An Economic Analysis of the New York Times Coverage of Extreme Weather Events
Why Does the Paper of Record Emphasize Doom and Gloom?
Back in 2017, Dora Costa and I published our Economica paper that studies decades of New York Times coverage of infectious disease trends over the decades. From 1890 to the mid 20th Century, the U.S experienced a huge decline in mortality from infectious disease but the nation’s leading newspaper rarely reported on this good news. Bad news often was publicized.
I think back to my media research as I read the New York Times “doom and gloom” coverage of the flooding in Vermont and New York. The Times is investing more resources in covering the “climate crisis”. I take the challenge of climate change quite seriously but I benchmark how the actual economy is functioning.
Vermont is home to 650,000 people and New York is home to 20 million people. Every day something terrible happens in both states. This week, an extreme weather shock has occurred and individual homes and businesses and local infrastructure have been damaged but relative to the assets that were exposed, the actual damage is tiny. Let me repeat, any death is a tragedy but in a huge economy —- terrible things occur every day. I would bet that there were more murders in New York State over the last week than there were deaths from the extreme rains.
Our economy is amazingly resilient to these shocks. Even the New York Times acknowledges this without commenting on this. A direct quote;
We SHOULD NOT be complacent here. My research agenda focuses on how to use microeconomic ideas to ACCELERATE the pace of our adaptation but we are already quite good. For those who are open to new ideas, read my 2021 book.
I am an empiricist. What are benchmarks of adaptation progress?
If we compare the economic output of Vermont and New York State in July 2023 (the shocked time period) to July 2022, do you expect that we will see a large difference? The cliché is that such shocks cause subsequent economic growth because of the reconstruction of the damaged capital stock such as homes and roads.
The interesting microeconomics here pertains to how investors who invest in upgrading the damaged buildings and infrastructure rebuild? I predict that many of them will “build back better” with better materials and better techniques so that their assets will face less future flood risk. A silver lining of flood events is the opportunity build back a capital stock that is better able to withstand Mother Nature’s tougher punches.
Returning to the victims of the flood. There is always a question of how we share risk. If 10,000 New York homes have been damaged (and keep in mind that the state has 20 million residents), and if each of these homes suffers on average $7,500 worth of damage , who should pay for these repairs? How quickly will these victims receive their checks? How inconvenienced will they be in the short run? When low probability events become more likely, how do markets help such individuals to cope?
We are used to this in the case of our health. If the main earner in a family has a heart attack and can’t work anymore, how does this family pay its bills going forward? To an economist, risk is risk.
The great news is that the death toll from natural disasters (deaths per person exposed to the shock) is falling sharply over time because we are richer and living in higher quality housing and our cell phones alert us to the emerging weather threat. Given that we are increasingly likely to survive. How do we protect our property and earn an income in the weeks after a disaster? For those people living in areas hit by the New York and Vermont flooding, how many of them will be going to work this week? How disrupted are their lives? How quickly will they get back on their feet? This is the microeconomics of adapting to shocks. These are the topics that I would like to see the New York Times exploring.
The evidence from the last few days bolsters my optimism about our increased capacity to adapt to extreme weather.
In our 2022 NBER Paper , we use changes in lights at night as our measure of the impact of floods. Here is our paper and our abstract for our study of thousands of cities around the world.
Adapting to Flood Risk: Evidence from a Panel of Global Cities
Sahil Gandhi, Matthew E. Kahn, Rajat Kochhar, Somik Lall & Vaidehi Tandel
WORKING PAPER 30137
DOI 10.3386/w30137
ISSUE DATE June 2022
Urban flooding poses danger to people and places. People can adapt to this risk by moving to safer areas or by investing in private self-protection. Places can offset some of the risk through urban planning and infrastructure investment. By constructing a global city data set that covers the years 2012 to 2018, we test several flood risk adaptation hypotheses. Population growth is lower in cities that suffer from more floods. Richer cities suffer fewer deaths from flood events. Over time, the death toll from floods is declining. Cities protected by dams experience faster population growth. Using lights at night to measure short run urban economic dynamics, we document that floods cause less damage to richer cities and cities with protective dams. Cities with more past experience with floods suffer less from flooding.