The Storm After the Storm: the Long-Run Effects of Natural Disasters

evening, everyone, and thank you so
much for joining us, the Master of Science
in Response Management program here tonight. We’re really excited
to have you all here and to talk about this really
important topic right now. Before we get
started, the lecture itself will go for about
45 minutes to an hour. And then there’ll be
time for questions. We’d really appreciate
it if you could keep your questions to the end. Yeah. OK. And I was also told to
remind you, any of you who are applying or are interested
in applying for the program, we are hosting an online
application workshop tomorrow to help you make an
outstanding application. So if you haven’t
already registered, I definitely encourage
you to do so. So without further ado, welcome
to tonight’s event, “The Storm After the Storm, the Long-Run
Effects of Natural Disaster.” My name is Natalie Foster. And I am the program
manager for the program. And it gives me great
pleasure to introduce tonight’s speaker, Amir Jina. Amir is an assistant
professor at the University of Chicago Harris School
of Public Policy, where he researches how economic
and social development is shaped by the environment. He uses applied economic
techniques, climate science, and remote sensing to understand
the impacts of climate change and natural disasters in
rich and poor countries, and has conducted field work
in India, Bangladesh, Kenya, and Uganda. Before joining the
University of Chicago, Amir received his
PhD in sustainable development from
Columbia University and has worked with the
Red Cross in South Asia. Please welcome me
in joining Amir. [APPLAUSE] AMIR JINA: Thank you very much. Hopefully, this is on. You can hear me. So just to give a broad sense
of background about who I am, why I’m here, what
my research is, and what I’m going
to talk to you about. So I came into– I’m basically an economist. I came into it
through a weird path. I started off in maths
and theoretical physics. And then I started to realize
that that was probably far too abstract for the things
that I was interested in. And I thought that climate
science was this nice way to take the physics
that I had learned and apply it to something
which matter to people. But while I started
learning about that, just before I started
my PhD, I realized that some of the
biggest questions were not necessarily
about what happens to air as it heats up and as
the CO2 increases and traps heat in the
atmosphere, but rather what we as a society
or we as a species even do to respond to this. How is it that we are shaped
by the environment around us? Why do we do some
things well in terms of our environmental policies? Why do we do some things badly? And those questions
were the ones which fascinated me a lot more. I had the fortune right at
the start of graduate school to be working with
the Red Cross and Red Crescent in India
and Bangladesh, which is one, where
I took this picture. But two, where I started
really thinking about disasters and the way in which
they could affect society in ways which we weren’t
really measuring correctly. So some of the things
that I’m going to say sounds a little bit like
environmental determinism. That the environment
is determining the abilities of societies
to grow and develop. It’s not really that. I’d say call it
neo-environmental determinism, if you want. What we set out to do in
a lot of this research is not say that the environment
is the most important thing for determining
economic prospects, but that it is an important
thing– one among many. And in order to make the
right policies, in order to make rational policies,
to deal with disasters, with climate change,
with air pollution, we need to understand
exactly what the extent of those impacts are. So a lot of it, to put it
in a very unglamorous way, a lot of what I do is
really about measurements, solving measurement issues
with the environment. In that way, I’d like to think
of myself as a scientist as well as an economist. I guess economists
are scientists. But the result of all
of this measurement is to find some kind
of unique things– answers to empirical
questions about, particularly about natural disasters, which
I’m going to discuss today and the way in which they
affect society in the long run. So as a broad
overview of the talk, I’m going to talk,
as you expect, about the long-run
impacts of disasters. This is not really where a
lot of people get into this. There’s a large and
incredibly important industries that have
researchers, everything about how to deal with deserters
immediately after the fact– so immediate response
to those impacts. There’s less understanding of
how those policies play out in the long run,
but also how to deal with the issues in the long run. Or even if there are
impacts in the long run. So that’s kind of
where, what I’m going to give an overview of. I’m going to try and keep
it at a pretty high level and give you a flavor of
what the research is– not go into a huge amount of
statistical or mathematical detail, unless you want me to. In which case, raise
your hand and I’m happy to talk about
statistics for a while. But I want to give you a
sense of really try to get at this set of questions here. In the end, we’ll
talk a little bit about Puerto Rico and
some work that I’ve been involved in there, or
I’ve definitely been watching. So the first one is
what are the effect that disasters have on long-run
economic development, if any? So this was the big question
which kind of started off my research career, probably
seven or eight years ago now with this particular paper. If there are effects, would we
see them in the United States? The United States is
the richest economy in the world, extremely
adapted, good infrastructure. Would we see them in
the United States? Similar question– would we see
them in Japan or other places that are wealthy and
what we would think would be well adapted? If we do see them, what
are the mechanisms? Why would we see
a long-run effect, when we know that
in a lot of places we have really coherent
disaster management policies, particularly for
dealing with short-run impacts? And then something
which I probably know much less about than people
sitting in this room, what do we learn from policy? And how can we decrease
negative impacts if we see them? So that’s broadly what I’m going
to try and talk about and give you a flavor of what the
research is saying about this. So when I started thinking
about this question with my co-author,
Sol Hsiang, who’s a professor at UC Berkeley, as
I said about eight years ago or so, we actually
started thinking about it based on an interesting picture
we saw of data from Haiti. So in the ’60s and
’70s, Haiti was growing. Its economy was booming. It was growing very quickly. And in 1980 for some reason,
this growth trajectory changed. And it started to decline, which
it hasn’t really come out of. And then after that in
’86, ’87, there was coups, there was political
unrest through the ’90s. There was a massive
earthquake in 2010. So this was a– started off thinking a
little bit about Haiti and what happened exactly
at that point in 1980. It turns out at
that point, there was a hurricane called Hurricane
Allen, which at the time was the most intense
landfalling hurricane that it had hit anywhere
in the Atlantic, right in 1980 when all
these things happened. As we got deeper
into the research, first of all the data
from Haiti are for reasons as you can probably
understand, very difficult. It’s not the best
data in the world. But also a lot of other
things happened at the time. So we took a step back and
started thinking, well, what would this– what do people think would
happen when a disaster hits a country to their economy? Would we see something
like that effect that we saw in
Haiti, where we’re growing through
the ’60s and ’70s, and then suddenly
in 1980, we stop. And basically,
economists the way they had thought about
this, had come up with four different
hypotheses, all of these are based on
theoretical concerns. They didn’t really have a
satisfying empirical answer. So what we have is, we
have a GDP per capita. So we would think of
it income per capita, growing at some baseline level. And so a country is
growing in some way. And then disaster strikes. The way economists were
thinking about this, there was four things
that could happen. And these people kind
of stuck to their guns on different ones. But by and large,
a lot of economists thought that one of these
two top trajectories would be what would be observed. So we’d have something
called creative destruction. So a disaster comes
in, you have a lot of out-of-date infrastructure,
out-of-date capital. It gets destroyed
and demolished. It gets rebuilt. And
then suddenly, we have this very beneficial
effect on the economy. The economy starts to boom
because we end up with, instead of a bad factory, we
have a good factory. You produce more. The reason the difference
between these two is that in the top
one, you would also see that the disaster
would have larger effects on the equilibrium
in the economy, and that you would end up
having increase in wages. So labor would labor supply
would go down in some area, and people would migrate in. And so it would start
to boom straightaway. And that’s really what
was stuck in the mind of a lot of economists–
that disaster should be good for development. In fact after Harvey, the
chairman of the New York Fed made this claim on
NBC that, he said, I apologize for saying it. It sounds insensitive,
but we know disasters are good for growth. So we’ll get over this initial
misery that people are seeing. And things will be fine. Again, this is an idea
that’s really entrenched in a lot of economists’
minds, this idea of building back better. That maybe you’d have some
declines in the immediate term, but that as the good factories
you’ve built kick in, you’d start to see this boon
to your economy, one which has been observed
and in fact, it’s been observed in some
other empirical situations. So two that come to mind
are population recovery after bombings in Japan. It looked like the
population recovered after these big shocks
during World War II. And one of the reasons
to think of that is maybe that, you
know, World War II ends. We don’t expect it
to happen again. And so people will start to
move, start to have children, and that population will
recover because there’s some economic benefit to being
