Congressional testimony on economic consequences of climate change

Since it's basically a blog post, here's the oral testimony I gave last week to the House Budget Committee during the Hearing on "The Costs of Climate Change: Risks to the U.S. Economy and the Federal Budget." If you have hours to spare, you can watch the whole hearing or read the full (referenced) written testimony. It's not every day that someone asks you summarize a decade of research progress from your field in 800 words, so it seems worth documenting it somewhere.

Thank you Chairman Yarmuth, Ranking Member Womack, and members of the Committee for inviting me to speak today. 

My name is Solomon Hsiang, and I am the Chancellor’s Professor of Public Policy
at the University of California, Berkeley and currently a Visiting Scholar at Stanford. I was trained in both economics and climate physics at Columbia, MIT, and Princeton. My research focuses on the use of econometrics to measure the effect of the climate on the economy. 

The last decade has seen dramatic advances in our understanding of the economic value of the climate.  Crucially, we now are able to use real-world data to quantify how changes in the climate cause changes in the economy. This means that in addition to being able to project how unmitigated emission of greenhouse gasses will cause the physical climate to change, we can now also estimate the subsequent effect that these changes are likely to have on the livelihoods of Americans. 

Although, as with any emerging research field, there are large uncertainties and much work remains to be done. Nonetheless, I’d like to describe to you some key insights from this field regarding future risks if past emissions trends continue unabated. 

First, climate change is likely to have substantial negative impact on the US economy.  Expected damages are on the scale of several trillions of dollars, although there remains uncertainty in these numbers. For example, in a detailed analysis of county-level productivity, a colleague at University of Illinois and I estimated that the direct thermal effects alone would likely reduce incomes nation-wide over the next 80 years, a loss valued at roughly 5-10 trillion dollars in net present value. In another analysis, a colleague from University of Chicago and I computed that losses from intensified hurricanes were valued at around 900 billion dollars. Importantly, these numbers are not a complete accounting of impacts and other notable studies report larger losses. 

Second, extreme weather events are short-lived, but their economic impact is long-lasting.  Hurricanes, floods, droughts, and fires destroy assets that took communities years to build.  Rebuilding then diverts resources away from new productive investments that would have otherwise supported future growth. For example, a colleague at Rhodium Group and I estimated that Hurricane Maria set Puerto Rico back over two decades of progress; and research from MIT indicates that communities in the Great Plains have still not fully recovered from the Dustbowl of the 1930s. As climate change makes extreme events more intense and frequent, we will spend more attention and more money replacing depreciated assets and repairing communities. 

Third, the nature and magnitude of projected costs differs between locations and industries.  For example, extreme heat will impose large health, energy, and labor costs on the South; sea level rise and hurricanes will damage the Gulf Coast; and declining crop yields will transform the Plains and Midwest. 

Fourth, because low income regions and individuals tend to be hurt more, climate change will widen existing economic inequality.  For example, in a national analysis of many sectors, the poorest counties suffered median losses that were 9 times larger than the richest.  

Fifth, many impacts of climate change will not be felt in the marketplace, but rather in homes where health, happiness, and freedom from violence will be affected.  There are many examples of this. Mortality due to extreme heat is projected to rise dramatically.  Increasingly humid summers are projected to degrade happiness and sleep quality. Research from Harvard indicates that warming will likely elevate violent crime nationwide, producing over 180,000 sexual assaults and over 22,000 murders across eight decades. Colleagues at Stanford and I estimate that warming will generate roughly 14,000 additional suicides in the next thirty years. Increasing exposure of pregnant mothers to extreme heat and cyclones will harm fetuses for their lifetime. These impacts do not easily convert to dollars and cents, but they still merit attention. 

Sixth, populations across the country will try to adapt to climate change at substantial cost.  Some adaptions will transform jobs and lifestyles, some will require constructing new defensive infrastructure, and some will involve abandoning communities and industries where opportunities have deteriorated. In all cases, these adaptations will come at real cost, since resources expended on coping cannot be invested elsewhere. 

