Does Media Coverage Affect Governments’ Preparation for Natural Disasters?

Abstract

While natural hazards have never been so frequent in modern history, the political economy of disaster preparation remains largely understudied. To prepare for natural disasters, local governments can adopt mitigation measures (e.g., infrastructure elevation, retrofitting, shelter construction, etc.). However, in doing so, there is a trade-off between risk reduction and risk disclosure as these initiatives may signal latent dangers of a place to unsuspecting homebuyers. Increased media coverage may ease this trade-off by revealing these dormant risks. I develop a measure of newspaper coverage of storms using data on newspapers' circulation and occurrence of storms at the ZIP code level in the United States. Using the variation in this measure, I identify the effects of heightened media attention on local governments' mitigation efforts under the Hazard Mitigation Grant program managed by FEMA. I find that when newspaper coverage is high, jurisdictions that have experienced severe storms tend to implement significantly more mitigation projects. Conversely, when coverage of storms is low, jurisdictions do not undertake mitigation projects after being hit by a storm. My results are primarily driven by ZIP codes with high pretreatment levels of vacant housing units, housing units occupied by renters, and housing units owned with a mortgage. I argue that local governments may be strategically underinvesting in disaster preparation to avoid revealing their jurisdictions' inherent risk to otherwise uninformed property investors.

Obtaining consistent time series from Google Trends

“…Since the technique produces consistent daily series, it also opens new possibilities for event studies at a daily level. Daily GSV data allows researchers, for example, to study public worries or anti‐immigrant sentiments following terrorist attacks; monitor the spread of diseases after natural disasters; or to measure public awareness about environmental risks and disasters and thus predict the likelihood for humanitarian aid (Eisensee & Strömberg, 2007) or local disaster preparedness (Magontier, 2020).…”