Metadata about: Abstract In this paper, studies on the real estate markets mainly focused on the relationship between abrupt change points and corresponding political issues and economic collapse. Within the past statistical framework, change-point detection technique was widely considered based on large and long data sets. Few studies considered the situation where a limited size of time-series data sets is available in the real estate markets. To fill in this gap, the wavelet analysis with minimax threshold is introduced in this paper. By comparing Daubechies LA(8), wavelet analysis with minimax threshold is a versatile and powerful approach to the analysis of residential data as they are flexible in their function form and provide a robust computational method even with a small sample size. The detected change points reflect some significant political issues and economic collapses. It can be shown from the empirical result that a “diffusion relationship” happened from one location to another.

About: Abstract In this paper, studies on the real estate markets mainly focused on the relationship between abrupt change points and corresponding political issues and economic collapse. Within the past statistical framework, change-point detection technique was widely considered based on large and long data sets. Few studies considered the situation where a limited size of time-series data sets is available in the real estate markets. To fill in this gap, the wavelet analysis with minimax threshold is introduced in this paper. By comparing Daubechies LA(8), wavelet analysis with minimax threshold is a versatile and powerful approach to the analysis of residential data as they are flexible in their function form and provide a robust computational method even with a small sample size. The detected change points reflect some significant political issues and economic collapses. It can be shown from the empirical result that a “diffusion relationship” happened from one location to another.

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