Residential Property Price Index Research Articles

The VECM implementation for measuring the impact of monetary variables on Indonesia Property Prices Index

The basic human need for housing makes property investment safer than other sectors because demand tends to be stable despite changing economic conditions. The decision to invest is influenced by various aspects, including economic variables, including GDP, property credit growth, non-performing loans (NPLs), interest rates, exchange rates, and money supply, which are then examined for their influence on the Residential Property Price Index (RPPI) in Indonesia through this research using a Vector Error Correction Model (VECM) with quarterly data from 2003 to 2022. The findings show that GDP, interest rates, and money supply have a significant long-term impact on the RPPI. In the short-term, GDP and property credit growth have a negative impact on RPPI, while NPL and exchange rate do not. Causality tests indicate a bidirectional relationship between NPL and GDP with RPPI, with probability values exceeding 0.05. This study provides valuable insights into the monetary factors affecting residential property prices and suggestions for future research. AcknowledgmentThe authors gratefully acknowledge Ahmad Dahlan University for the support and facilities provided in conducting this research. They also greatly appreciate the academic resources that supported the data collection process and careful analysis of our findings. Besides, the authors express their gratitude to Bank Indonesia and Badan Pusat Statistik for their invaluable contribution to the data used in this research.

Analysis of the Influence of Domestic Products, Loan Interest Rates, and Residential Property Price Index on Home Ownership Credit Distribution in Indonesia for the Period 2015:TW.I – 2023:TW.III

This research examines the relationship between Gross Domestic Product (GDP), interest rates and house prices on mortgages in Indonesia. Using the dynamic ECM Domowitz-Elbadawi method, this research explores the short and long term relationships between these variables. House prices are measured using the composite Residential Property Price Index in the primary market. The research results show that GDP has a positive and significant effect on mortgage distribution in the short term. On the other hand, in the long term, both interest rates and house prices have a negative and significant influence on mortgage distribution. These findings are valuable for strategic decision making in property investment and policy formulation, suggesting that increasing GDP can boost mortgage distribution, while managing interest rates and house prices is important for long-term stability.

Home Ownership Dynamics: Analysis of The Impact of Gold, Bonds and Stocks on Property Investment Moderated by Loan Interest Rates

The purpose of this study is to examine how shares, bonds, and gold affect real estate investment, which is influenced by loan interest rates. In this study, the data type used is quantitative. Secondary data in the form of residential property price index data, bonds, stocks, loan interest rates and gold prices were sourced from Bank Indonesia. On a monthly basis, sampling employed a time series data method. Multiple linear regression is the data analysis technique employed in this study, which makes use of the E-views software. The study's findings indicate that gold has little bearing on real estate investments. Bonds have an impact on real estate investing. This demonstrates how interest rates or the inclination to invest in real estate can be impacted by an increase in bonds. Increase in shares can influence the interest or tendency to invest in property. Loan interest rates cannot moderate the influence of gold on property investment. Loan interest rates can moderate the effect of bonds on property investment. The results of this research show that there is a negative correlation, meaning that loan interest rates can weaken the influence of bonds on property investment. Loan interest rates can moderate the influence of shares on property investment. The results of this research show that there is a negative correlation, meaning that loan interest rates can weaken the influence of shares on property investment.

Pengaruh Harga Properti Residensial terhadap Proporsi Kredit Pemilikan Rumah pada Portofolio Kredit di Indonesia

This research aims to analyze the effect of the Residential Property Price Index (RPPI) on the composition of Home Ownership Credit (KPR) in the banking credit portfolio in Indonesia. The study was conducted using secondary data from the period of 2010 to 2022 from various sources such as Bank Indonesia and the Central Bureau of Statistics. Using the time-series regression, the research indicated that RPPI insignificant effected the composition of KPR in the banking credit portfolio in Indonesia. However, inflation rate and interest rates have a significant impact on the proportion of KPR. For credit regulator, this study can add perspectives on the impact of RPPI changes on credit portfolio composition.

