TY - JOUR
T1 - Construct comprehensive indicators through a signal extraction approach for predicting housing price crises
AU - Xu, Yan
AU - Ma, Yuanting
AU - Zhu, Zhengke
AU - Li, Jun
AU - Lu, Tom
N1 - Publisher Copyright:
© 2022 Xu et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
PY - 2022/8
Y1 - 2022/8
N2 - In this paper, a novel early warning system that has usually been applied to predict the financial stress events is established to predict the likelihood of housing price crises in China. To achieve this goal, a signal extraction approach is used to monitor the evolution of a number of economic indicators that tend to exhibit the abnormal behaviors. 13 economic variables were selected as the individual indicators, and constructed as the four comprehensive indicators. Our empirical work shows that the early warning system for urban housing price crises is suitable for China's four province-level municipalities. The in-sample forecasting results indicate the reliability of the early warning system for urban housing price crises. By studying the out-of-sample forecasting results, the likelihood of housing price crises for the four cities can be effectively predicted. We construct a novel weighted average comprehensive indicator, which performs better than the three others in terms of overall performance across all of the criteria considered in. It is shown that the extended system is more flexible in decision making than the traditional early warning system.
AB - In this paper, a novel early warning system that has usually been applied to predict the financial stress events is established to predict the likelihood of housing price crises in China. To achieve this goal, a signal extraction approach is used to monitor the evolution of a number of economic indicators that tend to exhibit the abnormal behaviors. 13 economic variables were selected as the individual indicators, and constructed as the four comprehensive indicators. Our empirical work shows that the early warning system for urban housing price crises is suitable for China's four province-level municipalities. The in-sample forecasting results indicate the reliability of the early warning system for urban housing price crises. By studying the out-of-sample forecasting results, the likelihood of housing price crises for the four cities can be effectively predicted. We construct a novel weighted average comprehensive indicator, which performs better than the three others in terms of overall performance across all of the criteria considered in. It is shown that the extended system is more flexible in decision making than the traditional early warning system.
UR - http://www.scopus.com/inward/record.url?scp=85135404048&partnerID=8YFLogxK
U2 - 10.1371/journal.pone.0272213
DO - 10.1371/journal.pone.0272213
M3 - Article
C2 - 35913928
AN - SCOPUS:85135404048
SN - 1932-6203
VL - 17
JO - PloS one
JF - PloS one
IS - 8 August
M1 - e0272213
ER -