The Disaster Profiteers: How Natural Disasters Make the Rich Richer and the Poor Even Poorer

by John C. Mutter

  Using the graph and adding the effect of a capital shock, we see in Figure 2 that the capital shifted left to kD, the amount remaining after the disaster. We could say the capital loss is the difference between the equilibrium and the new capital, Dk = kD – kE. The same could be achieved by making the capital-widening line steeper by increasing depreciation of the capital stock. That would push the dot that is the point of intersection of the savings function with the capital-widening line to the left as well and have the same effect on production. Here we can say it was lowered by an amount Dq to qD.

  Figure 2. The effect of a capital shock ∆k on output ∆q. Output has dropped by the amount ∆q, an amount that is determined by the shape of the growth curve that is governed by the utility function, explained above.

  So the disaster does lower economic output, at least in the short run. It is fairly obvious also that the loss of output will be greater in this model for greater capital losses. Your position on the upper curve when a disaster happens matters a great deal. Imagine that the capital-widening line was less steep, caused, for instance, by a reduction in population growth rate, n. (Other things could cause the line to be less steep, of course.) The black dot in the center of the diagram would then move to the right and be on a flatter part of the curve. The amount of output loss is a direct function of the shape of the curve. If I moved everything to the right, the same Dk will have much less effect on output. That’s shown in Figure 3. What the figure expresses is that the loss of capital matters a lot less when an economy already has a lot of capital; the same point that was made in Appendix I using different graphics. And it is essentially the opposite of the effect of additions of capital in the Solow-Swan system: The marginal return on capital is smaller when you start with a great deal of capital; the marginal loss also is small when you have a great deal of capital to start.

  Figure 3. The same amount of capital loss occurs in this depiction, but the drop in output is much less because returns to capital are much more modeled on where the utility function is very flat.

  If you look at Figure 2, which shows the first way we considered production loss resulting from capital loss, you see how this might come about. Although you have fallen to a lower position on the production curve, that part of the curve actually has a steeper upward slope. The slopes are the dot-dash lines.

  Even though you have dropped to a position of lower production, you are now at a place on the growth function where output growth is more rapid for a given capital input, just as capital additions should be more effective in poorer economies. So capital was lost, but growth rate increased. That increase means you will experience a growth spurt from any new additions of capital (from disaster recovery assistance, say) and quickly get back to where you were. That quick recovery matches the thinking about getting back to the predisaster growth trajectory discussed before. In Figure 4 we see it is because the economy has moved to a state where returns to growth from capital input are greater.

  Figure 4. The effect of output on capital loss is the same as in Figure 2. Note that the slope of the utility function designated by the dash-dot line is actually steeper where output is, in an absolute sense lower.

  The Solow-Swan growth model predicts that poor countries should be growing very rapidly; many, however, simply are not. In fact, many are mired in stagnation, and some are even going backward. Jeffrey Sachs, the outspoken economist and director of Columbia’s Earth Institute, thinks that it is because at extremely low levels of capital accumulation, capital-based growth doesn’t work anymore. For additions of capital to be utilized effectively, a country needs some basic infrastructure of roads and ports and factories and a minimally literate, reasonably healthy population of workers. Sachs suggests there is a threshold of capital below which returns to capital may be low. Figure 5 is from the same study by Sachs and others. This curve is now S-shaped instead of L-shaped, with a very steep high-growth section in the middle and regions of low growth at the beginning and the end.

  Figure 5. Depiction of the Solow-Swan exogenous growth curve, but with a modification near the initial point of the graph to include slow growth at low capital levels that induce a poverty trap.