A Comparison of Home Purchase and Liquid Lazy Portfolio Returns in Turkey

This study presents a comprehensive comparison between the effectiveness of home purchase and liquid Lazy portfolio strategies for generating historical returns in the Turkish market. The primary aim is to develop a liquid Lazy portfolio that outperforms residential property investments. The study covers the period from January 2010 to June 2023, focusing on high-liquidity assets including the Borsa Istanbul 100 Index, currency exchange rates, gold prices, real estate investment trusts, and major stock market indices. Methodologically, the research involves data pre-processing, logarithmic transformations, and cumulative time series creation. Portfolio optimization centers around maximizing the Sharpe ratio with three test portfolios developed. Findings indicate that all portfolios consistently outperform the benchmark Residential Property Price Index, displaying higher returns and Sharpe ratios despite increased volatility. These insights are relevant for both academic researchers and investors seeking practical applications for portfolio management. It's important to note that historical performance offers insights but not future guarantees. In conclusion, the study highlights the potential benefits of constructing scalable, liquid, and high-return Lazy portfolios as alternatives to traditional home purchases

Rupiah exchange rate: the determinants and impact of shocks on the economy

The repetition of policy dynamics on Quantitative Easing (QE) and interest rate by The Fed potentially cause fluctuations in the exchange rate, including in Indonesia. Therefore, this study aims to analyze the determinants and impacts of exchange rate shocks. Inflation (INF), Money Supply (LJUB), Open Market Operations (OPT), Foreign Exchange Reserves (LCD), Expected Inflation (LEHU) and Interest Rates (SB) were used to analyze the determinants of Exchange Rate (NT) through Auto Regressive Distributed Lag (ARDL). The impact of NT shocks was analyzed using Vector Auto Regressive (VAR) by LEHU, Residential Property Price Index (PIHPR), Stock Transactions (LTRANS), and Banking Credit Volume (VK). The Expected Inflation variable and incorporation of ARDL-VAR are novelties in this study. In the secondary time series data for 2014M1 – 2022M9 period, the ARDL results showed that INF and LJUB had positive effect on NT in both long and short run, while OPT, LCD and SB had negative effect. LEHU had negative effect in the short run, but positive in the long run. The speed of adjustment in the model was 49.86% per month. Shock of NT had impacted VK until 15 months, PIHPR at 7 months, LTRANS at 10 months, and LEHU at 14 months. Based on these results, it can be implied that the monetary authority must maintain stability of NT, especially by INF and LJUB transmission. Next, shock's impact must also be overcome, especially on VK. This research is only focused on monetary sector, further research will be refined with other macroeconomic variables.

Measuring the response of the property price index to monetary policy shock: Evidence from emerging market economies

This study examined the response of the residential property price index (RPPI) to monetary policy shocks. The analysis utilized a panel vector autoregressive (VAR) estimation covering the markets of 12 emerging countries over a quarterly period from 2000 Q1 to 2022 Q4. In a dynamic data model, the panel VAR estimation could be biased when the coefficients of the endogenous variables differ across countries. The results of the pooling assumption showed that the models contain heterogeneity among samples, indicating the need for a solution to address this problem. Consequently, a mean group estimation for the panel VAR was performed to resolve the heterogeneity issue. The residential property price index negatively responded to changes in housing loan (HL) and central bank (CB) interest rates. In contrast, it positively responded to changes in inflation, gross domestic product, and population. This research provided policymakers with recommendations on emerging market demand. To successfully interfere in the property market, policymakers must pay greater attention to formulating monetary policy, notably central bank interest rates. A steady central bank policy rate prevents growth in the property sector. Future research should include macroprudential policy as an endogenous component in the model.

THE DISTRIBUTION OF HOME MORTGAGES BY COMMERCIAL BANKS, ISLAMIC BANKS, AND RURAL BANKS DURING THE COVID-19 PANDEMIC

This research aimed to examine the distribution of home mortgages by various banks, i.e., commercial banks, Islamic banks, and rural banks during the 2-year Covid-19 pandemic in Indonesia. This study used panel data as the analysis method and the variables consisted of Residential Property Price Index (RPPI) and interest rates. The regression results showed that RPPI had a positive but not significant effect on the distribution of home mortgages during the pandemic. From the regression results, it is found that IHPR has an insignificant effect on KPR distribution during the pandemic. That is, when property prices increase, it will not affect the distribution of mortgages provided by commercial banks, Islamic banks and rural banks. Loan interest rates also have no significant effect on mortgage distribution during the pandemic. This implies that when the loan interest rate increases, it does not affect the distribution of mortgages provided. However, the increase in mortgage distribution during the Covid-19 pandemic is due to government efforts through subsidized mortgage policies such as Loan to Value (easing credit limits), VAT exemption incentives and expanding these policies not only in banks but also to rural banks.