in a certain part of the world. There’s trade routes in Tokyo,
and et cetera, so people would move back
in and populations would start to grow. And eventually, we’d get back
to where we were growing before. And then there’s this
more pessimistic one. And I hate to tell you that
I’m on this pessimistic track, both ex ante this is what I
thought would be the case. This was the prior information
that was in my mind. But it’s also the one
that we find empirically. And this would just say
that some of these shocks are so large that it will
push us off that trajectory. We will, our
economy will diverge from what we call the
counterfactual, what would have happened if the
disaster had never hit. And we’ll end up
on a new trajectory that’s lower than the old one. So these were the four things
that were in people’s minds. And as I said, a
lot of economists were thinking that these
two would be naturally what the solution would be. A lot of that’s
coming from reasoning from old economic growth
models that everyone learns when they’re doing their
first macroeconomics class. But it’s a very strong– it’s a very strong
belief among people. So there was these
competing hypotheses. But there was no
real answer to those just by thinking through theory. We can come up with
anything, any part discussion of what’s happening
in the economy, to think of some friction– maybe people will
be able to move in, and so we’ll see this boon. Maybe they won’t. There’ll be some
barrier to migration. You can put in
different frictions to what’s happening in
economy to kind of end up at any one of these. So what we wanted to know is
what was actually happening. How would we solve this issue? How would we understand this? It was an empirical question
which needed to be resolved. A lot of the previous research
had issues with measurement. The way we measure
disasters is not– which might be surprising
to hear considering they’re so economically important– it’s not particularly good The way researchers
have been doing this was, if a disaster
happens in a year, they say, OK, disaster happened. It gets a one in your data. If a disaster didn’t
happen, it gets to zero. But that just means
that everything, every hurricane,
small and large, is treated exactly the same. Every earthquake is treated
the same as a hurricane, is treated the same as a flood. All disasters were treated
in the same kind of way in a lot of this research. So we had to try and
resolve that somehow. So basically what we did using
this training in both climate science and
economics, we decided we’d use the climate
science to try and tell us what the disaster
was actually doing. If we could measure
its intensity, we’d be able to solve
this measurement problem. So the first thing
that we had to do is build its global
model of hurricanes– hurricanes, tropical
cyclones, typhoons– I’ll use them all– or storms. I’ll use them all
interchangeably. This was a typhoon– Typhoon Nanmadol, I think,
over the Philippines, which is seen here. This tiny bar scale is
here is 100 kilometers. These are huge events. They happen over a very
short period of time. In a few days, they can cause
a lot of economic damage. And we know that there’s a
certain measurement of damage, measured with a lot of error. Sometimes it’s just, we know
what the insurance claims are. We don’t know what the
uninsured losses are. But we want to get
at something which– we wanted to get
at something which says more about what’s the
evolution of the economy after one of these things hits? So we built this model, knowing
what the meteorology was like for a storm
swirling around, knowing that they’re measured
kind of, well, from satellites. And we know where the track is. And we know what
that pressure is. We built this model
which showed here’s what the average exposure is
for all of these countries, for all these regions
that are in the world. So you can see that this
is the Atlantic Basin here. And these are the Atlantic
storms averaged over like 50, 60 years. The redder colors
are the more intense in terms of wind speeds. So you can see that
the average wind speeds that are in this Pacific
basin are much more intense. So the typhoons
are more intense. Partly that’s because the
Pacific Ocean is bigger. It has more time to
gather energy and become stronger storms. Places like the
Philippines are getting hit by 10, 15, 20 storms per year. So it’s a very active
cyclone climate. So we built this model. But the important
thing in the research was to not just look at
what the average effect is, but instead to look
at each specific year. So an important
thing to realize was that storms are going to
happen around the world. These tropical cyclones
are going to happen. But the exact path they
take is completely random. Whether something hits the
Philippines, or Taiwan, or parts of mainland China,
or Japan, it’s kind of random. You don’t know at the
start of the season if something is going to hit. So we exploit this and
we look at essentially what happens within
a year and it’s economic– within a country
within its economic growth. And in the years when
it gets hit by a storm, we’re using that kind of as the
treatment in our experiment. So we’re saying that we have
the year in when it’s treated, it gets a storm. And the year in which
it doesn’t, it’s the control group. And we look at that variation
that happens with storms as they’re getting hit. We don’t just do
this for one year. We do this for 60
years, as I said. So this is the
reconstruction historically of every tropical cyclone
which has hit the Earth. And we know exactly
what the wind speed is, what the power is at
each point on the surface. So now we have our setup. And so what do we find? Here’s the hypotheses
that we had before. I’ve already kind of
given the game away. You know what we found. We found this. So going, looking at
these two things together, we have the same
kind of picture. We have our baseline
trend growing. We have from two different data
sets, way that you measure– of two different data sets
that are measuring the income per capita for people. We see that when a storm hits– and I’m saying storms now
rather than disasters. There is some evidence
that the same thing holds for earthquakes, but
there’s a lot of work that needs to be done
on those as well. You start to see that compared
to what the growth trajectory was, you see this divergence. So it starts to grow slower. And you get this widening
separation between the place that gets hit by the storm and
what would have happened if it hadn’t been hit by the storm. It’s pretty substantial by
the time you get to the end. This is modeled out for a
one standard deviation storm. It’s not really important,
but a storm of a certain size. But for every meters-per-second
increase in wind speed, we see about 0.3% decrease
in the level of GDP 15 years later. So that’s meter per second
averaged over a whole country. We can go a lot more into that. It’s kind of a weird
measure to think of. But I’ll put up some
magnitudes later so you can kind of think about this. But you start to
see this divergence. Now, there’s a couple of
things that are, I think, important to note here for
thinking about disaster management– any kind of shock
that you’ll face to businesses, to anything. At the time of a large
environmental shock, is that around the
time that it happens, we don’t really see very much. Almost all of what we
think about for disasters is focused on this
period here, the year of, the year after, maybe
a couple of years after. But then it quickly
fades from memory. But we don’t see very much. Part of the reason there is
because these four hypotheses are kind of true
in the short term. If you get a big disaster
that gets a lot of attention, you can get a lot of
inflow of aid, inflow of workers, labor moves around. So you can get this
boost in the year. You get a lot of
reconstruction, which helps GDP. You count the things
you build back. You don’t count the
things that were lost. So it looks like your GDP
increases in the year after. So you can get this boost. Sometimes you can
get the opposite, if the disaster isn’t
big enough to really gain a lot of international
attention, if you’re in a poor country. Or if it’s not even
particularly large in the US, you don’t get as much
FEMA money coming from it. You can see that there would
be losses in that year. And it’s very
idiosyncratic which disasters get the
attention and which don’t within a certain threshold. The very large ones will
get a lot of attention. There’s a medium range,
where sometimes people will pay attention. Sometimes they won’t. And you’ll see this kind
of noisy response there. Who knows what’s happening? Sometimes there’ll be a boost. Sometimes there won’t be. So that’s one of
the reasons it’s difficult to see anything here,
because it kind of bounces around. It’s unclear. But what this is showing that,
what this is showing then is that, regardless of
what’s happening here, for every single
storm that’s ever hit mainland fall on any
country since 1950 to 2008, their economies for those
countries started to slow down. And they started to
gradually diverge from where they were
before the storm hit. This is something that’s very
difficult to see in the data. If you’re just looking at
the GDP of some country and you see it kind of, it
would be difficult to pick out where it starts to slow down. Because there’s
no one giant shock where you can pick it out. So that story of Haiti,
of seeing Haiti growing and then the growth
trajectory changing, you don’t really see
that a lot of countries. You just see this
very gradual change in their GDP, which
is what we see here. It’s kind of remarkable. We were very skeptical
of this result. Because when you look at
the magnitudes of some of the storms, these effects
are actually quite big. So 0.3 percent seems small. I’ll get onto what that means
for Puerto Rico and Hurricane Maria at the end. But some of these
effects are quite large. The other thing
to think about is what happens for
repeated hurricanes? So places that get
hit by a hurricane are often getting hit
again, and again, and again. It’s not like we’ll have
one hurricane in the US and then we wait 20 years
and we have no hurricanes. So here we have this
thing for a single storm. We see the years after
the storm up to 20 that we look like
there’s no recovery. Even as we go back
to 30, it looks like there’s no recovery– back to this baseline. But then what happens if
