AN ANALYSIS OF INFLATION HEDGING AGAINST SINGAPORE AND HONG KONG COMMERCIAL PROPERTIES

Abstract

This study examines whether office and shop in Singapore and Hong Kong can hedge against inflation in the long run. The quarterly data of office price index, shop price index and consumer price index are used in order to compare the inflation-hedging characteristics of office and shop return in Singapore and Hong Kong for a period of 23 years and 18 years. Comparative performance analysis and correlation analysis is undertaken to study the relationship between office and shop returns with inflation to form a historical review. Further empirical studies are carried out using cointigration techniques to test for the existence of any long-run equilibrium relationship between office and inflation, shop and inflation in the two respective countries. Followed by Granger causality tests to explore the causal relationship and the contemporaneous or lead-lag relationship between changes in office prices and inflation changes in shop prices and inflation in these two countries. The study concludes that there is a long run relationship between Singapore office prices and inflation, Singapore shop prices and inflation. However, the existence of a long run relationship is not very convincing. As for Hong Kong, no cointegration is found for office prices and inflation, shop prices and inflation. Implying that there is a lack of consistent relationship with inflation (insignificant relationship exist) Further Granger causality tests can only reject the null hypothesis of no causality from change in Singapore office prices to inflation and change in Singapore shop prices to inflation throughout the studied period. Implying that there is unidirectional causality for Singapore office price and inflation growth, Singapore shop price and inflation growth. As for Hong Kong, independence are suggested when the sets of change in office prices and inflation, changes in shop prices and inflation coefficients are not statistically significant in the four regressions.