Saturday, November 26, 2016

Rising Sea Levels and Sinking Property Values: the Effects of Hurricane Sandy on New York’s Housing Market

Abstract:
Are coastal cities adjusting to rising sea levels? This paper argues that large-scale events have the potential to ignite the process. We examine the effects of hurricane Sandy on the New York City housing market. We assemble a large plot-level dataset with rich geographic data on housing sales in New York City for the period 2003-2015, along with information on which building structures were damaged by the hurricane, and to what degree. Our difference-in-difference estimates provide robust evidence of a negative impact on the price trajectories of houses that were directly affected by Sandy. Interestingly, this is also the case for houses that were not damaged but face high risk of coastal flooding. Our results suggest that Sandy has increased the perceived risk of living in those neighborhoods. We also show that the negative effects on housing prices appear to be highly persistent.
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Far Rockaway boardwalk, six weeks after Hurricane Sandy in 2012. (Photo by cgc76, Creative Commons license)

These point estimates suggest an initial 18 log point price reduction in year 2013, with a partial recovery amounting to an 8 log point reduction in year 2014, and stabilizing at an 11 log point drop in value in year 2015. This pattern is illustrated in Figure 6, which plots the point estimates and the 95% confidence interval.... The Figures clearly show that the price reduction for units in HEZ12 took place precisely in the first quarter of 2013, providing strong confirmation in favor of identifying hurricane Sandy as the event responsible for the structural break. Furthermore, we learn that prices initially over-reacted and fell by close to 20 log points in the year immediately after Sandy.62 In the following years sale prices partially recovered but even in 2015 the Sandy price penalty appears to be around 10 log points.

To gain a deeper understanding, we turn to the estimation of Equation (6), reported in columns 2 through 4 of Table 11. In all three columns we notice the same pattern: small and non-significant estimates for all years with the exception of the large and statistically significant estimates for the post-Sandy years 2013-2015. The estimates suggest a similar pattern for units located in HEZ12 that were undamaged (identified by Dam0) or lightly damaged (Dam1): a large initial drop of about 17 log points, followed by a partial recovery so that in 2015 the price penalty is around 10 log points. In contrast the price penalty for severely damaged properties (Dam2) is large and fairly constant over time at about 25 log points throughout the post-Sandy period in our sample (2013-2015).



http://qcpages.qc.cuny.edu/~fortega/research/sandy_housing.pdf
by Francesc Ortega and Suleyman Taspınar both of Queens College, CUNY
October 21, 2016
(http://qcpages.qc.cuny.edu/fortega) and (https://sites.google.com/site/gcsuleymantaspinar

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