期刊:Social Science Research Network [Social Science Electronic Publishing] 日期:2023-01-01
标识
DOI:10.2139/ssrn.4322614
摘要
In 2017, Hurricane Maria made landfall in Puerto Rico, becoming the deadliest hurricane ever recorded on the island. The hurricane caused damage to hundreds of thousands of homes and left millions without power for days. This study seeks to investigate how that devastation affected the housing prices in Puerto Rico. We collected 1001 single-family house data from the Zillow website between 2018 to 2021. For the causal inference (treatment-effect), distance buffer from the track, location (house is on the right or left side of the hurricane path), and flood zone (house located in a flood zone or not), etc., were used as part of the primary identification strategy. We also combined the traditional hedonic price model with Regression Discontinuity Design (RDD) to measure the hurricane's causal (treatment) effect on housing prices. First, findings from the basic difference-in-difference hedonic price models indicated a downward trend/pattern of housing prices in post-hurricane years. We then used sharp and fuzzy RDD models with single and multiple cut-offs to estimate similar specifications. The RDD results also confirm the negative trend of falling prices. Identifying the best functional form of spatial hedonic models can help Puerto Rico policymakers and future researchers analyze housing price fluctuation in Puerto Rico in the aftermath of a major natural disaster.