16/04/2012 § 26 Comments
I’ve just spent some time in the South Island. We listened to the news and got the Christchurch paper a few times. The contrast between the news there and the news in the North Island is stark. In Christchurch, the earthquakes and the recovery are front-and-centre all the time. For Wellington, these issues are just one of many stories, merging into the general cacophony of stuff-I-should-care-about.
Well, Christchurch is screwed. Sorry for the language, but it’s true. And the rest of the country should take notice, because this is what will happen to them in a big event. The problem is the government — EQC and Cera — and the insurance companies. It’s the eternal run-around. It’s your worst medical insurance problem while waiting to renew your driver’s licence at lunchtime on a Monday.
The government is doing what bureaucracies do. It is creating processes. It is making sure that everything is correct, that all the boxes are ticked, and, above all, that their asses are covered. So it moves slowly, carefully. Safer to keep people from doing something than allow them do the wrong thing.
Insurance companies are doing what they do. They are minimising their expenses and protecting their bottom lines.
- TC3 land — Cera used to have three land categories, of which Green was the safest. Then, they re-categorised land. Green was subdivided into TC1, TC2, and TC3. Now, although TC3 is still Green, it doesn’t actually mean ‘safe for building’ anymore. It means ‘we have no idea’. Something may happen, but maybe not, and you might want to build with that in mind, but we can’t tell you how. Sensibly, people aren’t buying TC3 properties. So now, the property market for big areas of the city has completely seized up.
- Foundations — Cera says that they are working on figuring out what foundations are necessary for the different land categories. The problem is that Cera isn’t doing the rebuilding, the EQC is. EQC isn’t checking foundations unless there’s a good reason to check (house split in half or off its piles). The result is likely to be a bunch of repaired houses that either can’t be sold, sell at big discounts, or aren’t safe for the land on which they sit.
- Rental properties — Payments to cover people’s rent while they can’t live in their houses have been a problem from the start. The latest story is an insurance company saying that it would pay, and then reneging on that. The Minister in charge has said that there are a number of ways the private market could and should be sorting things out. Robin Clements rightly points out that the market IS finding its equilibrium, but that equilibrium is socially unacceptable.
- Red-zone repairs — The Red land zones are supposed to be beyond repair; the plan was to abandon these areas (e.g., these properties on the Avon River). [UPDATE:]
Now, insurers have decided that it will be cheaper to repair houses on those sections than to pay out for them. Part of the reason they can do this is thatthe Government conveniently relaxed building regulations. What hasn’t been made clear is how you sell such a house, since the Government has decided that the land should be abandoned.In the comments and in his own post, Eric Crampton clarifies the situation. [END UPDATE]
These are familiar economic problems: the market for lemons, decisions under uncertainty, asymmetric information, moral hazard. They boil down to two common threads:
- Increased uncertainty — Changing the rules and waiting for decisions have hugely increased uncertainty. These aren’t the result of the earthquakes, but of the subsequent policies. Uncertainty costs the economy, and Christchurch is paying dearly.
- Shifting costs onto individuals — People are having to paying out-of-pocket for rentals, fight to have legitimate bills paid, and take massive hits on their home equity. These are all costs that insurers and the government are shifting off their books and onto individuals.
Christchurch people paid their insurance policies. They paid for their earthquake coverage. They should be fully compensated. Instead, they’re getting shafted. Unless this changes, the Christchurch economy will be injured for many years. Not because of the earthquakes, but because of the aftermath.
05/04/2012 § Leave a comment
Easter is almost upon us, reminding me of my early lessons in endowments, preferences, and Pareto optimisation. I’m talking, of course, about trading Easter candy.
Now, parents have an impossible task. They can either give every child exactly the same endowment of candy (jelly beans, chocolate eggs, marshmallow chicks, etc.), or they can attempt to equalise the satisfaction of the children by matching endowments to known preferences.
I come from a big family. Easter morning, our baskets of candy would be waiting for us, delivered overnight by the Easter bunny. In a small family, it is possible to spend more time giving each child what they want. In a big family, everybody just needs to get in line and accept what they get.
So, we all had pretty much the same baskets. As a result, once the chocolate bunnies were eaten, we were each left with candy we didn’t particularly like. There was scope for Pareto improvement — each one of us could be better off and no one worse off by engaging in free trade. I was the only one who liked black jelly beans, so that was my ace in the hole. I was pretty much the monopsony buyer of black jelly beans. On the other hand, I don’t particularly care for marshmallow chicks, so I was happy to get rid of them. Also, as an older child, I had a bit of an advantage over my less experienced siblings.
Of course, candy is candy, even if it isn’t the best. Each piece still has a minimum sugar value. This sugar value functioned as a reserve price in the barter process.
What did I learn from all this?
- heterogeneity of preferences can be a strong driver of trade
- failures in initial endowments can be corrected through open markets
- information is powerful — use it to your advantage
- the trade price is indeterminate, so try to find your partner’s reserve price.
