Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/222261
Title: MACROECONOMIC FACTORS AND THE RENTAL HOUSING MARKET: EVIDENCE FROM SINGAPORE �S PRIVATE RESIDENTIAL SECTOR
Authors: YEO SHUN MING DARREN
Keywords: Real Estate
Cristian Badarinza
RE
2016/2017 RE
Cointegration
Error Correction Model
Private Residential
Rents
Issue Date: 3-May-2017
Citation: YEO SHUN MING DARREN (2017-05-03). MACROECONOMIC FACTORS AND THE RENTAL HOUSING MARKET: EVIDENCE FROM SINGAPORE �S PRIVATE RESIDENTIAL SECTOR. ScholarBank@NUS Repository.
Abstract: This paper probes the effects of economic fundamentals on the private residential market in Singapore, particularly on housing rents. Quarterly data from the period of Q1 1999 to Q4 2016 is collected for time series data analysis. The research objective is to examine if a long-run equilibrium relationship exists between macroeconomic variables of concern and private residential rents. The demand and supply drivers selected as explanatory variables comprise real Gross Domestic Product (GDP), mortgage interest rates (IR), inflation (CPI) and available housing stock (AS). Based on a cointegration Vector Error Correction Model (VECM) framework, the results present that private residential rents in Singapore are cointegrated with inflation, mortgage interest rates and the available housing stock in the long- run. The error correction mechanism is negatively signed and found to be statistically significant, correcting 90.8% of disequilibrium in one quarter. In the short run, lagged variable of inflation, available stock and change in rents are all statistically significant in explaining the change in current private residential rents. The estimation model for private residential rents is of good fit and able to explain 84.4% of the variation in the change in private residential rentals by the regressors.
URI: https://scholarbank.nus.edu.sg/handle/10635/222261
Appears in Collections:Bachelor's Theses

Show full item record
Files in This Item:
File Description SizeFormatAccess SettingsVersion 
Yeo Shun Ming Darren 2016-2017.pdf1.23 MBAdobe PDF

RESTRICTED

NoneLog In

Page view(s)

21
checked on Feb 2, 2023

Download(s)

9
checked on Feb 2, 2023

Google ScholarTM

Check


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.