House price indexes: an empirical exercise using spatial data analysis.

The housing market occupies a central place within any society. Residential property represents the essential parts of most families’ wealth, as well as a substantial part of their monthly expenditure. It also represents a large fraction of private investment, generating significant earnings. However, and despite this importance, the compilation of reliable residential property price indexes (RPPI) is far from satisfactory in Portugal, revealing an important gap in the field of statistical information. The construction of a residential property price index (RPPI) poses particular problems arising from the inherent nature of the object concerned. Considering the gap in Portugal regarding the lack of a sufficiently enlarged database allowing the compilation of reliable RPPIs, this article seeks to contribute to this area, proposing a methodology applied to the urban area of Aveiro and Ílhavo by means of a spatial data analysis.

On the Dynamic Relationship between the Housing Market, Stock Market, and Macroeconomic Variables in Hong Kong

The relationship between the housing market, stock market, and macroeconomic variables has long been a topic of concern to both academics and practitioners. This paper examines the short-run dynamics and long-run relationships between the residential property price index and the stock market index and four selected macroeconomic variables in Hong Kong. The Johansen (1991) cointegration approach and the Vector Error Correction Model (VECM) approach are used to examine the monthly time series during the sample period from 2004 to 2019. Our results show that there is a cointegration relationship between the residential property price index and the stock market index and selected macroeconomic variables. There is evidence that the Hang Seng index, money supply (M3), total loans, and unemployment rate are significantly associated with the residential property price index, while the consumer price index has no significant impact on the residential property price index in the short-run dynamics. Also, only the Hang Seng index and two macroeconomic variables have a long-run cointegration relationship with the housing market. This is the first attempt to shed light on both short-run and long-run relationships between two capital markets and macroeconomic variables in the context of Hong Kong. Our findings provide important implications for relevant government departments to stabilise the housing market and help practitioners form effective investment strategies.

Analisis Mekanisme Transmisi Kebijakan Moneter Melalui Saluran Harga Aset Pada Sektor Riil

The purpose of this study is to see how the variable response of the monetary policy transmission mechanism of the asset price channel in the real sector when there is a change in each variable and to see the contribution of the SBK, rPUAB, rKREDIT, IHPR, INV, OG, and INF variables to the final target. monetary policy reflected in inflation. The analytical method used is the Vector Error Correction Model (VECM) with the analysis of Impulse Responses (IR) and Variance Decomposition (VD). The results of the impulse response analysis show that the policy interest rate, interbank interest rate, credit interest rate, IHPR, investment and output gap variables quickly respond to the shock that occurs in each variable at the beginning of the period. The results of the analysis of variance decomposition in model 1 show that apart from the INF variable itself, each variable has a different contribution to the level of INF with the order of the greatest influence being the output gap (OG), IHPR, and INV. For further researchers, it is hoped that they will be able to do further research on the Residential Property Price Index (IHPR), especially the factors that influence it other than credit interest rates.

Predicting House Prices Using DMA Method: Evidence from Turkey

The aim of this study is to analyze the dynamics of the housing market in Turkey’s economy and to examine the impact of variables related to housing prices. Preferred by many international housing investors, Turkey hosts profitable real estate investments as one of the developing countries with a shining housing market. This study applies the dynamic model averaging (DMA) methodology to predict monthly house price growth. With the increasing use of information technologies, Google online searches are incorporated into the study. For this purpose, twelve independent variables, with the Residential Property Price Index as the dependent variable, were used in the period January 2010–December 2019. According to the analysis results, it was observed that some variables, such as bond yields, the level of mortgages, foreign direct investments, unemployment, industrial production, exchange rates, and Google Trends index, are determinants of the Residential Property Price Index.

