai Chen ◽  
Yu Sheng
Keyword(s):  
Productivity Growth ◽  
Knowledge Spillovers ◽  
Moving Average ◽  
Public Investment ◽  
Agricultural Productivity ◽  
Policy Implications ◽  
Data Set ◽  
Content Type ◽  
D Investment

Purpose – The purpose of this paper is to analyze the effects of public investment in agricultural R&D and extension on broadacre farming productivity in Australia. Design/methodology/approach – An autoregressive integrated moving average (ARIMA) regression model is applied to estimate the effects of public investment in agricultural R&D and extension on Australian braodacre productivity. Findings – The study reveals that public investment in agricultural R&D and extension has contributed almost two-thirds of average annual broadacre productivity growth between 1952-1953 and 2006-2007, the average internal rate of return to public investment in agricultural R&D and extension was 28.4 and 47.5 per cent a year, respectively, and overseas spill-ins is an important source of domestic agricultural productivity growth. Practical implications – Policy implications: the findings suggest that increasing public investment in agricultural R&D and extension and maintaining agricultural R&D policy stability are equally important to have a sustained long-term agricultural productivity growth, and maintaining an open trade and investment regime is important to benefit from foreign knowledge spillovers which is especially important for developing countries. Originality/value – This paper contributes to the existing literature by employing more sophisticated econometric techniques with an extended data set for the period from 1952-1953 to 2006-2007. The study separates the contribution of public R&D investment and the extension investment, and also takes into account the contribution of overseas public investment on the TFP growth in the Australian broadacre sector.

Club convergence and drivers of house prices across Turkish cities

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Lokman Gunduz ◽  
Mustafa Kemal Yilmaz
Keyword(s):  
Housing Market ◽  
Logit Model ◽  
House Prices ◽  
Emerging Market ◽  
Ordered Logit ◽  
Data Set ◽  
Content Type ◽  
Ordered Logit Model ◽  
Convergence Clubs ◽  
Convergence Club

PurposeThis paper aims to examine the convergence pattern of residential house prices in a panel of 55 major cities in Turkey over the period between 2010 and 2018 and to investigate the determinants of convergence club formations.Design/methodology/approachThe authors applied the log t-test to identify the convergence clubs and estimated ordered logit model to determine the key drivers.FindingsThe results suggest that there are five convergence clubs and confirm the heterogeneity of the Turkish housing market. Istanbul, the commercial capital, and Mugla, an attractive tourist destination, are at the top of the housing market and followed by the cities located in the western part, particularly along the Aegean and Mediterranean coasts of Turkey. Moreover, the ordered logit model results point out that the differences in employment rate, climate, population density and having a metropolitan municipality play a significant role in determining convergence club membership.Practical implicationsLarge-scale policy measures aiming to increase employment opportunities in rural cities of central and eastern provinces and providing lower land prices and property taxes in the metropolitan cities of Turkey can help mitigate some of the divergence in the house prices across cities.Originality/valueThe novelty of this study lies in employing a new data set at the city level containing 55 cities in Turkey, which is by far the largest in terms of city coverage among emerging market economies to implement the log t-test. It also contributes to the literature on city-specific determinants of convergence club formation in the case of an emerging economy.

Macroeconomic drivers of London house prices

2018 ◽  
Vol 36 (6) ◽  
pp. 539-551 ◽  
Author(s):  
Petros Stavrou Sivitanides
Keyword(s):  
Error Correction ◽  
House Prices ◽  
House Price ◽  
Policy Implications ◽  
Empirical Literature ◽  
Annual Data ◽  
Price Inflation ◽  
Partial Adjustment ◽  
Content Type

Purpose The purpose of this paper is to validate and quantify the effect of key macroeconomic drivers on London house prices using annual data over the period 1983–2016. Design/methodology/approach Within this context, the authors estimate alternative error-correction and partial-adjustment models (PAMs), which have been widely used in the empirical literature in modelling the slow adjustments of house prices to demand and supply shocks. Findings The results verify the existence of a strong long-term relationship between London house prices and key macroeconomic variables, such as UK GDP, London population and housing completions. A key finding of the study relevant to the debate on the causes of the housing affordability crisis is that the results provide little evidence in support of the argument that user demand, which is captured in the author’s model by Greater London population, may have had a diminished role in driving house price inflation in London. Practical implications The practical and policy implications of the results are that increased homebuilding activity in London will undoubtedly help limit house price increases. Also, any potential reduction of immigration and economic growth due to Brexit will also have a similar effect. Originality/value The originality of this research lies in the use of annual data that may better capture the long-term effect of macroeconomic drivers on house prices and the estimation of such effects through both error-correction and partial-adjustment models.

scholarly journals The sources of house price change: identifying liquidity shocks to the housing market

2016 ◽  
Vol 9 (1) ◽  
pp. 98-120 ◽  
Author(s):  
Paloma Taltavull de La Paz ◽  
Michael White
Keyword(s):  
Monetary Policy ◽  
Housing Market ◽  
Error Correction ◽  
House Prices ◽  
Price Change ◽  
Housing Prices ◽  
House Price ◽  
Content Type ◽  
The Uk

Purpose The purpose of this paper is to examine the role of monetary liquidity in house price evolution through examining the Asset (housing) Inflation channel. It identifies the main channels of transmission affecting house prices from monetary supply channels to house price change, examining how the Asset Price channel transmits changes in M1 to housing prices in Spain and the UK. Design/methodology/approach The paper uses Vector Auto Regression (VAR) and Error Correction models to test the Asset Inflation channel in the UK and Spain from 1991 to 2013 in two steps. In the first step, the supply elasticity is estimated through the long-term relationship between house prices and stock supply. The second step estimates a Vector Error Correction (VEC) to explain house price dynamics conditioned on supply reactions. The latter is defined as a long-term inverse demand model where housing prices are controlled by fundamentals in each market. Models allow forecast testing using Choleski impulse responses methodology. Findings Several results are found. In the supply model, both countries show rapid convergence to equilibrium with a larger elasticity of supply in Spain than in the UK but with a short run effect of new supply on prices in the UK. Regarding the Asset Inflation Channel model, the paper finds evidence of the existence of a housing accelerator effect in Spain, but not in the UK where changes in liquidity fully impact house prices in one direction. Research limitations/implications Implications of findings are mainly to forecast the effects of Monetary Policy measures in different economies. Practical implications The model supports the evaluation of different impacts of monetary policy in territories. It shows that the same policy will have different impacts in different housing markets and therefore highlights the importance of examining each market separately to identify the appropriate policy interventions. Originality/value This is the first paper that estimates the impact of the Asset Inflation Channel on house prices that endogenises housing market conditions and compares effects and interrelationships in two different economies.

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.

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