  The critical capital threshold is kT. Below that level, individual savings are below the capital-widening line, which means the economy is going nowhere, even with positive (but not high enough) capital investments. Sachs (and he is not alone) argues that economies on the wrong side of the critical capital threshold kT will experience poverty traps, which generally are defined as “any self-reinforcing mechanism that causes poverty to persist.”3 Many mechanisms can cause poverty traps. The health trap is perhaps easiest to grasp. People who are ill cannot work to earn income; if they are young, they cannot go to school to gain skills. That means that illness will likely lead to income reduction. But if you live in a poor country, you are much more likely to become ill because of poor levels of sanitation and low levels of health services. So poverty will cause you to be ill, but then your illness will cause you to be poorer still. The gray area on the diagram is the region of the poverty trap. Sachs’s argument is that, in this region, savings rates are just too low relative to population growth for places in this condition to get ahead.

  Figure 6. The same magnitude of capital shock ∆k is shown in poverty trap scenario. The output loss is now very large and has the potential effect of sending an economy from outside a poverty trap into such a trap.

  Now we finally can add the effect of disaster capital losses in this scheme. Look at the next graph. Three things are evident. One is that there is a dramatic drop in production for the same loss of capital, Dk, because the loss happens across the threshold on the steepest part of the production curve. Second is that because returns to capital are negligible in the poverty trap setting, loss of capital has little effect. This finding might explain why it sometimes seems that poor countries don’t suffer development setbacks as a result of disasters. Again, these invisible setbacks are like development in reverse. Because additions of capital don’t help a great deal in a poverty trap, losing a great deal of capital doesn’t matter much either.

  This finding gels with an idea put forward by Stéphane Hallegatte and Michael Ghil, but not about poor countries.4 They analyzed the effects that disasters have at different stages within the business cycle that is common in developed economies. It often is observed that businesses typically go through cycles in which good times follow low times follow good times, and so on. The cycle doesn’t have to be boom and bust exactly, but a cycle is evident all the same. So you can ask: Would you rather have a disaster happen during a good time or a low time? Almost everyone, including me, would answer in the good time. But Hallegatte and Ghil suggest that the opposite is true.

  They suggest that in good times, when things are going well, the economy is at full capacity and there is no excess capacity available. But in poor times, there is excess capacity. That may mean unemployed people sitting around waiting for work, idle machinery, empty retail stores, and the like. In boom times, the economy is already working at full tilt, and there is no one available to deal with a disaster. If a disaster happens in low times, there is capacity to deal with it.

  The third and possibly most important insight the last graph gives us is that capital losses that would have little effect on a highly developed country well to the right of the threshold can throw a country near the threshold from a growth situation into a poverty trap. The steeper and more precarious the middle part of the S-shaped curve is, the more dangerous it is to be near it. If you have just been able to claw your way out of the poverty trap, you want to get as far away from the edge as you possibly can. Even a small step backward can send you down into the trap again.

  The important point here is the difference between the factors that can put you into a poverty trap and those that can keep you there. A disaster can throw a society into the chasm of a poverty trap. Once there
, the mechanism by which individuals are kept from climbing out may have little to do with the disaster itself.

  Of course, this same S-curve can apply to different people in the same country or different economic sectors in the same overall aggregate economy. Everywhere countries contain both poor people and rich people. Rich people live well to the right of the threshold; poor people live near the threshold or to the left of it. The poor experience losses from a disaster very differently from how the rich experience them.

  Acknowledgments

  This work would not have been possible without the persistent, almost relentless encouragement from my agent, Elizabeth Evans. I probably never would have begun the project at all were it not for discussions with her, and I certainly would not have finished it without her support.

  I have been deeply informed by discussions on the subject of natural disasters with Sonali Deraliyagala, author of The Wave, with whom I teach and do research at Columbia University, and with whom I traveled to Myanmar to understand the effects of Cyclone Nargis on that country. I worked with Elisabeth King, now at New York University, on a project comparing natural disasters and civil conflicts from which—including many deeply meaningful conversations—I learned how similar yet different these two events can be. Before beginning this project I worked with Kye Borang on a project that looked at disasters along a human rights axis, and that work was the opening for thoughts about disasters and injustice that salted many themes in this book.

