Showing posts with label media. Show all posts
Showing posts with label media. Show all posts

Monday, March 31, 2014

IPCC report

I’m just getting back from the IPCC approval session in Yokohama, Japan. A full copy of the summary for policy makers, which we spent a week approving line by line, is here. The chapter reports are also there.

I’ve been doing some interviews on the report, but not that many given long flights, the different time zone here in Brizzy (yes, that's what they call it), etc. One really good overview story in NY Times is here.

One of the reasons we started the G-FEED blog was to have a chance to speak in our own words, rather than just through the media. So far some of the stories on the report have been over the top negative. So I thought it worthwhile to offer here a few thoughts:

First, the sky is not falling, and the report doesn’t say that it is. To me, the report has some simple messages: 1) The impacts of climate change are already evident throughout the world, in many different places and types of natural and human systems. 2) The risks of further impacts are very real. 3) There are many things we can do to reduce those risks.

The report is sobering because the facts are sobering. But it is also tries to be very constructive by pointing out all the options going forward. It lays out a vision, led by our co-chairs, of a much better world. I think the final summary for policymakers is a very well balanced and thoughtful report, and one that I am very proud to have been a part of.

I also get a lot of questions about the process. What is it like to be an IPCC lead author? Writing the chapter took about 3 years. When we meet we typically work up to 12 hour days, including weekends, often skipping lunch, usually jetlagged from long flights in coach class, and for no pay. But other than that it’s great!

More seriously, and on the positive side, it’s extremely rewarding to work with colleagues that are the best in the world at what they do, and to work hard with them to synthesize evidence and figure out what we feel comfortable saying, and how to say it most clearly. It’s also an honor to represent your country in an international process that is geared to providing the best possible scientific evidence. I typically leave the meetings tired but deeply impressed with the devotion and critical thinking of my fellow scientists. And jealous of those whose countries fly them business class.


As for the plenary approval, the only word I can think of right now to explain it is “exhausting”. Maybe I will have more energy and perspective later on to write about that. But if you want to know why some of the media stories are not completely clear, it may be that they were talking to authors who had slept maybe 5 hours in the past 48 hours, if that. It’s a further testament to the genius and stamina of Chris Field that he chaired endless sessions and still managed to be so articulate and upbeat in the press conference.


Monday, March 10, 2014

The power of avocado

I woke up last Saturday to several emails and voice mails asking for my view on guacamole. That isn’t usually how my weekend starts. But it turns out that Chipotle issued some statement in their annual report about risks of price increases, and among them was avocado. I presume this is mainly related to the current drought, but then Chipotle wrote something about this being a possible trend and cited a paper we wrote nearly 10 years ago with some projections for avocado.

None of that would have amounted to much, but I guess it was a slow news day and reporters rarely pass up the chance to use “Holy Guacamole” in a headline (nor should they). Today I checked and a search for “avocado Chipotle” on Google News gives over 6000 results, ranging from the predictable to the fairly impressive “Guacapocalypse”.

The study we did looked at state level data and tried to infer climate sensitivity for a range of high value crops. Avocados were one that seemed to suffer with very high late summer temperatures. This was based on only a couple of hot years and so the uncertainties were quite large, as we reported in the study. We also did some follow up work with more data and more fancy statistics in what I consider a better paper. There we decided to focus on crops where the relationships were most robust, and that didn’t include avocado. But it did include some popular crops, namely the four shown below (figure shows distribution of projected impacts in terms of % yield, not including CO2 effects). Which makes me wonder what the best headline for a story on cherries would be? I’m sure Max has already thought of a few good ones.


Maybe I’m over-analyzing (and by maybe, I mean almost definitely) but I think the episode demonstrates a few common things. First, it is very difficult to contrast current trends in crop yields or prices to what would have happened without anthropogenic climate change. Max’s last post discusses this issue, one he and I have been grappling with for years in our service for the IPCC. Should we expect more down years for avocado in the future? That’s not an easy question, certainly not one I’ve looked at enough for this particular crop to offer a firm answer, even if one was possible.

