scholarly journals A Study on the Interrelationship among Interest Rate, Housing Consumer Sentiment and Housing Market Using SVAR Model

2017 ◽  
Vol 95 (null) ◽  
pp. 3-20
Author(s):  
최윤영 ◽  
Cho Gyeongcheol ◽  
김지현
Keyword(s):  
Interest Rate ◽  
Housing Market ◽  
Consumer Sentiment ◽  
Svar Model

scholarly journals Analysis of Housing Market Dynamics Considering the Structural Characteristics of Mortgage Interest

2021 ◽  
Vol 13 (19) ◽  
pp. 10523
Author(s):  
Insoo Baek ◽  
Sanghyo Lee ◽  
Joosung Lee ◽  
Jaejun Kim
Keyword(s):  
Interest Rate ◽  
Interest Rates ◽  
Housing Market ◽  
Structural Characteristics ◽  
Housing Demand ◽  
Market Mechanism ◽  
Policy Implications ◽  
Mortgage Loan ◽  
Market Mechanisms ◽  
The Government

Mortgage loan interest rates consists of base interest and spread. In general, the base interest is adjusted by the government for the sustainability of the housing market. On the other hand, spread is determined by market mechanisms. Accordingly, the change pattern of base interest and spread may appear differently depending on the market situation. In the end, the effect of the government’s market intervention through interest rate policy may be different than expected. In this respect, the purpose of this paper is to analyze the effects of base interest and spread of the mortgage loan interest rate on the housing market and to derive important policy implications for the sustainability of the housing market. As a result of this study, the ineffectiveness of the government’s interest rate policies on the stability of the housing market was confirmed. The market mechanisms had more significant effects on the sustainability of the housing market than artificial political intervention. Further, housing supply policies based on the market mechanism could be more effective than housing demand policies based on interest-rate adjustments.

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.

scholarly journals LIBOR and interest rate spread: sensitivities of the Australian housing market

2019 ◽  
Vol 25 (1) ◽  
pp. 73-99 ◽  
Author(s):  
Martin Hinch ◽  
Michael McCord ◽  
Stanley McGreal
Keyword(s):  
Interest Rate ◽  
Housing Market ◽  
Interest Rate Spread

scholarly journals International Real Estate Review

2017 ◽  
Vol 20 (3) ◽  
pp. 375-396
Author(s):  
Gary Wai Chung Wong ◽  
◽  
Lok Sang Ho ◽  
Keyword(s):  
Interest Rate ◽  
Housing Market ◽  
Supply And Demand ◽  
Housing Prices ◽  
Housing Price ◽  
Price Expectations ◽  
Price Expectation ◽  
Long Run ◽  
Property Price ◽  
Explicit Consideration

This paper builds on the literature that shows policy often plays a key role in housing cycles. Using the cointegration approach which focuses on the supply and demand dynamics of the housing market, and with explicit consideration of housing price expectations proxied by the price-earning ratio in financial markets, this paper identifies two cointegrating relations: a long run demand-side relation that involves housing property price, interest rate, price expectation and income; and a supply-side relation that involves private housing completion, property price, interest rate, and building and land costs. Based on Hong Kong data from 1990 a£á¡§ 2012, which covers big cycles in the housing market, this paper suggests that policies to augment or restrain housing supply in the attempt to stabilize housing prices have been counterproductive.

Monetary policy and macroeconomic responses: non-recursive SVAR study of Egypt

2019 ◽  
Vol 11 (3) ◽  
pp. 319-337
Author(s):  
Mohamed Aseel Shokr ◽  
Zulkefly Abdul Karim ◽  
Mohd Azlan Shah Zaidi
Keyword(s):  
Monetary Policy ◽  
Exchange Rate ◽  
Interest Rate ◽  
Monetary Policy Shocks ◽  
Content Type ◽  
Macroeconomic Variables ◽  
Svar Model ◽  
Policy Shocks ◽  
Effect Of Monetary Policy ◽  
Foreign Shocks

