Why does driving too much make you poorer?
Posted by Stuart Staniford on January 15, 2006 - 4:00am
Topic: Economics/Finance
Tags: gdp, hubbert peak, oil prices, peak oil, us states, vmt [list all tags]
This is one of those analyses that I started with a firm opinion: I thought I knew where it was going. And then it went somewhere else and ended in a bit of a mystery. Details of my puzzlement below the fold.The graph to the right shows Gross State Product/Capita (source: BEA, 2003) plotted versus Vehicle Miles Traveled/Capita (source: FHWA, 2003 table VM-2) for 48 of the 50 US states. Click the graph to enlarge it.
However, tonight I wanted to take up a different theme. I have a somewhat contrarian stance on the idea, popular in certain parts of the peak oil community, that it's a good idea in the face of peak oil to move to the back of beyond and start trying to live off the land. My idea, prejudice, hypothesis, whatever we want to call it, was that rural economies produce less wealth but need to drive further, and therefore will suffer particularly hard as oil becomes less available.
So I decided to investigate this more carefully. It's hard to clearly delineate rural communities from urban in all the statistical series I needed, but what is generally available is state-by-state statistics (in the US). I figured that ought to be good enough for a first cut - we should be able to see how very urban states differ from very rural states.
So I got VMT statistics from the FHWA, 2003 table VM-2, gross state product statistics for 2003 from the Bureau of Economic Affairs, and population statistics from the Census Bureau, but the Wikipedia helpfully tabulates the states in the 2000 census in terms of Population, and also Population Density.
The first graph I produced was wealth created per capita (as measured by Gross State Product/capita) versus vehicle miles driven/capita:
Gross State Product/Capita (source: BEA, 2003) plotted versus Vehicle Miles Traveled/Capita (source: FHWA, 2003 table VM-2) for all US states. Click to enlarge.
Well, two states are clearly messing up the picture. I decided that we should sell Wyoming to Canada to pay down some of the national debt, and tow Delaware down to the Carribean to save most of our corporations the trouble of reincorporating themselves offshore.
There's probably a reasonable case for considering Delaware as a removable outlier due to it's special status as the headquarters of so many of our large corporations. However, I can't think of any good excuse for excluding Wyoming other than that it's having way too much influence on the trend for a state of small population and moderate area.
Anyway, after the dirty work is done:
Gross State Product/Capita (source: BEA, 2003) plotted versus Vehicle Miles Traveled/Capita (source: FHWA, 2003 table VM-2) for all US states except Delaware and Wyoming. Click to enlarge.
Prejudice confirmed, right? There appears to be a reasonably strong inverse relationship between states where people drive a lot, and states where people generate a lot of wealth. The technical criteria is the R2, which says that 42% of the variation in GSP/capita is explained by the inverse relationship with VMT/capita. It's not the only thing going on (58% of the variation remains to be explained by other things), but it's quite a big chunk of what's going on.
Well, not so fast.
When I delved into population density, to check that it really is rural/urban that explains this, it got more complicated. Here's vehicle miles driven/capita as a function of population density.
Vehicle Miles Traveled/Capita (source: FHWA, 2003 table VM-2) plotted against Population Density (source: US Census Bureau 2000 via Wikipedia) for all US states. Click to enlarge.
There is some trend for states of low population density to drive more, but it's not that strong (R2 of 22%). And then here's wealth created as a function of population density.
Gross State Product/Capita (source: BEA, 2003) plotted against Population Density (source: US Census Bureau 2000 via Wikipedia) for all US states. Click to enlarge.
This isn't that strong either. It's somewhat true that low population density states create less wealth/capita, but it's a weak relationship (R2 of 19%).
So while my initial hypothesis isn't exactly wrong---the correlations do run the way I expected---they aren't as strong as I expected. And, more interestingly, it looks like there must be some other linkage between driving a lot and producing less wealth. It doesn't seem to be just having low population density. I would like to know what that linkage is.