Second, the media has a bit of a tendency to exaggerate things. I assume I’m the first person to ever notice this. (That was sarcasm). Things are either a total non-issue or the end of the world, and nothing in between is newsworthy. That makes it tricky to communicate an issue like climate change where almost everything is somewhere between these two extremes. 

Third, and probably most important, is that people really take what businesses say related to climate change risks very seriously. The shame is that I know a lot of businesses are convinced of the science and have thought a lot about risks posed by climate change, but they rarely make these concerns public. I recall sitting on a panel at a large agricultural company and was asked what the company could do to help society prepare for climate change. My answer was that they should not be so silent about the issue. They were the third agricultural company that year to tell me they believe the science, that they are concerned about the risks, but that they don’t dare talk publicly about it for fear of alienating customers who see climate change as a political issue.


As a bit of consolation for US readers, please know it is hard to find an avocado here in Australia for less than $3 a piece. So that extra $2 for guacamole at Chipotle is a real bargain. I hope there’s still some left when I get back!

Wednesday, May 8, 2013

Is peace needed in the climate/conflict debate?


Yes, argues Andy Solow in a comment in Nature today.  He bemoans the "fierce battle that has broken out within the research community" over whether there is a link between climate and conflict, highlighting the protracted argument we've been having with Halvard Buhaug and colleagues over whether there is a link between temperature and conflict in Africa (see here, here, and here).  Solow's main point seems to be that these sorts of "reduced form" analyses of climate and conflict reveal little about the true underlying processes that drive conflict, and thus that people running these models ("quants") need to engage with folks that are studying individual conflicts in depth ("quals") to make the analyses meaningful.

Overall his comments are quite reasonable, and if I can speak for my co-authors I think we are sympathetic to many of his arguments.  I have a few main points of disagreement, however.  First, I would not characterize the disagreements between Halvard (and colleagues) and us as a disagreement between "quants" and "quals".  We would certainly put ourselves in the former category and I'm guessing Halvard would too.  The disagreements between us have really been about how to do the quantitative analysis correctly, something over which we continue to disagree and will continue to disagree as long as folks are estimating panel models without fixed effects, or estimating models that include outcome variables as covariates.  But contrary to what Solow suggests, we definitely have been engaging with Halvard and his colleagues.  For instance, at Halvard's generous invitation I participated in a couple sessions on climate and conflict at last month's annual meeting of the International Studies Association, sessions organized by Halvard and colleagues. 

More importantly, though, I think Solow misperceives what estimating reduced form models is all about in this setting, and does not allow that the very reason a "quants" might want to engage with a "quals" is because a reduced form effect has been established.  A typical quant approach would be to start with an initial hunch that conflict and (say) temperature might be related, put together some data, and estimate a regression of conflict on temperature.  If there is a relationship in this "reduced form", then this would motivate more careful study of the underlying cases and mechanism - i.e. an engagement with the quals.  On the other hand, if there is no relationship in the reduced form, there is arguably no reason to take a "deeper look behind the statistics", as Solow puts it.  This is because the reduced form effect is going to encompass all possible ways in which climate will affect conflict (even if it doesn't illuminate them), and a null result in the reduced form would tell you that there is no mechanism linking the two phenomena.  

(Some initial hint at the underlying mechanism can certainly motivate how the reduced form is estimated, and this is something people are already attentive to.  For instance, suppose you think that shortfalls in income are what link climate variables to conflict events; in a setting where income is earned in agriculture, then focusing on climate during growing season months might make sense.  This approach for example is pursued in a nice paper by Harari and La Ferrara, in which they show that drought during the growing season matters a lot more for conflict than drought in the non-growing season.)  


The argument with Halvard and colleagues is about whether there is a reduced form effect.  Because my colleagues and I think that the reduced form relationship between temperature and conflict in Africa has been pretty well established by different research groups working at multiple scales (e.g. here, here, here, here, and here), we are in full agreement with Solow that a closer look at mechanism is now warranted, and that we need to learn a lot from quals about what might be going on.  But if you do not believe this reduced form, then it doesn't make sense to engage with quals on how climate might affect conflict.  