When I say that trades were Pareto improving, that’s a technical term. It doesn’t mean there weren’t arguments and even tears. But that’s all part of the information discovery process, right? And, as much as everyone was better off, I have to admit that I might have been a bit betterer off. What can I say? That’s what big brothers do.
03/04/2012 § 1 Comment
The results in a new sociology article have been making waves in the blogosphere. Gordon Gauchat found that conservatives in the US have become less trusting of science. This was a test of a thesis from Chris Mooney. Some quotes:
Using data from the 1974 to 2010 General Social Survey, I examine group differences in trust in science and group-specific change in these attitudes over time. Results show that group differences in trust in science are largely stable over the period, except for respondents identifying as conservative. Conservatives began the period with the highest trust in science, relative to liberals and moderates, and ended the period with the lowest.
Mooney (2005) (from the blurb):
On a broad array of issues-stem cell research, climate change, missile defense, abstinence education, product safety, environmental regulation, and many others-the Bush administration’s positions fly in the face of overwhelming scientific consensus…. This is not unique to the Bush administration, but it is largely a Republican phenomenon, born of a conservative dislike of environmental, health, and safety regulation, and at the extremes, of evolution and legalized abortion.
I have seen something similar in my research, something broader than Gauchat’s findings. I started from the position that Slovic laid out, I think in the intro or first chapter of The Perception of Risk (2000). He called it the ‘white male’ bias. In research on risk, he found that there were ethnic and gender differences, but they interacted. He found that white males had different risk assessments than everybody else.
In my work on technology, I found sort-of similar results. But it was more subtle than that. Middle- to high-income males, particularly white males, seemed to have more positive views of new technology than everyone else. I played around with cross-tabs for a while — it was a minor issue in my research — and never quite resolved where the splits were. Other people’s work elsewhere suggested the same effect.
Because facts aren’t facts. We interpret them, we manipulate them, we try to make sense of them — and, chiefly, we insert them into narratives as best we can. With each piece of information, we ask, how does this particular fact fit with my identity and worldview? As a result, belief or trust in science is a badge we wear. We signal to the world who we are by the stance we take on science issues.
Where is this headed? The ‘white male’ bias is inherently trusting of official science. The opposite position, which tends to be correlated with females and non-whites, is sceptical. Now, US conservatives are becoming less trusting of science. It looks like the support for science — the official, lab-coated, expert-centred variety — is eroding. The ‘white male’ bias was always a minority position (although a privileged one). But now it is losing a key bloc — the conservative white male and his allies.
I can see potential good coming from this splintering. Slovic and others have shown that the experts aren’t necessary right. They do make mistakes, they engage in groupthink, they are subject to cognitive biases. Broadening the discussion about all kinds of science issues could make it more inclusive. That’s the optimistic position. The pessimistic position is that people with the strongest views and loudest voices (and deepest pockets) will determine things for the rest of us, regardless.
02/04/2012 § Leave a comment
Seamus Hogan brought in some mathematical notation, so I’ve been trying to figure out the notation for what I was thinking. Here goes:
VoSLs can be estimated by finding examples of people paying to reduce their risks of death. For example, if consumers pay $5,000 more for a car with a safety record that gives them a 1% lower probability of dying in an accident, that suggests a VoSL of $500,000. The equation is:
VoSL = Value / Probability.
We can use this to think about how much to spend now to reduce future impacts of climate change. We multiply the number of lives saved by the VoSL, and then use discounting to compare the future value to present spending:
(VoSL * lives) / (1 + discount rate)^years = spending.
But here’s the problem: VoSL in the future is affected by the quality of life in the future, which is affected by spending on climate change. That is:
Value = f(population),
because when lots of people die, life gets cheaper — this was the quote about the Black Death in the earlier post.
Population = g(spending), so
Value = h(spending).
Putting this back into the estimate of the right level of spending, we get:
((h(spending)/probability)*lives / (1 + discount rate)^ years = spending.
Instead of being able to look at future potential losses and calculating the ‘correct’ level of spending now, we find that spending is on both sides of the equation. Rearrangement gives us:
lives / (1 + discount rate)^ years = spending/(h(spending)/probability).
You can think of the LHS as a constant — the per-life discounting to be applied to future spending. Once you decide the timeframe (100 years?) and the discount rate (good luck), this is just a number. The RHS is a ratio — the ratio of current spending to future VoSL as a function of current spending. Since VoSL increases with spending, we aren’t guaranteed a unique solution. It all depends on h(spending), on that function. This was Seamus’s point — with concave functions for population and quality of life, there are potentially multiple equilibria.
Basically, the reasoning above says that two positions are as economically rational as each other:
- We put a high value on life, and we should preserve future lives by spending now to address climate change.
- It’s all going to descend into brutal chaos, anyway, so we don’t need to bother (insert gratuitous reference to the frightening cultural phenomenon that is The Hunger Games).
More basically, I don’t think economics gives us the answer (provides a unique solution). Instead, it is an ethical problem. Once we sort out the ethical goals, economics can help with the means to achieve them efficiently.