you’re getting hit each year? Like the Philippines,
that I said, is getting hit every
single year by many storms. So we have our baseline trend. A storm hits in year zero. And we have this divergence,
which is the thing that we had, that I just showed in
the previous slide. So this is what is happening if
a country is growing at around 2%, gets hit by a storm. It grows a little bit slower. What if it gets hit
again after three years? At that point three
years in, we see that it starts to diverge again. If they get hit after seven
or eight years, eight years I guess, it starts to diverge. At 15, it starts
to diverge again. So we see this very slow
almost imperceptible drag on the economy that
we see here because we saw this measurement
problem that wasn’t really clear before. If you think about
this, it’s pretty hard to do the mental math on this. But if you think
about this, think about the countries that have
a very active cyclone climate– like the Philippines, places
in Southeast Asia, the US Caribbean Islands– they’re getting hit each year. This is acting to
slow down their growth in a pretty significant way. We calculated in this
research what this sums up to across the whole world. And it’s a couple of percent
lower global growth because of these. It does look like some
countries are adapting. So places that get hit all
the time have smaller losses for each storm that hits them. They’re also getting
hit by more storms. So you’ve got to multiply
all those things out. But it looks like it’s a
pretty robust thing that’s happening, that you see
this slowdown of GDP. OK. To put this effect
in some context, we went through the economics
literature and looked at kind of the levels of or the effects
that have been estimated for big shocks to an economy,
and tried to think about where the sizes that we had– because
it was little bit difficult to think about them– where the size that we
had to fit in with that. So we see that, for
example, the estimate of a civil war after 10
years, it’s slowed down your– it’s lowered your GDP by 3%. The kind of, one of the
standard sizes of cyclones has lowered it by 3.6%
after 20 years, which is what we find–
so larger effects than civil wars on average. It’s something which
sits in quite well with financial crises,
currency crisis. These are large
shocks to the economy and have a long,
long-lasting effects. But then, of course, there’s
the US, the wealthiest country in the world. Should we be seeing this? There’s an interesting
fact, which has been noted in a lot
of the research literature that disasters when they
hit in rich countries cause more property damages
than they do loss of life– or relatively, they cause
more because there’s more expensive capital,
there’s more exposed property to get damaged. But people are kind
of shielded from what the intensity of the event is. In poorer countries,
the opposite is true. You have a situation
where you can have much higher
loss of life but much lower monetary damages. And this shift as
countries get richer. As people start to
get more protection, you see this shift
away from mortality and more towards
property damages. So richer countries– US, Japan
are two countries that are both wealthy and exposed to a
lot of natural disasters– they have better infrastructure. They have better
warning systems. It gets modeling these
kinds of disasters, modeling the hurricanes to give us
a three to five day warning has become a pretty
exact science. There’s still a
big, as you probably have seen those diagrams,
the cones of uncertainty that the National
Hurricane Center gives– there’s a wide range
where they can go. But we’re getting
pretty good at being able to pick up where the storms
are going to be and give people warning to evacuate people. It’s another reason
why there’s lower loss of life in wealthier
countries, lower loss of life in the US. So let me ask the question. Is the US adapted to
hurricane disasters? Do we still see this effect
in the US, or should we? So we broke up the world
into different countries. So small island,
developing states, you kind of think they
would be the most vulnerable because they’re tiny. Stronger wind speeds, when
a hurricane hits them, it’s sometimes the
size of the island. So their whole
economy is affected. It looks like, to within
a range of uncertainty, but the response is really
similar between those and all the other countries. If we break this up by the
major different basins– North America, all
of the countries then affected by that North
American basin hurricane– that’s right on where the effect
that I showed you before is. It looks like Asia is probably
having a little bit of a larger effect, maybe because
they have stronger storms. But this is something
which happens across the size of countries,
but also across the regions. So this is again
the percent of GDP that is lowered
years after a storm. And that’s what the growth
trajectory looks like. Then the thing which was
kind of most fascinating– I hope you can see it here,
because I can’t really see it on the screen. If we divided the world
up into rich countries and poor countries, based
on above-median income, below-median income, the
effect looks almost identical. For each meter per
second of storm, you’re getting,
again, after 15 years of at a 0.3% percent
decrease in GDP, regardless of what
your income is. So that’s kind of puzzling. You can imagine that this would
happen in developing countries. Why is something like
this happening in the US? What is the mechanism for
this happening in the US? We’ve got FEMA. We’ve got aid money. We’ve got reconstruction money
that happens straight away. So why was this something
which would happen there? Just a little bit
more on the US, particularly speaking
about hurricanes. So the effects are
the same in the US as they are in other
parts of the world. In terms of damages– and this is kind of surprising. There’s a paper from
a couple of years ago by Laura Bakkensen
and Rob Mendelsohn showing that the amount of
damage that the US experiences conditional on the
size of the storm hasn’t really changed in
the past 30 or 40 years. The rest of the world is
showing that it’s adapting. The amount of damage it has for
a certain intensity of storm is decreasing through time. Slowly in some cases, but
definitely decreasing. But the US has stayed
kind of the same. And that’s this big puzzle. Sometimes the culprit
is pointed at– the culprit of this
that is pointed to is a National Flood
Insurance Program. This has built in a lot
of intense financial risk when places are
exposed to hurricanes. We have a lot of capital. We have a lot of households. We have a lot of people
who are vulnerable, staying in places that are very
vulnerable because they’re not paying the right insurance
levels to stay there. And that’s definitely
a bigger problem than just this simple
description I gave. You have people
who are essentially stuck in houses with zero
value that they can’t sell, because they’re so
frequently exposed. And all they can do
is get federal money to rebuild them
year in, year out. So that’s one of the reasons why
we think that the US probably hasn’t shown the same level
of adaptation as others. It’s an incredibly hard
problem to deal with. And I’m sure there’s
people in this room that know more about it than I do. But it’s leading to this
massive drag, we think, on the US economy. OK. So what about mechanisms? What could lead to this
big decline in GDP? There’s probably a lot of them. It’s important to
think about what happens when disasters hit. So we think about what
happens straight away. You can have loss of life. You have damage to
your infrastructure, damage to factories,
things that are producing. So you can think of that. But you also have
these other effects that are a little bit longer
and a little bit more insidious, maybe. So you can see
businesses closing. I’m going to use a
really economics-y term and say you have
misallocation of labor. I’ll explain that in a second. You can have export shocks, so
either factories are damaged and they don’t produce as much. Or ports are damaged and
they can’t export as much. You see migration. And there’s some research
on that that will show about Hurricane Katrina. And there’s potentially
a lot of other ones. So just going through
a bit of those, this is now research
which has been done in the last few
years, by and large, looking at what some of the
causes of this big effect could be. So in a really interesting
piece of research that was done about
business closures after Hurricane Katrina,
there’s various ideas of what’s actually
happening to New Orleans after Hurricane Katrina. And some people say that some
areas have kind of grown back better than they
ever were before. Some places, like the Lower
Ninth, which was most affected, is still kind of a bit of
a quagmire, economically speaking. So some places have grown. Some places haven’t. What this paper does is
it looks at businesses. And it looks across places that
have different levels of damage due to Hurricane Katrina. And so you see that in the
year when the storm hit, we have that set at zero. That’s the number of
businesses there were. Ignore kind of what this is. This is just
effectively think of it as a number of businesses. And you see that through
time, the places that are undamaged– so
in Louisiana, there seems to be this kind
of, this already deep slow decrease of the number
of businesses in the economy. The places that
experienced a lot of damage from Hurricane Katrina
had this jump to go lower. So businesses were closing. It was often small businesses. You can see this looking just
within these damaged counties here, the ones that
were growing lower, that were closing more frequently. The places with really
severe damage, the businesses closed much quicker. Often, these were
small businesses. And then there was
more consolidation. So things like Walmart
were kind of fine, because they had this
diversified supply chain. A small business didn’t
really have that. So you see a lot of
small businesses closing. And then you can
think of, well, what does that do to a local economy
or even a national economy? You have a lot of people who
are losing jobs, et cetera. So this could be one
underlying mechanism. Here’s this labor
misallocation thing. So this is a paper by
Tatyana Deryugina at UIUC. So you look at what happens
to US, all US counties, after a storm hits. And you see the surprising