Lastly, outside of the US, the global consequences of climate change are projected to be large and destabilizing.  Unmitigated warming will likely slow global growth roughly 0.3 percentage points and reduce political stability throughout the tropics and subtropics. 

Together, these findings indicate that our climate is one of the nation’s most important economic assets. We should manage it with the seriousness and clarity of thought that we would apply to managing any other asset that also generates trillions of dollars in value for the American people. 

Thank you.

Climate impacts research is getting real

A few recent examples of our research getting out of the ivory tower and into the real world. This came up in a recent seminar I teach, so it seemed like others might appreciate the update.

1. The NYT sent some journalists to India to do a story following up on Tamma Carleton's recent work on climate and economic drivers of suicide in India.  This is powerful and humanizing work by the Times making hard-nosed numbers appropriately real and heartbreaking. Some of the striking one-line quotes they obtained from personal interviews:

"I go without food more days than I eat"

"If I were to take out any more loans, the interest would grow, and my whole family would be forced to kill themselves."

2. Last week the US Government Accountability Office released to congress the report Climate Change: Information on Potential Economic Effects Could Help Guide Federal Efforts to Reduce Fiscal Exposure. The report drew heavily form the American Climate Prospectus that we published a few years ago and our recent paper on US costs of warming. The GAO summary concludes:

Information about the potential economic effects of climate change could inform decision makers about significant potential damages in different U.S. sectors or regions. According to several experts and prior GAO work, this information could help federal decision makers identify significant climate risks as an initial step toward managing such risks. This is consistent with, for example, National Academies leading practices, which call for climate change risk management efforts that focus on where immediate attention is needed. The federal government has not undertaken strategic government-wide planning to manage climate risks by using information on the potential economic effects of climate change to identify significant risks and craft appropriate federal responses. By using such information, the federal government could take an initial step in establishing government-wide priorities to manage such risks.

3. Trevor Houser and I recently estimated the potential long-run economic consequences of Hurricane Maria on the economic growth of Puerto Rico and published an op-ed explaining the issue and putting the event in context. Basically, I ran my LICRICE model to compute wind exposure across the island, which totals 123 mph max wind speeds on average across the entire territory. For a territory of this size, especially in the Atlantic, this is unprecedented in my data.

Then we applied these numbers to the results of work with Amir Jina on the macro-economic effects of these storms. If you were take central estimates from our benchmark model, the picture is a 21% drop in GDP per capita, relative to trend, over the next 15 years. Based on the low pre-Maria growth rate, we estimate that this storm undid roughly 26 years of growth in under 12 hrs. As stated in the op ed 

"Almost nothing on the planet, short of nuclear weaponry, destroys economic value as rapidly as a mega-hurricane."

Evidence Should be Used in Global Management of Endangered Species: reply to the CITES Technical Advisory Group

In anticipation of the 17th meeting of the Conference of the Parties of the Convention on the International Trade in Endangered Species (CITES), the CITES Technical Advisory Group (TAG) on elephant poaching and ivory smuggling released a document (numbered CoP17 Inf. 42) in which they directly addressed a working paper released by Nitin Sekar and myself.

The document did not introduce new substantive arguments (see end of post for one exception regarding dates)—in fact, the document’s claims were nearly identical to those made in Fiona Underwood’s prior blog posts about our analysis (here and here). In her second post, Dr. Underwood (one of a handful of members of the TAG) openly states that the TAG asked her to evaluate our analysis, and it seems they have simply adopted her view as the official stance. These arguments provide the basis for the TAG's conclusion:

13) The claims in the working paper by Hsiang and Sekar are fundamentally flawed, both in logic and methodology. The MIKE and ETIS TAG is therefore of the view that the study should not be used to inform CITES policy on elephants.

Given that the arguments have not changed, we have previously responded to almost all the document’s claims in our two prior blogposts, here and here. Below we summarize the relevant points and address new points.