But a reduced form relationship is also much more than just a reason to talk to qualitative folks.  For the sake of argument, let's imagine that no manner of further engagement with quals is ever able to fully isolate the mechanism linking climate to conflict - perhaps there are just too many factors that are both affected by climate and that are potential contributors to conflict.  Does this mean that we learn nothing from the reduced form, or that it should be ignored by policy-makers?  


Probably not, for two reasons.  First, the reduced form effect of climate on conflict, when properly estimated, is estimating the causal effect of climatic fluctuations (typically inter-annual) on conflict outcomes.  This is because year-to-year variation in climate is pretty random and unlikely correlated with other unobserved variables that also affect conflict.  We know climate has "caused" conflict, we just don't know why.  

Second, even if we don't yet understand the mechanism linking the two variables, the fact that warmer temperatures and conflict are linked would appear useful to policymakers interested in whether we should take action to mitigate future climate change.  Clearly, as Solow points out, past responses to year-to-year variation and future response to long-run changes in means are not the same thing.  But given that adaptation to long-run temperature changes appears very slow at best, that sensitivity to extreme heat does not appear to be diminishing, and that past relationships are all we really have to go on, then assuming these relationships might carry into the future does not seem like a crazy place to start.  Moreover, important decisions are often made solely on "reduced form" evidence.  For example, I don't need to know how snake venom kills me to figure that, if I find myself in a room full of poisonous snakes, it might make sense to either invest in snake-proof boots or see if I can find a door.  The "adaptation" strategy here - buying boots - does involve knowing a little something about the mechanism: i.e. snake --> bite --> die;  the "mitigation" strategy - leaving the room - does not.  As a less prosaic example, aspirin was discovered before 1900 and was prescribed for decades before the mechanism underlying its efficacy was understood in the 1960s. Similarly, quinine has been used as a malaria drug since the 1600s although we still do not understand why it works.  So failing to understand a mechanism does not typically keep us from taking meaningful action when we've decided a reduced form effect is real.

Nevertheless, I hope (with Solow) that we can stop arguing about a few of the primary reduced forms in question -- e.g. the link between temperature and conflict in Africa -- and do more to understand what's going on and what to do about it.  Doing so will help inform adaptation investments in particular, and Solow is right that detailed case-study knowledge from the "quals" will be critical in building this understanding.  But moving in this direction involves establishing that there is a reduced form relationship between temperature and conflict, and it is for this reason we are arguing with Halvard and co.  

Sunday, December 9, 2012

Climate, food prices, social conflict and....Google Hangout?

My coauthor Kyle Meng was asked to participate in this HuffPost Live discussion about climate, food prices and civil conflict. It's an interesting discussion, which gets pretty rowdy at times, with an eclectic group. I am also very impressed by HP's leveraging of Google Hangout to produce a low-cost public, intellectual forum.

David has written about the food-price and conflict linkage before, and we've discussed the association between climate and conflict a few times here.  In general, I don't think a linkage has been demonstrated conclusively with data, but that doesn't seem to get in the way of people referencing it.

The debate is interesting and entertaining, highlighting a few of the differences in how some policy-folk, economists and ecologists view theses various ideas.


Kyle was asked to participate because he was an author of our 2011 Nature paper on ENSO and conflict.  He also happens to be on the job market right now.

Monday, November 12, 2012

Grow, Canada?


A quick post on an interesting article in Bloomberg last week about expansion of corn in Canada. I’ve been keeping an eye out for stories about possible adaptations in the wake of this summer’s poor corn harvest in the U.S (or as Stephen Colbert called it – our shucking disaster). As we’ve discussed before on this blog, having crops migrate northward is a commonly cited adaptation response. In addition to being encouraged by the warming trends, the northward migration of corn could be helped by new varieties that have shorter cycles and better cold hardiness.