fact that the transfers from the government
start to increase. This is the year
that the storm hits. This is years after the storm. These are years before. And effectively,
what this means is that more people are going
on unemployment insurance. You see the number
of people unemployed. Number of adults
employed is decreasing. And this is lasting
for 10 years. The most amazing thing about
this paper, the headline of it, is that the cost of this– of social security and of
unemployment insurance– is 10 times the damages that
occurred from the hurricane in the year that it happened. So then we experience
these damages and then we
experience effectively 10 times more damages
that are stuck with us for the next 10 years. So this is, I’m calling
is misallocation of labor. You have all these people
who were previously employed, who could have been contributing
to the economy in some way. Who for some reason at
the time that the storm hit, lost jobs and are
never able to get them back. Either their businesses have
closed or some other reason. So this is another
reason, thinking about why this effect might
be this long-term thing. I’ll get to what some
of the implications are for this for
policy in a moment. We have migration. This is by the same, one
of the same authors– and apologies for this image. But the thing I want you to see
here are two different things. So this is what happens to
people after Hurricane Katrina. So a lot of people migrated. And this paper got their tax
returns and looked at what happened to their wages– the
people who migrated versus the people who stayed– and followed them
for a few years. So you see this, just in
thinking about their wages, you see that they initially
lost wages when they migrated. They’re obviously searching for
new jobs, something like that. But after a year or two,
their wages start to increase. So you could think,
oh, these people who migrated after Hurricane
Katrina are better off. That would lead to some
kind of potential decline around Louisiana, but
maybe benefits elsewhere. But then you see
this other thing that makes this a more
complicated picture. Those people are also
permanently drawing down their retirement savings. So whether or not you
think this is a good thing, that you make more wages
today but have less income in the future when your
retirement savings, is kind of an open question. And I think these two are
really trading off each other. So it’s unclear whether
migration is actually beneficial or harmful. But it’s definitely something
which happens after disasters. This is on a paper
about the Philippines. You see that parents stop
investing in their kids. So in a developing
country, you can imagine that this would be a big issue. People are then
developing less skills. Human capital kind of
slows down a little bit. But effectively,
households– the axis is flipped here, so this is
losses in this direction. After a storm hits– sorry, after a
storm hits, people are losing or
spending less money. They’re reducing
their expenditures. And then you see a lot
of potentially bad things happen in that time. You can extrapolate a little
bit from this to the US. So if I in the year after a
storm have to spend less money, I might be in a situation if
I’m in a low-income family of having to make a trade off
between a set of important things– medication, doctor visits,
education, et cetera. Those immediate
shocks are things which carry on with us
for years afterwards. There’s a paper I
just saw recently. It was looking at
trade at a port level. So a storm hits, and
then months after you see that exports are declining. So either it’s factories
which are damaged, production is damaged. Or it’s something like ships
being diverted and then never going back to
that port because they view this as an extra risk. And so you see all the
imports and exports– exports in particular,
but imports also– being affected in the long
run because a storm hits once. So this five day event,
which then starts stops starts a port declining
over this two year period and not seeming to recover. So it’s important
here, what the research is showing from
the last few years is that it’s important
thing about what is actually happening when a disaster hits. So not just thinking
about the immediate things that we can see and
observe, not just seeing. In the case of
Hurricane Sandy which happened while I was
living in New York, there was houses in Staten
Island, expensive houses with insurance, which were the
poster children for the damage from Hurricane Sandy. And people lost their lives. And it was a serious thing. And they are the images that
we think of for a disaster. But what’s also happening
is that there are people who didn’t lose as much, but because
of power losses in Manhattan, low-income families–
particularly Hispanic families in New York– couldn’t go to work that week,
sometimes lost their job. But that week’s
shock to income is something which can often lead
to extra payday loans, which is interest you’re accruing
sometimes over the long run, to people not buying meditation,
to other things which we don’t really think
of as disaster impacts. We don’t think of unemployment
in the long run as a disaster impact, but that could be
one of the things which is leading to this large
diversion between what would have happened had we
not experienced the disaster and what happened when
we experienced it. So there’s something about
the saliency of the indicators we use. We really focus on that
moment, those moments afterwards, not potentially
on the things which are a little bit more insidious
which we don’t notice, which could drag on over time. OK. What does it mean
for disaster policy? As I said, this is the
part that I probably don’t have as much to say on. I get to research
miserable things every day, but not as many positive things. Broadly speaking,
there’s kind of two, there’s two distinct
periods of concern when you think about any kind
of disaster or big shock. There’s immediately after
the first few months, that kind of stuff. And then there’s the
rest of the time. A lot of the policy focuses
on this immediate aftermath. So even rebuilding
policy is about rebuilding things that were
lost, not necessarily changing plans or zoning, particularly in
the US, to deal with six months after to the next 50 years,
in some cases, when you’re building power plants, roads,
lots of large infrastructure projects. The results that
I showed on what’s happening at the
macroeconomic scale, what’s happening to the
country’s income, are inclusive of every
policy that everyone has ever put in place to
deal with disasters. Despite that, we still
see this decline. So the reason that things might
be noisy right in the year after or the year around
a disaster happens, is because some of those
policies work, some of them don’t work. But they might be doing
a good job of smoothing over those initial few years. But it’s clear that because we
see this drag on the economy, that there’s something
that we’re not doing thinking about
long-term policies, either in the actions
we take immediately after a disaster,
which could benefit, reduce damages, reduce
economic loss in the long term, or the policies that we
have over the long term. So it seems like perhaps even
if we do one right immediately afterwards, we’re definitely
thinking of this six months to years afterwards. There’s is a really
interesting piece of research, which came
out last year looking at the effect of FEMA spending. And it finds that the stuff
that we spend ex ante, so risk reduction money– and this is I think
one of the first, there’s this whole global
movement on disaster risk reduction, which takes,
which posits that and takes, in some cases, for granted that
spending money on disasters before they happen reduces
damages in the long run, and it’s a better thing to do. It’s something which doesn’t
have a lot of research support. It’s very difficult
to try and find out the effect of a disaster that
didn’t happen because you invested in something. So there’s this great paper
looking at what happens with FEMA spending that happens
before a disaster– so risk reduction–
versus ex post, stuff that happens afterwards– recovery, reconstruction,
that kind of stuff– and finds that it’s twice as effective
at reducing damages, Which is pretty
cool, except even this is open to interpretation. Because the specific
projects and the amount that’s spent on
risk reduction is much smaller than the stuff
that’s spent afterwards. So maybe it’s only that people,
what we have in these data are only the absolute
best projects that people wanted to
spend their money on, not cleaning up
after every disaster. But it’s definitely a
really suggestive and really encouraging piece of research– that a lot of this could be
about planning and about risk reduction, rather than
dealing with the effects after they happen. OK. I’ll move on for
the last few minutes to talking about Puerto Rico. So Puerto Rico is most, as
I’m sure everyone in the room has heard, is going through
this massive debt crisis. It’s the largest debt
crisis in US history. Puerto Rico has a very
unique relationship with the mainland US– not a state, not independent,
somewhere in between– and has a lot of potentially
distortionary policies because of that. So in particular, trade
has to go through US ports. It’s very difficult for it to
set trade policy, or wages, or anything independently. So it’s a very unique case. And what happened last
September is, as we all know, was Hurricane Maria, so
one of the most active, one of the most damaging, I think
the most damaging hurricane season in the US of
these three big storms– Harvey, Irma, and Maria. And Maria hit Puerto Rico,
went completely over the island such that, effectively,
there was not a single person on the island
of the whole population that didn’t experience at least
a Category 3 wind speed. And that’s huge for
such a large area. That’s one of the
largest landfalling storms in terms of
energy experienced by everybody on the island
that’s ever been experienced. Because of the
debt crisis, there was an appointed group
under an act called Promesa that was meant to step
in, impose austerity on the economy, try to
deal with the debt crisis It was Senate appointed. They spent a couple
of years coming up with a financial plan, thinking
about how they would pay back the debtor’s, how they would
invest in the Puerto Rican economy, what the
tax base would be, very exciting things