Economic Development through Mortgage Loan Distribution in Indonesia

The growing population of Indonesia is increasing every year, which also leads to the growing need for people's residences. Of course, this affects the financial sector in terms of mortgage loans. Therefore, this paper is a study of the factors that affect the distribution of mortgage loans in Indonesia. This study uses multiple linear regression with ordinary least square analysis with the variables Residential Property Price Index, Lending Rate Credit, and Gross Domestic Product as the independent variable (X) and distribution of mortgages as the dependent variable (Y). The data used in this study are the quarterly time series from 2009 to 2021. Based on the results, the variables Residential Property Price Index, Lending Rate Credit, and Gross Domestic Product have a significant influence on mortgage loan distribution in Indonesia. So, the hope is that the government and the banks can wisely set Lending Rate Credit based on the Gross Domestic Product level of their territory.

Housing prices in emerging countries during COVID-19: evidence from Turkey

PurposeBy considering the rapid and continuous increase of housing prices in Turkey recently, this study aims to examine the determinants of the residential property price index (RPPI). In this context, a total of 12 explanatory (3 macroeconomic, 8 markets and 1 pandemic) variables are included in the analysis. Moreover, the residential property price index for new dwellings (NRPPI) and the residential property price index for old dwellings (ORPPI) are considered for robustness checks.Design/methodology/approachA quantile regression (QR) model is used to examine the main determinants of RPPI in Turkey. A monthly time series data set for the period between January 2010 and October 2020 is included. Moreover, NRPPI and ORPPI are examined for robustness.FindingsPredictions for RPPI, NRPPI and ORPPI are carried out separately at the country (Turkey) level. The results show that market variables are more important than macroeconomic variables; the pandemic and rent have the highest effect on the indices; The effects of the explanatory variables on housing prices do not change much from low to high levels, the COVID-19 pandemic and weighted average cost of funding have a decreasing effect on indices while other variables have an increasing effect in low quantiles; the pandemic and monetary policy indicators have a negative and significant effect in low quantiles whereas they are not effective in high quantiles; the results for RPPI, NRPPI and ORPPI are consistent and robust.Research limitations/implicationsThe results of the study emphasize the importance of the pandemic, rent, monetary policy indicators and interest rates on the indices, respectively. On the other hand, focusing solely on Turkey and excluding global variables is the main limitation of this study. Therefore, the authors encourage researchers to work on other emerging countries by considering global variables. Hence, future studies may extend this study.Practical implicationsThe COVID-19 pandemic and market variables are determined as influential variables on housing prices in Turkey whereas macroeconomic variables are not effective, which does not mean that macroeconomic variables can be fully ignored. Hence, the main priority should be on focusing on market variables by also considering the development in macroeconomic variables.Social implicationsEmerging countries can make housing prices stable and affordable, which will increase homeownership. Hence, they can benefit from stability in housing markets.Originality/valueThe QR method is performed for the first time to examine housing prices in Turkey at the country level according to the existing literature. The results obtained from the QR analysis and policy implications can also be used by other emerging countries that would like to increase homeownership to provide better living conditions to citizens by making housing prices stable and keeping them under control. Hence, countries can control housing prices and stimulate housing affordability for citizens.

Determinant of Residential Property Price Index in Five Asian Emerging Market Countries: A Demand and Supply Approach

This study aims to analyze the factors influencing the Residential Property Price Index (RPPI) from the demand and supply sides in five Asian emerging market countries. The data used are semi-annual data from the first semester of 2009 until the second semester of 2019 because this study aims to denote the impact of RPPI toward the demand and supply indicators after the global crisis in 2008. The dependent variable of this study is the RPPI, while the independent variables include the number of workers, real interest rate, economic growth, and the Real Effective Exchange Rate (REER). The Fixed Effects Model (FEM) is thus the applied method to process the data. In the end, the results indicate that all independent variables are significant toward the RPPI. The number of workers, real interest rate, and REER negatively affect the RPPI, while economic growth positively affects the RPPI.