It’s certainly interesting to see the expansion of corn in areas like Alberta and Manitoba, or for that matter in North Dakota. But too often media stories, or even scientific studies, present the changes as de facto proof of adaptation. The question is not really if crops will move around – they always have moved around in the past, and will continue doing so in the future. And I don’t even think the key question is whether climate change will be an important factor in them moving around – the evidence is still slim on this question but the Canada transition is clearly one made easier by the climate trends. Instead, the most important issue is how much is gained by these adaptive moves relative to the overall impacts of climate trends.

Sol has been analyzing this in some detail for different regions around the world, so he will hopefully have some more to say with numbers to back it up. But let me just point to two relevant questions that were each alluded to in the Bloomberg article. First, is the scale of expansion large relative to the main zones of production? In the case of Canadian corn, the article mentions about 120,000 Ha of corn area sown in three provinces of Canada (Manitoba, Saskatchewan, and Alberta). That is less than one-half of one percent of the U.S. corn area.

Second, what is being displaced by the crop expansion? In most cases, including Canada’s, corn is being grown by farmers that used to grow wheat or barley. So the gain in corn production is offset to a large degree by the loss in wheat production (although not completely, since corn typically produces more grain per hectare than wheat). Modeling studies of adaptation typically assume there is a net expansion of total cropland in cold areas, not just expansion of individual crops. Without net area expansion, it is hard to offset losses incurred at lower latitudes.

There is certainly an argument to be made that big expansions of net area will only be seen with more substantial shifts in climate, since only then will it pay to make the large capital investments to open up new areas for agriculture. But it’s also possible that the constraints on expanding into new areas (poor soils, lack of infrastructure, property rights, rules on foreign investment) are large enough that only a modest amount of expansion will happen.

The main point is that changes in crop area have to be judged not just by whether or not they happen, but by whether their impact is large enough to matter. For most readers of Bloomberg, “large enough to matter” may simply mean that it’s an opportunity to make a lot of money. But for those of us interested in global food supply and price dynamics, the scale of interest is much larger. A 25% drop in U.S. corn production leaves a big hole to fill – it’s not enough to drop a few shovels full of dirt in and call it a day. 

Sunday, November 4, 2012

Too close to call?

All of the attention on the presidential election has brought up some issues that are familiar to those of us who work in the world of anticipating and preparing for climate change impacts. In particular, there's been a clear contrast in the election coverage between, on the one hand, a lot of media stories that describe the race as a "toss-up" or "too close to call" and, on the other hand, careful analysis of the actual data on polls in swing states that say the odds are overwhelmingly in favor of another term for President Obama. Nate Silver has become a nerd celebrity for his analysis and daily blog posts (his new book is also really good). But there are many others who come to similar or even stronger conclusions. Like Sam Wang at Princeton who has put Obama's chances at over 98%.

I think there are a few things going on here. One is that the popular media has basically no incentive to report anything but a very close race. It keeps readers checking back frequently, and campaigns may be more likely to spend more money to media outlets for advertising if the narrative is for a very close race (although admittedly, they have so much money that the narrative may not make much difference). A more fundamental reason, though, is just a basic misunderstanding of probability. Not being able to entirely rule out something from happening (e.g., Romney winning) is not the same as saying it could easily happen. People mistake the possible for the probable. They want black and white, not shades of gray (at least not fewer than 50 shades of gray).

(Also in the news this week: hurricane Sandy. Another case where people who understand probabilities, like Mayor Bloomberg, have little trouble seeing the link to global warming, while others continue the silly argument that if it was possible for such things to happen in the past, then global warming can't play a role. In their black and white world, things can either happen or they can't. There is no understanding of probability or risk. I call this the Rava view of the world, based on the episode of Seinfeld when Elaine tries to convince Rava that there are degrees of coincidence:

RAVA: Maybe you think we're in cahoots.
ELAINE: No, no.. but it is quite a coincidence.
RAVA: Yes, that's all, a coincidence!
ELAINE: A big coincidence.
RAVA: Not a big coincidence. A coincidence!
ELAINE: No, that's a big coincidence.
RAVA: That's what a coincidence is! There are no small coincidences and big coincidences!
ELAINE: No, there are degrees of coincidences.
RAVA: No, there are only coincidences! ..Ask anyone! (Enraged, she asks everone in the elevator) Are there big coincidences and small coincidences, or just coincidences? (Silent) ..Well?! Well?!..)

