Modelling the Drivers of Housing Price using Autoregressive Distributed Lag – Error Correction Model (ARDL-ECM) in Indonesia - Bagaskara (Journal of Asset Management and Public Economy (JAMPE), 2023)
This study aims to design a model tand to estimate the effect of market fundamentals (macroeconomic drivers) on housing prices in Indonesia. The identification of macroeconomic drivers helps the government utilize these macroeconomic indicators to control housing prices in accordance with the current situation. Therefore, the contribution of this study is to analyse how is the housing price in Indonesia. The analytical tool used in this study is the Autoregressive Distributed Lag-Error Correction Model (ARDL-ECM). The variables used in this study are the residential housing price index, real loan interest rates, and the unemployment rate with the observation period starting in the first quarter of 2010 - fourth quarter of 2019. The process of establishing the ARDL-ECM was carried out through a series of tests on research data. Based on the ARDL-ECM estimation results, it was found that in the short-term real loan interest rates had a negative and significant effect on housing prices, while in the long-term real loan interest rates and unemployment rates had a negative and significant effect on housing prices. These results indicate that real interest rates and unemployment rates as macroeconomic drivers can affect housing prices so that they can be utilized by policy makers, specifically through monetary policy (interest rates) and fiscal policy (unemployment rate).