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This research suggests improvements to the macroeconomic housing
indices of a thin real estate market, such as that of Cyprus, by testing
various index construction methods with transaction-based data.
Authors employ around 80% of the total number of apartment transfers
documented at the Department of Lands and Surveys (DLS) of
Cyprus, spanning from the first quarter of 2015 to the second quarter
of 2022. They utilize this data to generate comprehensive indices
at both the national and district levels. Authors studied, analyzed,
and identified the deficiencies of the DLS database and tested the
sample with six different methods. Log-linear time dummy hedonic
models were found to explain the variation of prices better than
other methods, mainly due to their ability to handle the diversity of
properties in terms of location and physical characteristics and proposed
techniques to deal with the issues of the standard time
dummy (STD) and rolling time dummy (RTD) methods, regarding
index revisions and low transaction volume during periods of downturns,
respectively. Furthermore, a hybrid dependent variable of
actual and appraised prices, that is, the accepted price, extracts
explicit significantly better statistical measures. Additionally, the overall
model fit was enhanced by introducing locality dummy variables
and, through different combinations of attributes, captured the optimal
results per district. Eventually, when the introduced transaction based
indices were compared to the corresponding existing published
indices, which are based on non-actual data, we saw some
resemblances, but overall, there were wide deviations.