scholarly journals Does immigration affect residential real estate prices? Evidence from Australia

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Narvada Gopy-Ramdhany ◽  
Boopen Seetanah
Keyword(s):  
Real Estate ◽  
Housing Prices ◽  
Past Research ◽  
Housing Demand ◽  
Interstate Migration ◽  
Causality Analysis ◽  
Residential Real Estate ◽  
Content Type ◽  
Long Run ◽  
Real Estate Prices

Purpose This study aims to investigate the effect of immigration on housing prices in Australia both at the national and regional levels. Design/methodology/approach Data for eight Australian states on a quarterly basis from 2004–2017 is used. To study the possible dynamic and endogenous relationship between housing prices and immigration, a panel vector autoregressive error correction model (PVECM) is adopted. Findings Analysis of the results indicates that in the short run immigration positively and significantly affects housing prices, whereas in the long run no significant relationship was observed between the two variables. From the regional breakdown and analysis, it is discerned that in some states there is a significant and positive effect of immigration on residential real estate prices in the long run. Causality analysis confirms that the direction of causation is from immigration to housing prices. Practical implications The study illustrates that immigration and interstate migration, as well as high salaries, have been causing a rise in housing demand and subsequently housing prices. To monitor exceedingly high housing prices, local authorities should be controlling migration and salary levels. Originality/value Past research studies had highlighted the importance of native interstate migration in explaining the nexus between immigration – housing prices. In this study, it has been empirically verified how immigration has been affecting the locational decisions of natives and subsequently how this has been affecting housing prices.

scholarly journals Does Immigration Affect Residential Real Estate Prices? Evidence From Australia

2020 ◽  
Author(s):  
Narvada Gopy-Ramdhany ◽  
Boopen SEETANAH
Keyword(s):  
Real Estate ◽  
Housing Prices ◽  
Housing Demand ◽  
Population Increase ◽  
Residential Real Estate ◽  
Vector Autoregressive ◽  
Long Run ◽  
Short Run ◽  
Real Estate Prices ◽  
Using Data

Abstract Worldwide migration flows have been gaining momentum over the past years, leading to population increases in some countries. Consequently, the population increase might have led to more housing demand in the host country. This study investigates the effect of immigration on housing prices in Australia by using data for eight states on a quarterly basis from 2004 – 2017. To study the possible dynamic and endogenous relationship between housing prices and immigration, a panel vector autoregressive error correction approach (PVECM) is adopted. Analysis of the results indicates that in the short run immigration positively and significantly affects housing prices, whereas in the long run no significant relationship was observed. From the regional breakdown and analysis, it is discerned that in some states there is significant and positive effect of immigration on residential real estate prices in the long run. Interestingly, analysis of reverse causation indicates that housing prices affect migration in a negative and significant way.

Real effects of real estate: evidence from unemployment rates

2020 ◽  
Vol 37 (4) ◽  
pp. 605-623
Author(s):  
Can Dogan ◽  
John Can Topuz
Keyword(s):  
Real Estate ◽  
Housing Prices ◽  
Real Economy ◽  
Residential Real Estate ◽  
Content Type ◽  
Unemployment Rates ◽  
The Real ◽  
Real Estate Price ◽  
Real Effects ◽  
Real Estate Prices

Purpose This paper aims to investigate the relationship between residential real estate prices and unemployment rates at the Metropolitan Statistical Area (MSA) level. Design/methodology/approach This paper uses a long time-series of MSA-level quarterly data from 1990 to 2018. It uses an instrumental variable approach to estimate the effects of residential real estate prices on unemployment rates using the geography-based land constraints measure of Saiz (2010) as the instrument. Findings The results show that changes in residential real estate prices do not have a causal effect on unemployment rates in the same quarter. However, it takes 9-12 months for an increase (decrease) in real estate prices to decrease (increase) unemployment rates. This effect is significant during both pre- and post-financial crisis periods and robust to control for the economic characteristics of MSAs. Research limitations/implications This paper contributes to the emerging literature that studies the real effects of real estate. Particularly, the methodology and the findings can be used to investigate causal relationships between housing prices and small business development or economic growth. The findings are also of interest to policymakers and practitioners as they illustrate how and when real estate price shocks propagate to the real economy through unemployment rates. Practical implications This study’s findings have important implications for academics, policymakers and investors as they provide evidence of a snowball effect associated with shocks to real estate prices: increasing (decreasing) unemployment rates following a decrease (increase) in real estate prices exacerbates the real estate price movements and their economic consequences. Originality/value This paper analyzes a significantly longer period, from 1990 to 2018, than the existing literature. Additionally, it uses the MSA-level land unavailability measure of Saiz (2010) as an instrument to explore the effects of residential real estate prices on unemployment rates and when those effects are observed in the real economy.

