The impacts of hurricanes analyzed in the previous post in this series may be far-reaching in the Second District. In a new Staff Report, we study how banks in Puerto Rico fared after Hurricane Maria struck the island on September 17, 2017. Maria makes a worst case in some respects because the economy and banks there were vulnerable beforehand, and because Maria struck just two weeks after Hurricane Irma flooded the island. Despite the immense destruction and disruption Maria caused, we find that the island’s economy and banks recovered surprisingly quickly. We discuss the various protections—including homeowners’ insurance, federal aid, and mortgage guarantees—that helped buttress the island’s economy and banks.
Hurricane Ida, which struck New York in early September 2021, exposed the region’s vulnerability to extreme rainfall and inland flooding. The storm created massive damage to the housing stock, particularly low-lying units. This post measures the storm’s impact on basement housing stock and, following the focus on more-at-risk populations from the two previous entries in this series, analyzes the attendant impact on low-income and immigrant populations. We find that basements in select census tracts are at high risk of flooding, affecting an estimated 10 percent of low-income and immigrant New Yorkers.
A previous Liberty Street Economics post found that minority-owned small businesses in the Federal Reserve’s Second District have been particularly vulnerable to natural disasters. Here we focus on the aftermath of disasters (such as hurricanes, floods, wildfires, droughts, and winter storms) and examine disparities in the ability of these firms to reopen their businesses and access disaster relief. Our results indicate that while white- and minority-owned firms remain closed for similar durations, the latter are more reliant on external funding from government and private sources to cope with disaster losses.
In this post, we follow up on the previous Liberty Street Economics post in this series by studying other impacts of extreme weather on the real sector. Data from the Federal Reserve’s Small Business Credit Survey (SBCS) shed light on how small businesses in the Second District are impacted by natural disasters (such as hurricanes, floods, wildfires, droughts, and winter storms). Among our findings are that increasing shares of small business firms in the region sustain losses from natural disasters, with minority-owned firms suffering losses at a disproportionately higher rate than white-owned firms. For many minority-owned firms, these losses make up a larger portion of their total revenues. In a companion post, we will explore the post-disaster recovery of small firms in the Second District: how long do they remain closed and what are their sources of disaster relief?
The intensity, duration, and frequency of flooding have increased over the past few decades. According to the Federal Emergency Management Agency (FEMA), 99 percent of U.S. counties have been impacted by a flooding event since 1999. As the frequency of flood events continues to increase, the number of people, buildings, and agriculture exposed to flood risk is only likely to grow. As a previous post points out, measuring the geographical accuracy of such risk is important and may impact bank lending. In this post, we focus on the distribution of flood risk within the Federal Reserve’s Second District and examine its effect on establishment location decisions over the last two decades.
In our previous post, we identified the degree to which flood maps in the Federal Reserve’s Second District are inaccurate. In this post, we use our data on the accuracy of flood maps to examine how banks lend in “inaccurately mapped” areas, again focusing on the Second District in particular. We find that banks are seemingly aware of poor-quality flood maps and are generally less likely to lend in such regions, thereby demonstrating a degree of flood risk management or risk aversion. This propensity to avoid lending in inaccurately mapped areas can be seen in jumbo as well as non-jumbo loans, once we account for a series of confounding effects. The results for the Second District largely mirror those for the rest of the nation, with inaccuracies leading to similar reductions in lending, especially among non-jumbo loans.
The National Flood Insurance Program (NFIP) flood maps, which designate areas at risk of flooding, are updated periodically through the Federal Emergency Management Agency (FEMA) and community efforts. Even so, many maps are several years old. As the previous two posts in the Extreme Weather series show, climate-related risks vary geographically. It is therefore important to produce accurate maps of such risks, like flooding. In this post we use detailed data on the flood risk faced by individual dwellings as well as digitized FEMA flood maps to tease out the degree to which flood maps in the Second District are inaccurate. Since inaccurate maps may leave households or banks exposed to the risk of uninsured flood damage, understanding map inaccuracies is key. We show that, when aggregated to the census tract level, a large number of maps do not fully capture flood risk. However, we are also able to show that updates do in fact improve map quality.
Climate change may pose two types of risk to the economy—from policies and consumer preferences as the energy system transitions to a lower dependence on carbon (in other words, transition risks) or from damages stemming from the direct impacts of climate change (physical risks). In this post, we follow up on our previous post that studied the exposure of the Federal Reserve’s Second District to physical risks by considering how transition risks affect different parts of the District and how they differentially affect the District relative to the nation. We find that, relative to other regions of the U.S., the economy of the Second District has considerably less exposure to fossil fuels. However, the cost of reducing even this relatively low economic dependence on carbon is still likely to be considerable.
In this post, we discuss the climate-related risks faced by the Federal Reserve’s Second District and compare these with risks faced by the nation as a whole. The comparison helps contextualize the risks while framing them in the broader context of a changing climate at the national level. We show that the continental Second District—an area consisting of New York State, the twelve northern-most counties of New Jersey, and Fairfield County in Connecticut—faces fewer and less severe climate-related physical risks than the nation as a whole. However, the areas that comprise the Second District still rank somewhat high in key risks that include “heat stress.” This holds true especially for New York City.
Much of the work on climate risk has focused on the physical effects of climate change, with less attention devoted to “transition risks” related to negative economic effects of enacting climate-related policies and phasing out high-emitting technologies. Further, most of the work in this area has measured transition risks using backward-looking metrics, such as carbon emissions, which does not allow us to compare how different policy options will affect the economy. In a recent Staff Report, we capitalize on a new measure to study the extent to which banks’ loan portfolios are exposed to specific climate transition policies. The results show that while banks’ exposures are meaningful, they are manageable.