Abstract
This study examines the effects of a government announcement of soil liquefaction potential on housing prices in the reported areas, and explores the rate at which these prices changed after the announcement. This investigation utilizes published real estate price registration data from Taipei City, Taiwan covering the period January 1, 2015 to December 31, 2017, and resolves the issue of data heterogeneity by applying nearest-neighbor matching (an aspect of propensity score matching), and employ the difference-in-difference method in conjunction with two-stage spatial quantile regression. The empirical results indicate that although low, moderate, and high housing prices in potential soil liquefaction areas were all negatively affected by the announcement initially, after a period of one and a half years, the negative effect decreased for low housing prices and was no longer significant for moderate and high housing prices.
Notes
1 Kuan and Lee (2008) indicate that in a counterfactual framework, two types of reactions exist for each group. The first type is the reaction after receiving experimental treatment and the second type is the reaction without experimental treatment. Therefore, a counterfactual framework can be also referred to as a potential outcome model.
2 Larger percentage indicates greater reduction of experimental and control group differences in characteristic variables after matching.
3 1 ping is equal to 3.305 m2.
4 Optimism bias refers to the optimistic belief that one's neighborhood is less likely to be affected by disasters compared to other neighborhoods (Helweg-Larsen, 1999).
5 Consumers who prioritize housing characteristics are those who are attracted to these characteristics. For example, those who prefer larger living rooms will overlook the fact that a housing unit is located in an area with a high disaster risk if said unit has a large living room.
6 One example is the Taipei City Regulations for the Accelerated Reconstruction of Dangerous and Old Buildings.