House price index (HPI) and Covid-19 pandemic shocks: evidence from Turkey and Kazakhstan

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Yeşim Aliefendioğlu ◽  
Harun Tanrivermis ◽  
Monsurat Ayojimi Salami
Keyword(s):  
Real Estate ◽  
Price Index ◽  
Housing Prices ◽  
House Price ◽  
Monthly Basis ◽  
Data Set ◽  
House Price Index ◽  
Content Type ◽  
Asymmetric Pricing ◽  
Long Run

Purpose This paper aims to investigate asymmetric pricing behaviour and impact of coronavirus (Covid-19) pandemic shocks on house price index (HPI) of Turkey and Kazakhstan. Design/methodology/approach Monthly HPIs and consumer price index (CPI) data ranges from 2010M1 to 2020M5 are used. This study uses a nonlinear autoregressive distributed lag model for empirical analysis. Findings The findings of this study reveal that the Covid-19 pandemic exerted both long-run and short-run asymmetric relationship on HPI of Turkey while in Kazakhstan, the long-run impact of Covid-19 pandemic shock is symmetrical long-run positive effect is similar in both HPI markets. Research limitations/implications The main limitations of this study are the study scope and data set due to data constraint. Several other macroeconomic variables may affect housing prices; however, variables used in this study satisfy the focus of this study in the presence of data constraint. HPI and CPI variables were made available on monthly basis for a considerably longer period which guaranteed the ranges of data set used in this study. Practical implications Despite the limitation, this study provides necessary information for authorities and prospective investors in HPI to make a sound investment decision. Originality/value This is the first study that rigorously and simultaneously examines the pricing behaviour of Turkey and Kazakhstan HPIs in relation to the Covid-19 pandemic shocks at the regional level. HPI of Kazakhstan is recognized in the global real estate transparency index but the study is rare. The study contributes to regional studies on housing price by bridging this gap in the real estate literature.

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.

The user cost of housing in the Baltic states

2017 ◽  
Vol 10 (1) ◽  
pp. 17-34
Author(s):  
Darius Kulikauskas
Keyword(s):  
Real Estate ◽  
Interest Rates ◽  
Housing Prices ◽  
Residential Real Estate ◽  
Baltic States ◽  
Data Set ◽  
Content Type ◽  
Real Estate Markets ◽  
User Costs ◽  
The Baltic

Purpose This paper aims to use the user costs approach to identify the periods of over- and under-valuation in the Baltic residential real estate markets. Design/methodology/approach Three alternative estimates of the user costs of homeownership in the Baltics are computed: one that does not discriminate between the leveraged and unleveraged parts of a house and the other that takes loan-to-value ratios into account. Findings The approach successfully identifies the overheating that took place in the Baltic real estate markets prior to the crisis of 2009 and shows that there is significant upward pressure for the housing prices in the Baltics in the low interest rate environment that became prevalent ever since. Research limitations/implications The paper uses only the current values of the fundamentals to compute the user costs. The framework could be augmented to account for the expected future developments of the fundamentals. Practical implications The macroprudential policy makers should monitor the developments in the Baltic residential real estate markets closely and be ready to act because an increase in the price-to-rent ratios might seem sustainable, given the current low interest rates, but could potentially bring harmful volatility when the monetary policy normalises. Originality/value This paper builds a novel data set on the real estate markets of the Baltic countries and is the first to derive the user costs of homeownership in the region. It is also among the first to identify periods of housing price misalignments from their fundamental values in the Baltic States.

scholarly journals Effects Of Exchange Rate Volatility On Real Estate Prices In Developing Economies, A Case Of Ghana