  I benefited tremendously from extensive discussions and travel to New Orleans with Richard Garfield, currently at the Center for Disease Control, but formerly at Columbia’s Mailman School of Public Health. I know no one more dedicated to understanding how to respond to the trauma of the disaster moment and minimizing the threat to life that it poses.

  I particularly want to acknowledge Stacy Parker LeMelle, with whom I traveled to New Orleans several times, and who, through her network of local friends and her skill and diligence at discovering key actors in the Katrina drama, gave me insight into that city and the trials of its people; it was an indispensable education to me. One person we met, Pastor Joe Cull of the New Orleans Police Department, who ministers to police officers in distress and alerted me to the high incidence of police officer suicides following Katrina, was a true inspiration.

  Many students and others helped me assemble thoughts and words for this book. I particularly want to acknowledge Solomon Hsiang, Amir Jinar, Jesse Antilla-Hughs, Stephanie Lackner, Epsita Kumar, Valentina Mara, Svetlana Maronova, Leila Wisdom, Marissa Brodney, Semee Yoon, Belinda Archibong, Erin Stahmer, Brenden Kline, Elizabeth Thornton, Jessica Rosen, Meran Killackey, Saira Qureshi, and Phoebe Leung.

  Notes

  Please note that some of the links referenced in this work may no longer be active.

  Introduction. Crossing the Feynman Line

  1.One example is Social Science Research Council, “Understanding Katrina: Perspectives from the Social Sciences,” June 2006, http://understandingkatrina.ssrc.org/.

  2.Daniel Kahneman, Thinking, Fast and Slow (New York: Farrar, Straus and Giroux, 2011).

  3.Daniel Kahneman and Amos Tversky, “Prospect Theory: An Analysis of Decision under Risk,” Econometrica 47, no. 2 (1979): 263.

  4.Daniel Mendelsohn, “Unsinkable: Why We Can’t Let Go of the Titanic,” New Yorker, April 16, 2012, http://www.newyorker.com/magazine/2012/04/16/unsinkable-3.

  Chapter 1. Natural Disasters: Agents of Social Good and Evil

  1.The way in which this might come about is described in chapter 2.

  2.The best work done using these approaches is that of Amir Jina and Solomon Hsiang, and their study considers only tropical cyclones. Still, it is very compelling. See S. M. Hsiang and A. S. Jina, “The Causal Effect of Environmental Catastrophe on Long-Run Economic Growth: Evidence from 6,700 Cyclones,” working paper NBER 20352, National Bureau of Economic Research, Cambridge, MA, 2014.

  3.“Japan’s Demography: The incredible Shrinking Country,” The Economist, March 25, 2014, http://www.economist.com/blogs/banyan/2014/03/japans-demography.

  4.The San Juan earthquake of 1944 destroyed essentially the entire city and took an estimated 10,000 lives.

  5.Mark Skidmore and Hideki Toya, “Do Natural Disasters Promote Long-Run Growth?” Economic Inquiry 40 (2002): 664–687, doi:10.1093/ei/40.4.664.

  6.To be accurate, Schumpeter was born in what was at the time the Austro-Hungarian Empire and is now the Czech Republic.

  7.Joseph Schumpeter, Capitalism, Socialism and Democracy (New York: Harper, 1947).

  8.Drake Bennett, “Do Natural Disasters Stimulate Economic Growth?” New York Times, July 8, 2008, http://www.nytimes.com/2008/07/08/business/worldbusiness/08iht-disasters.4.14335899.html?pagewanted=all.

  9.Douglas C. Dacy and Howard Kunreuther, The Economics of Natural Disasters: Implications for Federal Policy (New York: Free Press, 1969), 270.

  10.Betty Hearn Morrow, “Stretching the Bonds: The Families of Andrew,” in Hurricane Andrew: Ethnicity, Gender and the Sociology of Disaster, eds. Walter Peacock, Betty Hearn Morrow, and Hugh Gladwin (New York: Routledge, 1997), 141–69.

  11.Online Etymology Dictionary, http://www.etymonline.com/index.php?term=disaster.