As shown below,

• numerous statements about our analysis (either in the manuscript or follow-up analysis in these prior posts) made by the CITES white paper are factually incorrect;
• in supporting its narrative, the white paper misreports results and conclusions of other studies;
• the white paper makes erroneous statistical arguments;
• when the approach advocated for in the white paper is correctly implemented, it provides results virtually identical to the original findings in our analysis.

Thus, overall, there is no evidence to support the claims in the CITES white paper and therefore no reason for CITES to refuse to consider these results when developing policy.

Do guns kill people or do people kill people? An economist's perspective

Marshall and I think a lot about the economics of violence, so when the debate about gun control started on House of Cards, I started considering the classic,

"Guns don't kill people, people kill people." 

I mulled over this a bit and got in a debate with my wife since it didn't seem immediately obvious to me what this statement meant and whether it was testable.

I think the economist's take on the statement is that guns are a "technology" used to "produce" murder. This framing made it easier for me to think about what people meant in a way that had some testable predictions.

If "people kill people," that means there are other technologies out there that are pretty similar to guns and can easily be used to produce murder. In econospeak: guns have substitutes. This could happen for two reasons. First, either there are other technologies that produce murder at similar cost, where costs include both the psychological burden of committing murder and the convenience of gun technology, in addition to actual dollar costs. Alternatively, there might be technologies out that that are much more costly than guns (think: committing murder with a knife probably has different psychological costs), but the "demand" for murder is so high that people are willing to use those much more costly technologies to get the job done, i.e. demand for murder is inelastic. If this is true, then raising the cost of gun technology (e.g. strengthening gun control measures) won't save lives since people will be so motivated to produce murder they'll just use the alternative technologies, regardless of whether they they have to pay a higher cost of doing so.

If "guns kill people," I think that means gun technology is so much better than the next closest substitute that simply the presence of guns affects the likelihood that murder is produced. In order for this to happen, it seems you need two conditions to hold. (1) People would have to be willing to commit murder if they can use a gun, but not if they can't (demand for murder would have to elastic) and (2) gun technology must substantially lower the cost of committing murder relative to the closest substitute (seems likely to me). If these conditions are true, then one could effectively reduce the total production of murder by raising the cost of using gun technology, forcing people to use costly alternative technologies. If demand for murder is elastic, then some marginal would-be-murderers will find it's not worth the trouble and lives will be saved.

This led me to an alternative framing of the original statement, which seemed much more tractable to me:

"Are guns and knives substitutes?"

My curiosity piqued, I stayed up late hunting down some data to see if there were any obvious patterns.

I found the FBI Uniform Crime Reports, which tabulate homicides by weapon used for each state in Table 20. I created a state-by-year panel for 2005-2014, converting homicide counts into rates with census data, which goes up until 2010. I needed a measure of the "cost" of gun technology, and after a little hunting around (there is amazingly little data on gun-related anything) found Okoro et al (Pediatrics, 2005) which estimated the fraction of homes with a loaded firearm present using a randomized survey.  Obviously, there is a lot of other stuff that goes into making gun use costly, but it seemed to me that having a loaded gun in the house would dramatically lower the cost of using the gun for murder compared to the alternative situation where a gun had to be located and obtained prior to the act. The data set I put together is posted here in case you want to mess around with it.  (I imagine an enterprising graduate student can analyze the time series variation in this data, but I ended up collapsing this to a cross-section for simplicity.)