PENGARUH HARGA PROPERTI RESIDENSIAL DAN KEBIJAKAN FINANCING TO VALUE TERHADAP STABILITAS PERBANKAN SYARIAH DI INDONESIA

This study aims to analyze the effect of residential property prices and Financing to Value policies on the stability of Islamic Commercial Banks in Indonesia. This study uses secondary data, namely time series data from all Islamic Commercial Banks in Indonesia during the period March 2010 to December 2020. The model used in this study is the Error Correction Model (ECM). The results of the study found that the Residential Property Price Index of small and medium types in the long term has an influence on the stability of Islamic Commercial Banks. However, each of them supports a different hypothesis, namely the collateral value hypothesis and the deviation hypothesis. Meanwhile, it was found that in the long and short term the Financing to Value policy had an influence on the stability of Islamic Commercial Banks in Indonesia.
 Keywords: Islamic Banking Stability, Property Price, Financing to Value

Analysis of Residential Property Price Index (RPPI) Using Multi Input Transfer Function

Residential property or home is one of the basic human needs as a shelter, to be able to continue to live. As the population in Indonesia increases, express the need for residential property will also increase. The movement of residential property prices in Indonesia can be observed from the Residential Property Price Index (RPPI) issued by Bank Indonesia. Residential property prices can be influenced by several factors. For example in economic, the movement of RPPI can be influenced by several factors such as inflation, Composite Stock Price Index (RPPI) and loan interest rates. Forecasting the RPPI can be done with times series modeling. Modeling RPPI using three influencing variables requires a multivariate time series model. The multi-input transfer function model is a multivariate model that can be used in modeling RPPI. In the multi-input transfer function model there is an output series (y t ) which is the RPPI which is estimated to be influenced by several input series (x jt ), which are inflation, IHSG and loan interest rates. Based on the model obtained in this study, it can be seen that the prediction of RPPI at the t-time is influenced by the amount of inflation in the previous two months until previous five months, influence by loan interest rates without delay so that it is influenced by the t-time until previous three months, influenced by the IHSG at t-time until previous four months, and also influenced by itself at one month before to four months before.

Türkiye Konut Piyasasında Zayıf Formda Etkinlik Analizi: Makroekonomik Bakış

The aim of this study is to look for an answer to the question of “Is it possible to discuss the existence of an efficient market for the housing market in Turkey?”. It was observed that relatively low housing (mortgage) interest rates were accompanied by price rigidity. Accordingly, in the formation of the housing market definition from the Central Bank (CBRT) database; an empirical analysis was made using the Residential Property Price Index for New Dwellings (NRPPI), the Residential Property Price Index for Existing Dwellings (ERPPI), the Residential Property Price Index (RPPI) and the Hedonic House Price Index (HHPI). The data range for the first three indices is between 1/2010 and 1/2020. Hedonic housing price index data range is between 1/2011 and 1/2020. Unit root tests were used to test the Random Walk Theory, which shows the characteristic condition of the housing market. The results from the study show that above average sustainable returns cannot be obtained from the housing market, as a result the market is poorly efficient. At the same time the housing market in Turkey, the rigidity of prices found along with excess supply situation is worrisome. Therefore, it is necessary to prevent all kinds of manipulative news that may occur in the housing market by the regulatory and supervisory institutions.

FINANCING-TO-VALUE (FTV) POLICY AND ITS IMPACT ON RESIDENTIAL PROPERTY PRICES IN INDONESIA

Financing-to-value (FTV) policy is a macroprudential policy currently used by the central banks to maintain the stability of financial systems and prevent systemic risks. In Indonesia this is particularly the case in relation to financing of the property sector by Islamic financial institutions. This paper aims to analyse the impact of FTV policy on the residential property price index (RPPI) in Indonesia using a panel data analysis method. Indonesia is chosen in this study as it is one of the countries implementing FTV policy in its Islamic banking system. There are three important findings to be drawn from the study. First, FTV policy ratios significantly affect RPPI.

Bangladesh

The purpose of the mission was to assist the Bangladesh Bank (BB) in progressing on the compilation of a residential property price index (RPPI). This will be the first technical assistance (TA) mission to Bangladesh on the RPPI to be conducted under the auspices of the Data for Decisions Fund (D4D). The aim of the mission is to assist the BB in improving data for RPPI compilation and to compile an experimental RPPI.