  12.John Stuart Mill, Principles of Political Economy with Some of Their Applications to Social Philosophy (1848; London: Longmans, Green, 1909), http://www.econlib.org/library/Mill/mlP5.html#I.5.19.html.

  13.See, for instance, Philip Brickman, Dan Coates, and Ronnie Janoff-Bulman, “Lottery Winners and Accident Victims: Is Happiness Relative?” Journal of Personality and Social Psychology 36, no. 8 (1978): 917–27.

  14.An article in Time magazine describes Bonanno’s work and that of others in the new field of bereavement research by suggesting that the new studies debunk a series of grief myths. Ruth David Konigsberg, “New Ways to Think about Grief,” Time, January 29, 2011, http://content.time.com/time/magazine/article/0,9171,2042372-1,00.html. The book was published as The Other Side of Sadness: What the New Science of Bereavement Tells Us About Life after Loss (New York: Basic Books, 2009).

  15.W. G. Sebold, The Natural History of Destruction (Munich: Carl Hanser Verlag, 1999).

  16.The Economist magazine defines moral hazard as “one of two main sorts of market failure often associated with the provision of insurance. The other is adverse selection. Moral hazard means that people with insurance may take greater risks than they would do without it because they know they are protected, so the insurer may get more claims than it bargained for.” The definition is available at http://www.economist.com/economics-a-to-z/m#node-21529763.

  17.Charles Percy Snow, The Two Cultures (1959; repr., London: Cambridge University Press, 2001).

  18.Public Religion Research Institute, “Believers, Sympathizers, and Skeptics: Why Americans Are Conflicted about Climate Change, Environmental Policy, and Science,” report, November 21, 2014, Washington, DC, http://publicreligion.org/research/2014/11/believers-sympathizers-skeptics-americans-conflicted-climate-change-environmental-policy-science/.

  19.CRED’s web address is http://www.cred.be/.

  20.David Stromberg, “Natural Disasters, Economic Development, and Humanitarian Aid,” Journal of Economic Perspectives 21, no. 3 (Summer 2007): 199–222.

  21.“Counting the Cost of Calamities,” Economist, January 14, 2012, http://www.economist.com/node/21542755.

  22.Geoffrey Ward, review of This Republic of Suffering: Death and the American Civil War by Drew Gilpin Faust, New York Times, January 27, 2008, http://www.nytimes.com/2008/01/27/books/review/Ward-t.html?_r=0,

  23.His son was killed by Confederate soldiers who were stranded behind Union lines after a battle and had disguised themselves as Union soldiers by wearing the uniforms of dead soldiers.

  24.Eric
Klinenberg, Heat Wave: A Social Autopsy of Disaster in Chicago (Chicago: University of Chicago Press, 2002). See also “Dying Alone: An interview with Eric Klinenberg, author of Heat Wave: A Social Autopsy of Disaster in Chicago,” University of Chicago Press website, 2002, http://www.press.uchicago.edu/Misc/Chicago/443213in.html.

  25.David Laskin, The Children’s Blizzard (New York: HarperCollins, 2004).

  26.William Bronson, The Earth Shook, the Sky Burned (San Francisco: Chronicle Books, 1996).

  27.National Oceanic and Atmospheric Administration, A Study of Earthquake Losses in the San Francisco Bay Area–Data and Analysis, report prepared for the Office of Emergency Preparedness (Washington, DC: U.S. Department of Commerce, 1972).

  28.Gladys Hansen and Emmit Condon, Denial of Disaster: The Untold Story and Photographs of the San Francisco Earthquake and Fire of 1906 (San Francisco: Cameron, 1989).

  29.Centers for Disease Control, “Deaths in World Trade Center Terrorist Attacks—New York City, 2001,” Morbidity and Mortality Weekly Report 51, Special Issue (September 11, 2002):16-18, http://www.cdc.gov/MMWR/preview/mmwrhtml/mm51SPa6.htm.