Five Percent: Conserve Energy

Climate Change Is Important: Energy Conservation is the First Step

April 18, 2008

Freakonomics Gets It Right/Wrong (Completely)

Category: Climate Change,Editorial,Rants,Transportation – Tom Harrison – 10:46 pm

Cars cost a lot more than we pay for, say Dubner and Levitt of “Freakonomics” fame:

with roughly three trillion miles driven each year producing more than $300 billion in externality costs, drivers should probably be taxed at least an extra 10 cents per mile if we want them to pay the full societal cost of their driving.

Their article will be published in Time Magazine this week. In nearly the first paragraph, they define the problem:

…there are all sorts of costs associated with driving that the actual driver doesn’t pay. Such a condition is known to economists as a negative externality: the behavior of Person A (we’ll call him Arthur) damages the welfare of Person Z (Zelda), but Zelda has no control over Arthur’s actions.

That’s the good news (I guess). The bad news is they say that externalities from carbon emissions are a mere $20 Billion of that $300 Billion a year cost (traffic congestion and property damage are both far more costly unrealized costs).

So while I am very, very glad to have the world now understand externalities, and while I always trust everything all economists say, I must admit that my non-scientific side thinks that perhaps the cost of CO2 emissions from cars may be, in the longer run, at least comparable to the cost of lost time and property damage. Perhaps even more costly.

The Trouble With Tiggers

And therein lies the problem with externalities. There’s usually a good reason why our expenses do not reflect the total costs of using a resource like a car. It’s simply that such costs are very, very hard to measure at all, much less accurately.

I like the Freakonomics guys because, in turning many “reasonable” and “rational” arguments on their heads, they correctly cast a shadow of doubt on much of our economic truths.

They do this using regression analysis on huge hoards of data that they are able to collect and correlate. If regression analysis sounds hard to you, it’s because it is. It’s one of those sciences that gave statistics a bad name. If you get enough data on something, you can pretty much be sure whether or not a correlation (relationship) exists between two things.

The Trouble With Real Estate Agents

For example, in their book, they measure whether there was a correlation between whether you were a real estate agent and the price you got for your house (there was: real estate agents got more for their own houses than they did when selling your house for you).

These kinds of correlations can pretty accurately show directionality (the “vector”) but are not as good at measuring how much (“magnitude”). And both metrics begin to falter when all of the “facts” may not be available to number-crunch upon.

It’s easy to calculate the costs of property damage because this is data that is very carefully measured and which translates very directly into money values.

Costs of congestion is a little harder—you have to make some assumptions about how many dollars per hour of productivity are “lost” due to people being in traffic rather than working. (I, for one, am pretty much useless after 8 hours of work, and some would say this time is too long, regardless of how much time I spend commuting. Indeed, the time I spend driving or riding my bike to and from work gives me an opportunity to clear my mind. This is difficult to measure.)

The Trouble With Measuring Carbon

But to calculate the cost of carbon emissions is pure folly. Don’t get me wrong, measuring carbon cost is an absolutely essential part of what we must do to efficiently and quickly address the major issues of global warming. But just because it’s important doesn’t mean we actually can measure it. We cannot. I would be more than thrilled to be proven even a little bit wrong. The person who figures out a good way might get a Nobel Prize (Levitt already got one, can you get multiples?)

Regression analysis requires lots of good raw data, and to draw an economically relevant conclusion, such data needs to be convertible to monetary costs. While we may have a reasonable source of raw data, it’s foolish to think we can assess a cost for carbon emissions.

What are the components of that cost? Did they calculate the cost of the Iraq war? Probably not, as it was is a war about weapons of mass destruction, or was it oil, no, it is terrorism. What does that have to do with global warming?

How about the potential cost of various weather events? So far the cost of Katrina has been incalculable the cost of the Indonesian tsunami has been enormous there have been few measurable weather costs associated with global warming.

Future costs associated with war and disease displacement due to rising sea level escalating food costs, lack of water, and famine are pretty much unmeasurable.

So, do estimates of carbon emissions truly measure cost? No!Sure they do—don’t you trust the mythology science of economics?

The Trouble With EconomistsNobel Prizes

Sorry Dubner and Levitt. Nobel Prize, schnobel schmrize. I’ve got a blog just like you, and I got a C- A- in economics from Princeton (assuming you account for my thesis grade).

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