Back to my point (you have a point!?), when we turn to climate impacts on agriculture, it's still quite common to hear people say that we just don't know what will happen. Usually this comes in some form of a "depends what happens to rainfall, and models aren't good with rainfall" type of argument. It's true that we do not know with complete certainty which direction climate change will push food production or hunger. But we do know a lot about the probabilities. Given what we know about how fast temperature extremes are increasing, and how sensitive crops are to these extremes, it's very probable in many cases, like U.S. corn, that impacts on crop yields will be negative. (For example, a few years back I tried with Claudia Tebaldi to estimate the probabilities that climate change would negatively impact global production of key crops by 2030. For maize, we put the odds at over 95%). Even in cases where rainfall goes up, the negatives tend to predominate. It's also also very likely that in some cases, like potatoes in England, that impacts will be positive. In either case we cannot say anything with absolute certainty, but that doesn't mean we should describe impacts as "too close to call"

Us academics can probably learn a thing or two from how Nate Silver is trying to explain risk and probability in his daily posts. But it's also fair to say that our task is a little hard for a couple of reasons. First, there are lots of data on past polls and election results, which people can use to figure out empirically how accurate their methods would have been in past cases. With climate change, we are often talking about changes that have not been seen in the past, or at least not by enough cases to develop a large sample size for testing. A second and, in my view, more critical difference is that climate impacts happen on top of many other changes in society. Elections provide a clear outcome - a candidate wins or loses. But what does a climate impact look like? How do we know if our predictions are right or not?  A lot of the entries in this blog are around that question, but the short answer is we can't directly measure impacts, we have to be clever in thinking of ways to pull them out of the data.

So maybe all of the attention to the election forecasts will help the public understand probabilities a little better. If nothing else, people should understand the difference between a 50% chance and an 80% chance of something happening. Reporting the latter as if it were the former is annoying in the context of the election, or as Paul Krugman says "Reporting that makes you stupid". But confusing the two in the case of climate impacts is more than annoying, it can lead to a lot more wishful thinking and a lot fewer smart investments than would otherwise be the case.

One final note: even when people are on board with the meaning of probabilities, it's still not so easy to get them right. Silver has the election at ~85% chances for Obama. That's high, but his chances of Romney winning are about 10 times higher than what Wang has. So just like with climate impacts, smart people can disagree, and it usually comes down to what they assume about model bias (Silver seems to admit a much higher chance that all polls are wrong in the same direction.) But even if smart analysts disagree, very few if any of them think the election results (or climate impacts) are a toss-up..

Saturday, October 13, 2012

Global hunger: down but not out



A recent revision of the FAO's calculations on how many hungry people there are in the world has garnered some attention, not least because the FAO seems to have backed off their earlier headline- and funding-generating claim that high food prices and the global economic downturn had resulted in there being over 1 billion people hungry in the world.  The roundness and bigness of that number was certainly shocking and galvanizing, but what was perhaps more worrying at the time was the implication that earlier gains in reducing the number of hungry were being rapidly reversed - that hunger was "spiking" and that there was a serious crisis underway.

FAO's revised numbers, out in their annual State of Food Insecurity, tell a somewhat different story.  See the plot below, which is pieced together from the last three SOFI reports. The total number of hungry is now about 850 million - below a billion but still a debacle by any normal standard - but the updated numbers (shown in blue) now completely wipe out the highly-publicized food crisis spike of 2008-2010. Instead, it looks like there were more hungry people in the world in the 1990s, but that this has been more or less steadily improving ever since - with some leveling off in the last half-decade. The take home from these numbers:  we had a worse starting point, but much more progress since then and no big spike.