2019 ◽  
Vol 6 (11) ◽  
pp. 268-287
Author(s):  
John Kwame Adu Jack ◽  
Frimpong Okyere ◽  
Emmanuel K. S. Amoah
Keyword(s):  
Exchange Rate ◽  
Real Estate ◽  
Developing Economies ◽  
Negative Impact ◽  
House Prices ◽  
Housing Prices ◽  
Exchange Rate Volatility ◽  
Bounds Testing ◽  
Long Run ◽  
Real Estate Prices

This study aims to find out whether exchange rate volatility affects real estate domestic house prices in Ghana. To this end, a 32 years secondary data from World Development Indicators (WDI) and data from Real Estate Developers in Ghana are employed for the study. The study employs Autoregressive distributed lags (ARDL) bounds testing of cointegration t o test the null hypothesis that exchange rate volatility has n o impact on real estate housing prices. The study finds that real estate price is cointegrated with remittances, exchange rate and inflation. The long run equilibrium is stable and significant. Exchange rates d o not cause changes in real estate prices in both short and long run. Similarly past prices of real estate d o not have impact on current house prices.  Rather, remittances positively cause real estate prices. Inflation on its part has a negative impact on real estate prices. It is therefore concluded that, volatility in the exchange rate between the cedi and other trading currencies does not predict changes in real estate prices.

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.

Real estate prices and stock market in Germany: analysis based on hedonic price index

2019 ◽  
Vol 12 (4) ◽  
pp. 687-707 ◽  
Author(s):  
Korhan Gokmenoglu ◽  
Siamand Hesami
Keyword(s):  
Real Estate ◽  
Stock Market ◽  
Stock Prices ◽  
Price Index ◽  
Real Estate Market ◽  
Hedonic Price ◽  
Content Type ◽  
Long Run ◽  
Real Estate Prices ◽  
The Relationship

PurposeReal estate and stocks are two major asset types in an investor’s portfolio. Therefore, this paper aims to investigate the relationship between these two markets to provide a valuable insight into the process of portfolio optimization and security selection.Design/methodology/approachThis study examines the long-run relationship between residential real estate prices and stock market index in the case of Germany for the period of 2005-2017 by applying time series econometrics techniques. To this aim, this study uses Hedonic House Price Index as a proxy for real estate prices and DAX30 as a proxy for stock prices. Moreover, three additional variables, namely, consumer confidence, credit availability and supply of mortgage loans, are incorporated as control variables to assess the robustness of the results.FindingsObtained empirical results indicate a long-run relationship between stock prices and real estate prices which suggests that in long-run, there is no diversification benefit from allocating stock and real estate assets in a portfolio. This finding is especially important for long-term investors such as pension funds.Originality/valueTo the authors’ best knowledge, this is the first study that empirically investigates the relationship between the real estate market and stock prices using the Hedonic Price Index for the case of Germany.

Non-mortgage loans in the Chinese residential real estate market

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Kerry Liu
Keyword(s):  
Real Estate ◽  
Real Estate Market ◽  
Cointegration Analysis ◽  
Residential Real Estate ◽  
Mortgage Loans ◽  
Data Set ◽  
Monthly Data ◽  
Content Type ◽  
Real Estate Prices

Purpose From January 2021, the potential flow of Chinese household non-mortgage loans, including business loans and short-term consumption loans to the residential real estate market, has attracted the attention of the regulatory authorities. This study aims to examine the effects of household non-mortgage loans on the Chinese residential real estate market. Design/methodology/approach Based on a monthly data set between July 2011 and December 2019, this study adopts a cointegration analysis. Findings This study finds that household non-mortgage loans do play a significant role in driving residential real estate prices in China. Originality/value While many studies have examined the Chinese real estate market and its linkage with the financial system and the economy, this study is the first of its kind in the academic literature that exclusively focusses on the role of non-mortgage loans in real estate prices, and makes an original contribution.

Short Sales and Residential Real Estate Prices

2013 ◽  
Author(s):  
Andrew Narwold ◽  
Stephen J. Conroy ◽  
Dirk Yandell
Keyword(s):  
Real Estate ◽  
Short Sales ◽  
Residential Real Estate ◽  
Real Estate Prices
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