thinking, trying to project what the
tax base would be. It turns out that that’s one
of the single most important things that you
could be thinking about when you’re
thinking about what’s happening with Puerto Rico. If the economic
growth slows down, the tax base is going
to be much lower. They can pay back less money. If it gets to the extent
where the debt that they have to pay back is so
large, is extremely large, it could push them into
an economic down spiral, which they might not
recover from a generation. It’s an extremely important
thing to think about. They came up with this
fiscal plan and said, OK, here’s what the Puerto Rican
economy is going to be like. Here’s where
population movements are going to be like
for the next two years. And they decided on that
in summer of last year after much negotiation. And then Hurricane
Maria happened and they effectively tore it up. So then the question
for them was, what do we think the economy
is going to do in Puerto Rico after we’ve had this? So not in next year,
not in the year after, but in the long term over
the course of these loan payback periods. So there was obviously
much concern. There was, as I’ve
kind of pointed out, not too much research on
that beyond the paper that I was talking about at the start. And so through some
people at the IMF who knew about this paper,
and had replicated, and shown that the results were
real, and through an op ed that the group
that I work with published in The I
York Times, they saw, OK, here’s where we
have a problem here. The economic projections,
the economic assumptions that we previously had are
going to be way off if this is actually born out. So here’s what
Hurricane Maria looked like in terms of the miles
per hour of wind speed. As I said, if you look
at something here, there was nobody on the
island who didn’t experience at least a Category 3. It went completely
over the island. This is what we
project would happen. So this dark gray
line is what was happening with Puerto
Rican income per capita before the storm. The storm hits here. This is just extrapolating
out the average growth rate of the last few years. So this is kind of the
what would have happened if the storm didn’t
hit, assuming that Puerto Rico was acting in
the same way as it was here. Here’s what our
results would suggest would happen with the economy
after 15 years, 20 years. So what they were interested
in is this gap here. We estimated that as the effect
of Hurricane Maria in 15 years from now leaving the
economy 21% lower than it would have been otherwise. So this is an enormous event
leading to enormous damage to the economy. Putting that in
context like we did before with some other
things, you know, this is on par with the
Asian financial crisis impacts on Indonesia. It’s up there with some of the
worst Great Recession effects that we saw in
the United States. This is something which
has major implications for the Puerto Rican economy. And so they put
forward a plan which would take this into account. The question that I asked at the
start, what happens immediately after a disaster, is
something that they have a big issue with. A lot of aid and
FEMA money came in. And that’s going to look like
there’s some kind of boon to the economy in that year. And so if you’re sitting
as one of the debt owners, you think, OK, their economy
is growing in that year. Disasters are good
for development because they have this view in
their mind of the economists that this means we’re
going to build back better and everything is fine. You could be sitting from the
point of view of the government thinking, OK, this
is good but it’s not enough money to rebuild. We’ve got this ailing
infrastructure. But let’s get as much as we can. People are thinking a lot about
what happens in that year. An important thing about Puerto
Rico’s political statuses is that a lot of the aid money
actually just came right back to the mainland US. It was a lot of jobs. It was, you know, ComEd going
there and rebuilding some power infrastructure. But they were teams coming
down from the mainland US. And so then you got
to try and understand how much of that FEMA
money that went in, out of the billions that went
there, actually stays in Puerto Rico and helps people. The answer is
probably pretty low, something like, something
between 10% and 20%. So of all of that aid money,
only about 10% or 20% of it went to Puerto Rico or
stayed within Puerto Rico. It also has this other
challenge of massive population movements. The population now is about
between three and four million. People are leaving
at a massive rate. And we still don’t
have good numbers on what’s going to happen. But it looks like the
island of Puerto Rico is going to have this
large population decline. So it’s got everything
stacked against them. And then thinking about
this hurricane effect makes it kind of
a thornier issue. So what they have
proposed is that, based on the money that
they’re getting in, they will have this
bump in year one. As that money stops, they
will have this big decline. And then they’re going to have
this low-ish growth rate, where there is some kind of growth
but their economy is diverging. So if you kind of ignore
what happens here– because as I said, this is
the part where it’s noise and it goes anywhere– they’re aiming to say,
give a range of scenarios, but one of the most likely
scenario is somewhere here– 21% lower. And what does that mean
for their debt payback? That’s something
which is, I think, they just released their
plan about a month ago. So we were working with them on
trying to understand just how unprecedented this effect is. Whether it’s true for small
islands, whether, you know, places like Grenada that had
experienced big hurricanes had recovered differently. Or just how unique
and unusual this is. All the evidence we can
find using the techniques that I showed at
the start points to this being a
real thing that will be experienced without some
major structural change. As I said, the plan
was just released in the past couple of weeks. All of those people
who own their debt are going to be facing
what you’d call a haircut. They’re not going to
get back all the money that they’re owed. If they try to get back all
the money that they’re owed, it could push Puerto Rico
into this economic spiral that they won’t
be recovered from. It could slow down the recovery. And so there will be over
the coming months pretty, I’d say, energetic
debate in courts, in Congress, in the
Senate about exactly what the implications of this are. But by and large,
they’re looking at this 21% number as
what the economy is going to be like in 15 years. OK. So some conclusions then. So disasters are
negatively effecting economies in the long run. This research was
for hurricanes. And I mostly focused
on hurricanes. But there’s some evidence
now that it’s also true for earthquakes, maybe over
slightly shorter time horizons. But a lot of these
long-run effects are showing up in
different things, not just the economy–
also in trade, et cetera. It’s remarkably generalizable
across countries. This is something,
this is a policy gap that we’re not understanding
for some reason. That as good as we get
at dealing with disasters immediately afterwards,
there is something which means that we don’t
deal with the long run in a way which is allowing
those economies to grow as fast as they were. There’s probably not one
reason why this is happening. As I showed, there’s
lots of different reasons why this can be happening. And it’s specific to
each different policy. So the National Flood
Insurance Program, for example, or the unemployment
insurance that’s happening in the
US, which I think is definitely a
good thing, but it’s leading to this drag on the
economy in the long run. That mechanism is probably very
different in other countries, based on their
specific policies. And then I think this is
something which is probably an enormous hindrance for
Puerto Rico going forward in the next 20 years,
particularly with this debt crisis that it’s facing. I think that’s where
I want to stop. And I’d be very interested,
in particular, discussion to have on thinking
about this policy. What is this policy gap? What are we doing in the
near term which is leading to this long-term effect? Or what are we not doing it
in the term which is leading to this long-term effect? And try to get some of
your perspectives on that. I think that’s it. AUDIENCE: Yeah, perfect. [APPLAUSE] AUDIENCE: Hello. My name is Charles. I have a question with
respect to Puerto Rico, in listening to
everything you said. And it’s like a
two-part question. First, do the negative
impacts of these hurricanes have a compounding
effect on each other? So like when you said
that it dropped 21%, if the hurricane was
to hit again next year, would that be another 21%? Will it compound? And if so, in some
way, could you predict a point in
which there would be a point of no
return for Puerto Rico? Like, it just totally crashes. AMIR JINA: Do you want
to ask both together or which do you want me to take? AUDIENCE: Yeah. You know, just. AMIR JINA: We could
do it with this. So it’s interesting. As a showed, there’s
this repeat effect, the impact that happens if you
get a storm right afterwards. So if Puerto Rico were to get
another storm today, in fact, this is quite similar
to what happened in Haiti after the earthquake. This hurricane went over and
people were extremely exposed, extremely vulnerable. Nowhere had been
rebuilt and people were living in large slums. And a hurricane came over. So you see this kind
of double impact. You could, with what we’re doing
here, come up with scenarios. So if a storm hit next year, you
can give a range of magnitudes. If a storm hit in two years,
three years, five years, you can give a range of
magnitudes for those. So we could definitely
do that, and think what’s going to happen to push
Puerto Rico extremely low? What will happen
at some point is that everything that can get– everything that’s
immediately exposed will start to be damaged. And if it’s not getting
rebuilt, then it’s going to be– there’s going to
be less to damage. So it will actually
look like Puerto Rico is becoming more adapted. So this is this weird
thing and the way we think about adaptation. We think about adaptation
meaning that damages are lower. But if damages are
lower because I’m Japan and I’ve invested in this
amazing infrastructure, then, I mean, the