So what happened? Why the progress, and where'd the spike go? Calculating the number of hungry in the world is not an easy task.  The way the FAO does it is to combine population estimates for a given country (which we know pretty well) with estimates of dietary requirements for people in that country (based on anthropometrics, which we know decently well), with estimates of calorie availability.  This last part is where things get tough.  What the FAO does is to (try to) use household survey data to get an estimate of the distribution of consumption within a country, and then because these data are not available every year, use broader indicators of food availability (e.g. data on country level production and trade) to shift this distribution around.  In this technical note, they suggest that the revision had a little to do with better estimates of calorie distribution across households (which reduced estimates of the number of hungry 2008-2010 by about 60million), and a lot to do with better accounting for food losses and wastage (which increased the number of hungry in each period by about 125 million).  

This to me explains why the levels went up, but does not really explain where the spike went.  In the 2012 SOFI, the authors explain:  

"The methodology estimates chronic undernourishment based on habitual consumption of dietary energy and does not fully capture the effects of price spikes, which are typically short-term. As a result, the prevalence of undernourishment (PoU) indicator should not be used to draw definitive conclusions about the effects of price spikes or other short-term shocks. Second, and most importantly, the transmission of economic shocks to many developing countries was less pronounced than initially thought."

This seems a little weird, since basically the same methodology was used to show a huge hunger spike on account of the 2008 price rise. 

In any case, it was likely there was (and is) still a hunger spike.  What of course you can't show on that plot is the counterfactual - what hunger numbers would have looked like had there been no economic downturn and food price increase.  There is plenty of evidence from other sources, including good micro work by folks at the World Bank, that price spikes in 2008 and again since mid-2010 have pushed 50-100million people below the $1.25 poverty line.  Hunger is of course different than poverty, but they are closely related - and this makes the FAO revision again confusing since it suggests that things were getting worse for a lot of people.  

Good household survey data are a critical component to any adding up of the number of hungry, and if you had these surveys every year and in a bunch of countries, you would know a whole lot more about how much people are eating and how much they are hurt by higher food prices.  And there are many other (potentially much more clever) ways to use household expenditure data to get at hunger without adding up every single calorie consumed by the household.

The FAO seems to realize this.  In their technical note on the updated numbers, the FAO notes that: 

"If nationally representative surveys collecting reliable data on habitual food consumption were conducted every year and could be processed in a timely and consistent manner throughout the world, then a simple head-count method, based on the classification of individuals, could be used. Until then, a model based estimation procedure, such as FAO’s, is still needed."

What I don't understand is why the FAO is not already doing these surveys.  Calculating the number of hungry people in the world (and its different regions) would seem like one of - if not the - most important task the FAO has on its annual to-do list, and something that might be worth throwing some money at. 

FAO's annual budget is $1 billion USD (which as noted by this website equals the "cost of six days of cat and dog food in nine industrialized countries").  Lets say you wanted to do annual household surveys in 100 poor countries.  A good rule of thumb for doing surveys in poor places is that it costs about $25 to survey one person, inclusive of all costs.  So for $100k, you could survey 4000 people, which is a decent sized national survey.  So doing these surveys annually in 100 poor countries would cost $10million, or 1% of FAO budget.  (Initial survey costs might be higher, but once you've paid the fixed costs of getting together a survey team, costs over time would go down..)  And with modern electronic data collection methods, you could collect, aggregate, and analyze this data pretty quickly - which is not to say that doing surveys is easy, but that this seems like a fixable problem. Furthermore, the much, much richer World Bank is already doing a bunch of these surveys - the LSMS - so presumably would be willing to go halvsies. 

Until they do so - and given the large differences in the what the poverty numbers and the hunger numbers seem to say about the food crisis -  it's not obvious that we're better off trusting the new estimates of the global number of hungry a whole lot more than the old ones.  Either way, there are a whole lot of hungry people in the world, and high food prices do not appear to be doing them any favors.

