De-lagging Hong Kong's office price indices via State Space Model with Kalman filter

Purpose This paper aims to find out whether lagging problems exist within Hong Kong's office values. Design/methodology/approach A State Space Model with the Kalman filter is deployed in detecting the extent of lagging errors in Hong Kong's office price indices, proffered by the ratings and valuation department (RVD). Findings The findings suggest that about one year of lagging errors exists in RVD's office price indices compared with the stock market property indices. Also, the finding suggests that the Kalman filter provides a more efficient form of estimates for real estate values and returns. Originality/value While most studies investigating lagging problems of appraisal-based returns concentrate on the US real estate market, studies in this regard for Asian countries (or cities) are few and far between. Hong Kong, in particular, is worth studying, considering its established role as a financial centre in South East Asia. This paper also provides some insights for further studies on the prediction of future real estate values, in particular those with fewer transactions.