good equilibrium– if damages are lower
because I’m Haiti and I don’t have that
much left to be destroyed, then I’m at bad equilibrium. But it kind of looks
like both of them are low damage scenarios. So that’s kind of what
starts happening in Haiti. If it’s too– sorry, in Puerto
Rico– if it’s too frequent, the point of no return
would be a difficult thing to kind of talk of anything
about, because of the way the capital’s not
getting rebuilt, because of the way people’s
behavior might change, that kind of stuff. But we could do something
which definitely looks at some scenarios for that. AUDIENCE: I’m curious. Were you just focused
on Puerto Rico? What about USVI? Because they were
affected by Irma and Maria pretty heavily as well. AMIR JINA: So we didn’t
focus on the Virgin Islands. This was kind of at the
specific request of Puerto Rico. This has come up a few times. So Fiji had a major hurricane,
maybe three or four years ago. And we write something
in the paper that says, this could be a
big deal for Fiji. And then it, I think, it
was discussed by the finance minister, like these
academics don’t know what they’re talking about. Fiji are going to grow
back and be amazing. And that’s not really, we’re
not trying to do it out of any form of criticism. So we can do exactly
the same projection for the Virgin Islands. I think because the reason
that Puerto Rico became– the reason that the people
working in Puerto Rico became so interested in
this was because they needed to make a
population projection and an economic
projection in order to think about how much
debt they would pay back. So USVI didn’t have
that same situation. AUDIENCE: Yeah,
that makes sense. That makes sense because
they were in major debt. AMIR JINA: Yeah. AUDIENCE: And USVI did not
end up in a major debt. SPEAKER 1: Exactly. NATALIE FOSTER: All right. So the live stream can hear you. AUDIENCE: So I’m curious why
the trend lines don’t have built in the expectation
of these disasters, especially the ones where
they have repeated disasters. AMIR JINA: So this is more,
this is kind of a display thing. We’re just showing
what the trend line would be with no disasters. But in that when I showed this
repeated disaster happening as the first disaster happens,
it pulls the GDP growth down And that becomes
the new trend line. And that’s the one that gets– that we divert off from. So it’s more a display thing. AUDIENCE: This was
a really great talk. AMIR JINA: Thank you. AUDIENCE: And my question
is, you’ve characterized this as an analysis of the
impacts of natural disasters. Have you also looked
at the impacts of human-caused disasters,
like terrorism, you know, on a large scale, small scale? Because there’s databases
out there that discuss that. AMIR JINA: So this is where my
cautious academic hat comes on. And I say, well, I don’t know
much directly about that. And then I try to change the
question about something else. But if I try to not
put on my academic hat, I think it’s important,
so thinking about– I characterize
this as disasters, but I specifically talk
about hurricanes a lot. And then there’s some, I’m
doing some work on flooding. I have a co-author doing
work on earthquakes. It’s important to think
about what’s particularly distinct about those. So I mentioned this idea
of Japan and bombing. So I believe terrorism fits
a little bit more into that. It’s a human-caused violence. There are a different
set of policies and a different expectation
about their return interval, probably. I will think about terrorism
very differently than I’ll think about a disaster. And so the policies
for dealing with them would obviously
be very different. In terms of what this
would do to and economy, I think because in
comparison the destruction is quite limited
from a single event, you wouldn’t see the same event. I mean the economic
damage from a hurricane that hits Florida is enormous. It would be hard
to cause that much with a single terrorist event. For a large-scale civil war
or a cluster of large events, you might be starting
to approach that. So that was why I
put this thing up in the context of a civil war. But I think to
answer your question, it would probably
be, they would be distinct for various reasons. The policy responses
would be different, if we’re thinking about
these long-term things. And I think that the
magnitude of the events, before they get
to a large scale, would probably put
them in a smaller range than what happens from
Harvey or Irma, for example. But it’s an
interesting question. People do look at it,
but not really thinking about economic growth. There’s a lot of other things
that happen to an economy when you enter a situation
of large-scale civil strife that could also be causing
degradation to the economy. AUDIENCE: So my question is
kind of going off of that, but more in regards
to your model and the counterfactual
[? sash ?] controls that you used. So did you take into account
the likelihood or existence of human-made
disasters or conflicts in the areas when you looked
at when these papers were run on a global scale? Or when you controlled for that,
did it just not matter enough? Or was it so small
in the aggregate that it wasn’t worth looking at? AMIR JINA: So
there’s, first of all, I’m glad to know that you
remembered all the terminology from the last quarter. But the- AUDIENCE: I’ll try to get this. AMIR JINA: Yeah. So it’s kind of
interesting in thinking about when I show this table
of the financial crises, other things like that,
a financial crisis can’t lead to a natural
disaster occurring. Natural disasters are
what we call exogenous. They’re kind of random. They’re external to the system. We can predict them
to some extent, but you can’t tell exactly where
a hurricane is going to happen. So the causality can’t go from
financial crisis or a conflict to causing a natural disaster. It could lead to extra
population vulnerability when a disaster happens. But you could also
think of the disaster or the environmental
thing leading to conflict, financial crisis,
currency crisis, something like that. So that’s potentially
one mechanism for– that’s potentially
a set of mechanisms for what you’re seeing here. You could think
of the other thing in Aceh, in Indonesia,
after the earthquake, it was famous for bringing
about– the earthquake was famous for bringing about peace. But essentially,
that the civil war, which had been going on
in Aceh for many years, people were so badly affected
that the costs of conflict were essentially
too high for people. So you could think of
it in some other way. But there’s potential
for some of those things to be mechanisms
here, in as much as they are driven by
the storms and the storms kind of happen out of nowhere. We’re picking up something which
is maybe inclusive of them, maybe independent of them. But the human caused
ones, rather than the storm caused ones,
are not going to trouble the estimates in any way. Because they are not related. Does that make sense? AUDIENCE: Yep. AMIR JINA: OK. AUDIENCE: But
doesn’t human affect on some of these
natural disasters diminish it heading forward? Like down in Houston,
where you know, they knew that they
were going to be more susceptible to flooding. And so what they did was
that they designed a way to build the roads down there
that draws the water away. So the next time you
have a natural disaster, the impact gets marginally
less, and less, and less. Haiti building codes,
they weren’t pretty much in existence before. Now all of a sudden, they
have building codes built in. And so every time you
have a natural disaster, you tend to get
more human input. Katrina, the Corps of
Engineers told them they should never have built in
certain parts of New Orleans. And they did anyhow,
because, again, humans have a very short memory. And after the parishes got
completely flooded and wiped out, the Corp recommended not to
building in those areas again. And what did they do again? They built in the
exact same areas. But you know, there’s
some sort of learning curve that does come from with
natural disasters in which, you know, they seem more
prone to anticipate them, to lessen their impact
based on technology. How does that figure on
the recovery process? AMIR JINA: So that’s a very– that question touches
on a lot of things. I’m going to try and make
sure that I hit as many of them as possible. So all of those things,
in as much as this is an exercise looking at every
hurricane impact in every GDP trajectory of every country, any
policy response that was made is included in here. So it seems like
all of those things, we don’t have the worlds
where Japan, for example, didn’t change its building
codes to have earthquake-proof buildings everywhere. And so it’s difficult to
estimate what would happen if they had never done that. What we’re doing here is
inclusive of all of those. So even with those things,
there’s some residual effect. But what you’re
saying is obviously, perfectly, it’s
absolutely correct. And this is something which has
been seen by some researchers. But it’s very
difficult to know when a disaster is going to trigger
that big policy response. We have two things. We have kind of the impact
and then we have the behavior. We can observe that places that
get more frequently exposed– or I do a lot of work on climate
change and weather impact. And you see places that
are hotter on average. You know, in Houston, they
have air conditioning. In Seattle, they don’t
have air conditioning. If Seattle got as
hot as Houston, they would all have
air conditioners. And so you’d see this
different effect of heat. The same is true for disasters. Like in Chicago, we’re not going
to build to protect ourselves from hurricanes. But if for some
really bizarre reason, hurricanes started
coming up here, we might start investing in it. So that’s true. And we can see that in
the data. that places that are more frequently
exposed are, they’re getting less damage for
each event that hits them. But what exactly triggers– I mean, that’s a whole set
of policies and behaviors that we’re picking up here. What exactly triggers
those specific ones? Or what ones are the
right policies is really like an open and
fascinating question. And that’s– AUDIENCE: The other thing
too is that the intensity of the storms, with the
climate change, which we, the Earth has always gone
through climate change. I remember when the
Russians were drilling toward the bottom of [? thaws ?]