Purpose This paper aims to examine the effects of monetary policy and foreign shocks on output, inflation and exchange rate in Egypt. Design/methodology/approach This paper studies the effects of monetary policy and foreign shocks on output, inflation and exchange rate by using non-recursive SVAR model and quarterly data. Findings First, the empirical results reveal that monetary policy shocks, through changes in interest rate or money supply, have a significant effect on output, inflation and exchange rate in Egypt. Second, the world oil prices and foreign output have significant impacts on output, inflation and exchange rate in Egypt, while foreign interest rate has a significant effect on domestic output and inflation. Research limitations/implications The limitation of the study is examining one country only. Practical implications The Central Bank of Egypt (CBE) should adjust interest rate to stabilize inflation, output and exchange rate. By stabilizing inflation, output and exchange rate, the CBE would be able to achieve the ultimate targets of monetary policy, namely, price stability and economic growth. Social implications It is important for the CBE because it shows the significant effect of monetary policy on macroeconomic variables in Egypt. Also, it is important for people because it shows the important role for the CBE. Originality/value It is important for the CBE because it examines the effect of monetary policy and foreign shocks on macroeconomic variables.

scholarly journals What Role Does the Housing Market Play for the Macroeconomic Transmission Mechanism?

2020 ◽  
Vol 13 (6) ◽  
pp. 112
Author(s):  
Mats Wilhelmsson
Keyword(s):  
Interest Rate ◽  
Housing Market ◽  
Housing Prices ◽  
Bank Lending ◽  
Transmission Mechanism ◽  
Bank Lending Channel ◽  
Lending Channel ◽  
The Interest Rate ◽  
The Impact ◽  
Over Time

The main objective is to answer the question: What role does the housing market play for the transmission mechanism and (in particular) is the impact constant over time? The research question also includes analyzing the importance of the housing market for the transmission mechanism. We estimate an eight-variable structural vector autoregression (SVAR) model of the Swedish economy over the period 1993 and 2018 using quarterly data, covering both the internet bubble in 2000 and the financial crises in 2008. The results indicate that interest rates have both a direct effect on housing prices and an indirect impact through the bank lending channel. Over time, the traditional interest rate channel importance has been stable. On the other hand, the role of the bank lending channel has increased over time. Household debt has increased substantially in Sweden and elsewhere. That means that the interest rate sensitivity in society has increased. Based on the results, it is possible to evaluate and forecast potential house price effects (both direct and indirect) when the interest rate changes.

HAS MONETARY POLICY CAUSED HOUSING PRICES TO RISE OR FALL IN CHINA?

2018 ◽  
pp. 1-18 ◽  
Author(s):  
XIAO-CUI YIN ◽  
CHI-WEI SU ◽  
RAN TAO
Keyword(s):  
Monetary Policy ◽  
Interest Rate ◽  
Housing Market ◽  
Money Supply ◽  
Asset Price ◽  
Housing Prices ◽  
User Cost ◽  
Rate System ◽  
Short Run ◽  
The Impact

This paper examines whether broader money supply (M2) and interest rate as two monetary policy tools may have differently affected housing prices in China. Empirical results show that there is a co-movement between housing prices and M2 in the short run and it becomes more pronounced after 2006 in the medium run. In addition, generally M2 positively affects housing prices. This supports the asset price channel which indicates that an easing monetary policy offers ample liquidity and results in raising the housing prices. The excess liquidity after 2008 spread to housing market, resulting in too much money chasing relatively few assets and triggering a surge in housing prices. On the other hand, we observe that co-movement between housing prices and interest rate is not very evident in most time. Moreover, we find that interest rate has a positive effect on housing prices which is not consistent with the user cost approach and indicates that a contracting monetary policy is not effective in curbing housing market. Not completely liberalized interest rate system and the high return on housing investments reduce the impact of interest rate on housing prices. These findings indicate that money supply is more effective than interest rate as channel to control the housing prices in China. The results are helpful for the scientific formulation of monetary policy for reasonable regulation of the market.

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