AN EMPIRICAL STUDY ON THE RELATIONSHIP BETWEEN BUSINESS AND PROPERTY CYCLES OF SINGAPORE

Abstract

The primary interest of this study is to examine the correlation between real estate and business cycles of Singapore. Through the application of informal turning points and spectral analyses, the significant periodic components of business and property cycles are discovered. Subsequently, the correlation between the business cycle and the cycles of various property segments are inspected via the informal lead-lag linkages and cross-spectral analyses (coherency, cross-amplitude and phase spectrum). The informal turning points and spectral analyses produce a similar estimation of major cycle’s length around six years for the business cycle while the property cycles’ lengths are around six to eight years. An informal point-to-point (trough-peak-trough) analysis reveals that GDP generally leads property cycles. An exception to the aggregated and low-density private residential properties shows that the GDP leads at the point to bottom up, lags to peak, followed by leads to dip again by the end of a cycle. The general observations are confirmed by the cross-spectral analysis. Specifically, the coherency test shows that the aggregated and segregated GDP-Residential and GDP-Industrial exert moderate to strong correlation at most frequency bands. Although the aggregated GDP-Office and GDP-Retail have comparatively weak correlations, the central area GDP-Office and GDP-Retail are found to have stronger correlations than their counterparts in the fringe areas. Lastly, the phase spectra substantiate the informal turning point analysis by showing that GDP leads property market at the major cycle of reference cycle in general. The duration of phase difference ranges from 2.2 quarters to 6.2 quarters. However, the phase shifts are noted to be established only if it is accompanied by strong correlation between two markets. ii Results from the study would assist investors to comprehend cyclical behaviours of property markets to time each investment better with reference to the general economic conditions. This allows the property investors to make informed decisions thereby maximizing the overall profits of an investment. Keywords: Property cycle, Business cycle, Spectral analysis, Cross-spectral analysis