at the inner Arctic, in which they found fossils of
plants known to exist only in [INAUDIBLE] weather. And so we know that there’s
been many times in which the Earth has been ice free. And so, you know, with
adding levels of water, you know, the form, intensity,
the magnitude of the storms are different than when
we have a lot of ice when winds are less. So it’s a always a
dynamic type change. We can never assume that the
that earthquakes will always be at this level. It may be at increasing levels. It may be at lessening levels. AMIR JINA: So on the
climate change thing, we do. So first of all, I’ll
say that the rate of the changes that we’re seeing
and the magnitude of changes that we’re seeing in the
climate are faster than anything that has been observed in
the history of the planet. And in particular,
they’re any changes which did happen before which
we see on some like graph which has a 10 million
years on the x-axis and we see these big changes. They’re happening over
the course of thousands or even millions of years. And so those changes were very
slow and allowed for people to adapt. The changes that we’re seeing
now and not only bigger in extent than some of
those, but also our species wasn’t in existence when
those things were there. So it’s a very, like the
experiment of turning up the thermostat on the
Earth at the moment is probably a bit of
a wrongheaded one. We look at that so that the
best evidence at the moment shows that the
intensity of hurricanes is going to increase. And so then we have
two things that relate to your previous question. You have places that always
get hit by disasters, but maybe they don’t
think that it’s in their best interest, because
it’s too expensive to make a policy or to build these
kinds of permeable roads, for example, or something. There will be places
that are experiencing more intense disasters and
so adopt those policies that wouldn’t before. So you’re going to see
the impacts decrease. But then you’re also
going to see the intensity and to some extent maybe
the frequency increasing, but mostly the intensity. So as they’re adapting, they’re
in this race against how much the intensity is increasing. And it’s unclear who
wins in that situation, particularly for infrastructure
investments, which are– we put down today
and it’s 50 years. If we’re not thinking
what the world is going to be like in 50
years, then we’re not engineering our
way out of the problem in the way we
should be, I think. AUDIENCE: Thank you. AUDIENCE: My name
is John Fitzpatrick. I’m actually in the
liberal arts program, but this is interesting, a very
thought provoking presentation and the work involved. And I’m curious
about your research I mean, we know from
thousands of years ago when earthquakes happened
in places like Greece, people just picked up
and left and migrated. So migration happened
and nothing was rebuilt where the earthquake
occurred for lots of reasons. But in places like
Houston, Harvey where the estimates are
that there’s huge loss, but we know that
$35 or $40 billion of the $70 to $90
billion of loss– and these are, one of the
cap modeling firms RMS that come up with
these numbers– $35 or $40 billion
was insured loss. And so that money starts
flowing in and buying wallboard, and construction
materials, and new cars, and all sorts of things. And we also know
that the government approve $36 billion more for
I think Harvey and maybe Irma. And I don’t know what
they did with Maria. But so there’s a lot of– we’re talking about $70 billion
worth of hard cash going into what is measured by GDP. And it is, hopefully,
some of it’s going into things
that are better construction, better building
codes, better infrastructure solutions. So I’m a little bit
surprised by the fact that, if there’s a high level
of insured loss, why you’re not seeing in the data the
immediate boost to GDP that comes from that. Because that money
goes right into GDP. It’s measured in GDP. It’s measured in national
income and personal income, whereas the stock of what
was destroyed is not in GDP. In other words, it’s
not a zero-sum game, you build back a house. The way it’s measured, the fact
that the assets got wiped out doesn’t subtract from GDP. So I’m really mystified
that the numbers don’t show kind of a boost in
GDP, while the building and construction is happening
after an event, where there are in places like America,
United States and Japan where it’s heavily insured. AMIR JINA: So again, another
question that touches on a lot of things. And I’m going to try and make
sure that I cover all of them. So one thing which I didn’t
quite talk about here but is kind of my working
hypothesis for what’s happening– and this broadly
orbits around your question. We have this idea. So GDP, which I
mentioned very briefly, you do see this
construction boom. So sometimes in the year after,
GDP looks like it’s increasing. That’s what a lot
of people would have said is this
build-back-better type of idea. But what’s happening
in a lot of those cases is that I have money to invest
in something, particularly, if it’s federal money. So there’s very low rates
of insurance for flooding. So a lot of the Harvey
damage, for example, was flooding damage. And people just don’t
buy their insurance. It’s not priced right. And they also know
that in the case of a big flood
like this one was, the government is
going to bail them out. And that’s what happens
often with the National Flood Insurance Program. People don’t buy in a
lot of disaster areas, because they know
that the government is an automatic
insurance mechanism. So that’s one thing– the level of
insurance is too low. But if you think
about it then as– I’m going to use the word
counterfactual again– what would have happened if
we didn’t build this fantastic factory? So before I said
build-back-better idea was you have a bad factory. It gets knocked down. You build back a
much better one. It’s more productive. But where did that
money come from? And what would have
happened if we didn’t experience that disaster? If we didn’t experience
that disaster, we would have had a bad factory
and a really good factory. It could have been
invested somewhere else. And so in particularly in the
case of a federal disbursement of funds, you’re
seeing that money which could be going to some
other productive investment somewhere else is going
towards rebuilding things. So that’s one part of it. And that might be one reason
why we see this, that’s like a misallocation issue. And that might be one reason
why we’re seeing this. Another reason why we might
not see a boom that is lasting is because of precisely what’s
insured and what’s not insured. So we see it in
the immediate term. But as I said, some
of these mechanisms are people going on unemployment
insurance, for example. So the people who
would be uninsured might be the reason why
there’s this slow down effect on the economy. And then the other
reason probably being like low-ish levels
of insurance, given the risk that people in
different places are facing. So there’s many reasons
why you’d see that. But you’re definitely
correct you do see this boom in construction. And often after a
disaster you see, particularly driven
by construction, you see this big spike in GDP. And then kind of nothing
in the subsequent years, because what’s the
damage and what’s missing doesn’t get counted. Did that touch on? AUDIENCE: Well, I guess
I’m thinking about the fact that we live on planet Earth. And Earth has
windstorms, earthquakes. And they have
happened in the past. They will happen in the future. And so there is no state
where there are no storms. And that comparison
to me is less useful because that state of
the world doesn’t exist. So it seems to me what
matters is these things are going to happen. I completely agree with you
about the climate change and the intensity and the
severity of the storms will go up, particularly in
the areas that are populated. So it’s all about how do
we finance these losses? Should we, pre-event,
do loss mitigation? And it looks like
you’ve got evidence that says it’s valuable to do that. Should you finance
for it in advance by buying insurance and
having tens of billions, hundreds of billions available
to flood in to the economy and rebuild better? It seems to me those are
things that do make sense. But we know governments don’t
buy insurance pre-event. They barely have enough
money, let’s say– let’s use Chicago, or
Cook County, or Illinois as an example– they barely have enough to pay
for their current operating expenses. And rarely do they have the
money to pre-event or pay for a one in 100 year event. They just won’t do it. And yet that’s what
they should do, because what they
have to do later is increase taxes, which cause
migration and so on post-event if they finance that way. That’s the history of
some of this elsewhere. AMIR JINA: So I completely
agree with you, that the– and this is probably
the place that I like I’m interested
in a discussion going, because we are seeing this
residual effect in the long run because there’s
some policy failing. And insurance in this country
in particular and many others is it’s not accurately priced
for environmental risk. It’s low. People are assuming that
the government is going to bail them out in many cases. And so it’s not optimal. And that’s kind of the situation
with a lot of the policies we have. They’re not optimal. A lot of the building and
urban planning in Houston was also not optimal, knowing
what the flood risk was. So there’s this
