Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
We use a matching procedure to construct three commercial real estate indices (office, shop and multiple-user factory) in Singapore using transaction sales from 1995Q1 to 2010Q4. The matching approach is less restrictive than the repeat sales estimator, which is restricted to properties sold at least twice during the sample period. The matching approach helps to overcome problems associated with thin markets and non-random sampling by pairing sales of similar but not necessarily identical properties across the control and treatment periods. We use the matched samples to estimate not just the mean changes in prices, but the full distribution of quality-adjusted sales prices over different target quantiles. The matched indices show three distinct cycles in commercial real estate markets in Singapore, including two booms in 1995–1996 and 2006–2011, and deep and prolonged recessions with declines in prices around the time from 1999 to 2005. We also use kernel density functions to illustrate the shift in the distribution of house prices across the two post-crisis periods in 1998 and 2008.