The first thing I did was to plot the homicide rate (where a gun was the weapon used) for each state against the fraction of homes with a loaded weapon present. Maybe someone has done this before, but I was struck by the plot:

The slope of the fitted line is 0.18, implying that a 1% increase in homes with a loaded firearm is associated with and average 0.18 additional annual gun murders per 100,000 state residents. This might not be a causal relationship, it's just a correlation. But the the idea that "guns don't kill people, people kill people" has the testable prediction that "guns and knives are substitutes." If this is true, then we would expect that in the states where guns are less accessible, people simply commit murder with other weapons. If we assume for the moment that people in all different states have similar demand for murder, then the substitutability of guns and other weapons would lead us to expect to see this:

Maco, Multipliers and the Environment

A little follow up from my post the other day:  It's probably going too far to say investment to curb climate change, if made during a depression, is a free lunch.  But certainly the basic benefit-cost analysis for what constitutes the most efficient policy with respect to climate change, or any other environmental or public good, changes when there is another massive market failure at play.  Spending to reduce emissions would seem to have two benefits: reduced externalities plus closing the macro output gap.

In some ways it feels a little like the so-called "double-dividend" hypothesis: the idea that taxing pollution can solve the environmental externality while raising revenue that can reduce distortionary income or sales taxes.  That rather compelling idea still gets kicked around a lot, and there is probably a small truth to it, although the calculation turns out to be more subtle (see Goulder's review, for example).

At first blush, the macro double dividend seems like it could be much larger.  As the late James Tobin apparently used to say, it takes a lot of Harberger triangles to fill and Okun gap.  The old double dividend literature dabbles with the former, and now we're talking about the latter.  I'm not familiar enough with the literature to know whether that have been attempts to bridge these vastly different areas of economics.  It strikes me as a difficult thing to do.  And even if it were done well, likely hard to publish due to the macro wars.

Still, if environmental policy were to be structured with macro multipliers in mind, it could change the entire calculus about the relative benefits of standards versus prices, especially if one would induce more spending in the near term.  It might also alter the implications of uncertainty.  Standard micro analysis, which is fashionable in environmental economics, favors delayed timing of investments, but with small economic values at stake.  The macro effect would strongly favor investment now, with presumably big economic stakes.

Of course, there are public goods besides reducing environmental externalities.  Spending on basic infrastructure like roads, bridges, tunnels and railways might have similar double dividends.  So how do we more generally evaluate the costs and benefits of public policies in a depressed economy, assuming (as I would) that macro output gaps are real may be with us for awhile?

I don't know the answer to this question.  But there would seem to be a lot more to it than measuring multipliers.  So, who are the brave, inquisitive souls willing to dive in?

Taking action on climate change

The Obama administration is side stepping congress and finally doing something about climate change.  The "action plan" has a nice outline of strategies, but no specifics.  It will be interesting to see what kinds of rules the EPA and DOE roll out in response to this initiative and how they will be justified under existing laws like the Clear Air Act.

Precedent for this kind of action was established by the Supreme Court awhile back.  If the Obama administration didn't take action soon, agencies would be sued by environmental groups and forced to do something.  So this kind of thing was bound to happen, one way or another.

In response, Paul Krugman makes an interesting and surely controversial point.  The new rules, whatever they turn out to be, will make energy more costly.  That's not to say action shouldn't be taken, but that there are tradeoffs involved with curbing climate change.  Krugman argues, however, that because these are not ordinary times, the costs may be considerably less.  Indeed, these rules may actually benefit the rest of the economy, not hurt it.  In other words, action on climate change could be free lunch.

Yes, this violates one of the first principles of economics.  But that sort of thing might actually happen when we have a depressed economy and vast inefficiency to begin with.  His reasoning is that we have too little demand right now, so that investments into alternative energy or carbon capture would employ resources that would otherwise sit idle.  And once those idle resources are employed, the economic activity they would generate would grow real income.  Put another way, since aggregate demand is insufficient, investments to curb global warming do not displace other kinds of investments and instead just add to GDP.

Environmental economists don't think this way, probably because depressed economies don't happen very often, and so the field pays little attention to macroeconomics.  But since the economy is depressed and likely to stay that way for at least another year or two, it does seem like a good time take action. After all, as Krugman likes to remind us again and again,  the latest evidence shows Keynesian ideas to be stronger than ever.  Maybe we should eat that free lunch while we can.