social planner view that we need to increase
insurance penetration. We need to plan properly. And that might be
the policy that deals with this or
the set of policies. And I think that’s the
right place for a debate to go after something
like this happens. Not for all the media and
everyone to focus on– I mean, they
rightly should focus on making sure people are
safe in the near term. But to very quickly
try and turn it into, how can we stop this
from happening again? And as you said, these
things happen all the time. But we know that enough. And we know that
there’s a set of things that work, a ways for us to
pool our risk through insurance, that would actually be very
good policies to adopt here. So that’s one thing. I completely agree
with you that we’re in a suboptimal world
in terms of policy and in terms of how we
think about these things. On a related note, there’s– so I say that as the
dispassionate social planner with some welfare function
of everybody in mind. And I want to improve
everybody’s welfare. And then I’m going to say,
oh, well, you are living in– the marginal person living in
Puerto Rico, I’m going to say, no, you’re living
in the wrong place. I’m going to move you over here. But that’s completely ignoring
then the human side of this. The reason why people would stay
in New Orleans without a job is because of their social
network, these other things– amenity value,
familiarity of place, family, all these
other things which the dispassionate economic,
social planner wouldn’t see. So it’s also
important in thinking about that kind of stuff. I mentioned that the National
Flood Insurance Program, where you have people
whose houses have no value and can’t move. And we say well,
you’re the problem. You’re getting a grant every
year to rebuild your home. And they could turn around and
say, like, I can’t go anywhere. My family is here and
my social network, my social structure is here. I can’t get access
to anything else. It’s important to
think of those things when making the policy as well. So not just thinking what
the optimal policy might be, but what is that optimal
policy actually acting on and what context it’s acting in. So I completely agree
with you that we’re in the suboptimal
world, but also that the set of things
we view in order to get us that optimum needs
to be much wider than the ones that we typically think of. AUDIENCE: Hi. I had a question
about the slide you showed about the repeated
exposure to storms. And specifically,
I was wondering what the effect of the time
between two storms was? And my initial
impression would be that as the time increases
between the storm, the effect on the GDP over the
long term would be stronger. But I was wondering whether
that’s reflected in the data or not? AMIR JINA: So now you point out
all my statistical failings. What we assumed for
that was this thing called additive separability. So that one storm
happens and it’s not interacting with the
next storm that happens. And we estimate this effect. What we’d need to do to estimate
what you’re talking about is try to look at
the return period. So we kind of do that in
terms of the average frequency of storms. And we see that the ones
that get a lot of storms have these lower damages. But that doesn’t really say– that means on average
over a really long term. What that doesn’t
really say is, what happens if, again
by random chance, like in the question that came
up earlier, if Puerto Rico was to have a storm, had this
storm last year, and was to have one next year, versus
having one in 15 years time, and what the difference
would be there. And the answer is, I don’t know. So part of the
reason for that is that it’s a difficult
thing to estimate with any kind of precision,
to say something. And you could imagine it
going kind of both ways. I think the question
earlier about what leads to a policy
change, I think, that’s an important question
for people to start looking at. It’s something that I’m
interested in looking at. Maybe it’s the case that two
disasters right after the other leads to this change in building
codes or change in something that helps us in the long run,
in a way that one disaster and then one 15
years later doesn’t. But it’s a question that I
don’t know the answer to. But I think one
that’s very important. MARSHA HAWK: I think we
have time for one more. You had your hand up before. AUDIENCE: Of for
goodness gracious. MARSHA HAWK: The last question. It’d better be good. AUDIENCE: Well, that’s
too much pressure. I was just thinking
back on that race you’re describing of
adaptability versus escalation of climate change, and looking
at the policy that we have, and the political
moment we’re in, and the fact that that
escalation of climate change is being called into
question right now. I’m wondering, did
you look in your model at all at how the gravity of
the situation is going to change and how the economic effects
might increase over time? AMIR JINA: So that’s
a great question. I love talking about
climate change. We do look in the paper some
climate change projections for what’s going to
happen to storms. And as I said,
there’s this result that the intensity
will increase, the frequency
probably won’t change for various
meteorological reasons. We project out into the future
what effect that would have, but with a very
strong specific set of assumptions, which is that
people aren’t going to adapt. We just kind of look
at what the risk is if you dropped climate
change on top of people now with no policy change. And so that makes
it something which is suggestive of
how important it is, but not probably a good
prediction of the future. So for that suggestive
exercise, there is a kind of a
well-known paper by one of the forefathers of thinking
about climate change impacts on the economy, called
Bill Nordhaus at Yale. And I think he
put the value of– I’m probably going to
get these numbers wrong– and he put the value
of climate change to the global economy at
something like $15 trillion. And we find an extra $9 or $10
trillion because of our effect. So just to put
those side by side, we think this growth
effect is enormously important financially
and enormously important as a climate change impact,
and one which has never really been included before. But it’s not something
that I would stand behind and say this is what the
future will look like. So I think we explored
it to the extent that we think it’s
important and should be on the forefront of people’s
mind, but not to the extent we would say here’s the
direct policy from that. I think more generally,
well, while we’re on the topic of climate change,
so it will increase risk to some extent for these things,
also for a lot of other stuff. So the other part
of my life is really trying to solve the
issue of how to use data to inform what the
costs of climate change are. We’ve got this enormous
project with about 25 people working on it now,
trying to do just that, to come up with
this thing called the social cost of carbon. The political moment
we’re in is one such that the current
social cost of carbon, this measure of the damages
from climate change, has been effectively
set to zero through some anti-scientific
manipulations of the methodology. And that kind of thing,
to leave everyone on a really
optimistic note, there is an erosion of the previous
climate change denial debates back and forth. There was always some
recourse to data. Now it seems like– or to facts. Now it seems like we’re entering
a world in which facts just don’t matter, which is
hard for someone who tries to generate them for a living. But it’s a pretty
worrying time to see that those kind of things
are being disregarded. This kind of research
has filtered its way into how the Puerto
Rican government is thinking about their future. And that’s a really
positive sign, probably more positive than
what the outcome is. But it’s a rare case where
someone will go and pull a number out of
a research paper. So it’s a big issue. And it’s a worrying time. It’s good to see people
dealing with this rigorously in some way. And I can only hope
that the future brings more of a view back
towards what facts have to say. [APPLAUSE] MARSHA HAWK: Thank you, Amir. Thank you for helping
us to understand the relationship between natural
disasters and economic policy. I learned a lot tonight. And I’m sure everyone
here did as well. So again, let’s give him
another round of applause. AMIR JINA: Thank you. [APPLAUSE] MARSHA HAWK: You can stay
around to answer any questions for a few minutes longer. AMIR JINA: Sure. MARSHA HAWK: Great. Well thank you everyone. My name is Marsha Hawk. And I am the director
of the University of Chicago’s Master of Science
and Threatened Response Management program. We are sponsoring
this event tonight. So thank you for all coming out. As my colleague Natalie
mentioned earlier, we have a number
of elective courses that we would like
to introduce you to. So please stop by
our table in back and pick up information
on the program. You’re able to take courses
outside of the degree program if you’re interested in joining
us is a student at large. Or for those of you
who are currently University of
Chicago students, you may actually take them
as elective courses in your program. So that pretty much
concludes tonight’s event. Thank you for coming out. And I’d also like to thank
those who are joining us via live stream this evening. And I hope that you will join
us for events in the future. Thank you. AUDIENCE: Thank you. [APPLAUSE]

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