Friday, September 14, 2012

Chicago Council's Drought Series

I was asked to comment on the 2012 drought, by the Chicago Council on Global Affairs. They have been active in food issues the past few years as part of their Global Agricultural Development Initiative. I especially like their weekly newsletter (despite its title "Food for Thought", which I suspect tops the list of most over-used phrases in the world). It's a great a way to follow different stories in the media, especially on the status of production and policies in other countries. you can sign up for it here.

You can see my post here and the rest of the drought series here.

Friday, August 17, 2012

Predicting food prices and conflict


I am generally a stickler for the peer review process. As a scientist I know the peer review process isn’t perfect, but it is a very effective way of weeding out nonsense. And on the topic of food, there is no shortage of nonsense out there.

That’s partly why I have been intrigued by some of the work coming out of the New England Complex Systems Institute (NECSI). Over the past couple of years, they have had reports on how food prices lead to climate and how speculation and ethanol can explain nearly all of recent price movements. And they have recently released a report on the effects of the current droughton food prices

These are all complex topics (which I’m guessing is what drew the Institute’s attention in the first place), and quantitative analysis can be very difficult -- the type of situation where reviews by peers can be especially useful. But they clearly have a different mode of doing science than I do, since they appear to not use the peer review process at all. Instead, they self issue reports, and do press releases on these reports that get wide media coverage.  It’s possible some versions of these reports are in peer-review somewhere, but I don’t see any mention of it on their website.

As I said, the peer review process isn’t perfect. It does not always help, and it is almost always slow. So I can understand reluctance to use it, especially when working on such topical issues. But it raises the question of how credible their work is. For example, I have gotten several questions from colleagues asking what I think of their work, questions that likely would not have occurred if the work had been peer reviewed. 

But in the case of NECSI, I think they have come up with a pretty satisfying solution – making testable predictions about the next year. For example, the figure below is from their most recent report, claiming that the drought should drive FAO’s food price index to about 240 by the end of the year. And they are already on record as saying these levels of food prices lead to large scale social unrest (they state a threshold of 210, so 240 is actually well above that). 


So by the end of the year, surely before most peer review processes would have been completed, they will have a clear test of their model. Now, it’s possible they could get things right for the wrong reasons – a broken clock is right twice a day. But they are going out on a limb, which is a way to establish credibility. Hopefully, they will be as honest and diligent in reporting their failures as their successes.

Speaking of which, FAO just released the new food price index for July 2012, which is 213. That’s 3 points above the threshold!

Friday, August 3, 2012

Declining public interest in the drought

David Lobell mentioned that there seemed to be less news coverage of the drought, so I checked Google Trends and David was right. Looking just the USA, interest in the drought peaked about a week ago:


(news report volume looks similar, but Google doesn't give me the raw data). Is interest/news falling because the nation's corn crop has recovered? Probably not.  But a week ago, something else took over the airwaves and peoples' attention:


Is this spurious? It's possible, but this general pattern is well documented. In a 2007 articleDavid Strömberg linked the quantity of US disaster relief (a proxy for public interest) to "whether the disaster occurs at the same time as other newsworthy events, such as the Olympic Games, which are obviously unrelated to need."  He concludes "that the only plausible explanation of this is that relief decisions are driven by news coverage of disasters and that the other newsworthy material crowds out this news coverage." So it isn't crazy to think that the London Games might soak up some of the public interest that would otherwise go towards our own drought.

In a closely related 2011 paperMatthew Kahn and Matthew Kotchen showed that "an increase in a state's unemployment rate decreases Google searches for "global warming" and increases searches for "unemployment."

Yet, while it seems unlucky for folks in the midwest to get hit by this drought during the Olympics, they are "lucky enough" to get hit just before the presidential race. In their 2007 paperThomas Garrett and Russell Sobel "find that presidential and congressional influences affect the rate of disaster declaration and the allocation of FEMA disaster expenditures across states. States politically important to the president have a higher rate of disaster declaration by the president... Election year impacts are also found. Our models predict that nearly half of all disaster relief is motivated politically rather than by need. The findings reject a purely altruistic model of FEMA assistance and question the relative effectiveness of government versus private disaster relief."

(cross posted on F-E)