In particular, its intriguing that growing the economy appears to require driving more, and yet places that drive a lot produce less wealth per capita. It suggests something that I explored quite a bit back when I was looking at the lockstep relationship between GDP and VMT - I wonder if growing the edge of town is one of the harder things the economy has to do to grow, and so it has something to do with setting the rate of economic growth.
This would further prove (if the correlation exists and is positive), that we are indeed borrowing GDP growth from Mother Nature in the form of cheap gas. The scales have to balance eventually.
This is a common, but usually wrong, way to think about things.
We have oil in the ground because the dinosaurs failed to develop a biofuel program. We are using the energy that the dinosaurs (and the rest of their ecosystem) didn't use.
Obviously, oil is finite. And we're running out of ability to increase production capacity. But where, in these statements, are the quantities that must be balanced? Where is the repayment that must be made?
Obviously, we should conserve, and we're being pretty stupid in not developing alternatives to fossil fuels. But that is not the kind of apples-to-apples comparison that you can weigh on scales.
The idea that everything is zero-sum, and anything that seems beneficial must be repaid, is--in many contexts--wrong. If you don't look at the whole system, you can't say that the system is closed or zero-sum. Our entire earth is not a closed system, thanks to the sun.
We may well overshoot and crash, but that will be more of a karmic debt than a physical debt. As long as the sun is shining, there is no law of nature that says we have to run out of energy. Imagine how much better our prospects would be if, instead of spending $200 billion on the Iraq war, we had awarded two hundred billion-dollar prizes for half-million BOEPD reductions in fossil energy use.
Chris
If it is just the total population of the state divided by the total area of the state, then that may not tell you much. A large state may have most of it's population clustered in urban areas?
These days, I would say that the proportion of people living on the land is quite small and has gone down quite drastically in the last 50 years. Modern intensive farming techniques require fewer people to produce the same amount of produce (or even more).
I know that here in New Zealand, a lot of the population has migrated into big centres, while the rural areas have declined and sometimes even 'died'.
I think that a better measure would be to compare the population density of a state with the population density of its conties (the Census Bureau gives a very convenient xls file with all the different populations and densities). See what the variance is for each state. This will give you a measure to see if the distribution of the population is uniform (rural) or is non-uniform (urban). It looks like a fun exercise. It would be nice to complement your analysis with this information. But, unfortunately I am very busy today.
The Census Bureau also gives a nice picture:
In the west counties are larger (huge in fact). Some of those large counties house huge cities (Los Angeles) and unihabited mountainous stretches that dilute down the urban density figures.
Some counties house million + cities and yet are over half uninhabited. You dont get this in the east.
http://www.deloitte.com/dtt/research/0,2310,sid%253D1000%2526cid%253D28906,00.html
First of all, we have the obvious fact that what we call 'states' are merely lines on a map, and there is no inherent reason why demographics, income, and driving patterns should conform to lines on a map. For example, the Chicago metropolitan area has far more in common with the New York metropolitan area than does Chicago with downstate Illinois or New York City with upstate New York. So when you deal with per capita mileage in such a state you are really dealing with an averaging of highly urban and highly rural areas. What can that possibly tell you? My own state of Delaware is smaller than many counties in Texas but it has a highly surburanized northern part and a highly rural southern part. The income and driving patterns in each are very different.
I really think it's more of an urban vs rural thing. (A person living in NYC can walk to a movie, theatre while someone in Wyoming might have to make a 70-mile round trip.) I strongly suspect that If you use data available in terms of Statistical Metropolitan Areas, you will see these per capita numbers to be fairly similar from one SMA to another SMA. Then if you selected say 50 rural counties in different states at random and compared the data for them, you might see that they were not too far apart from each other.
By the way, on a day like this I'm all for your suggestion of towing Delaware down to the Carribean!
I fully agree with you about small, out of the way places. I used to do a good deal of business travel, and I always found it so depressing to be eating dinner at some mediocre franchised chain restaurant in a strip mall almost totally identical to any other strip mall in the country.
Just as a high degree of variation is essential for a healthy biosphere, so is a high degree of variation essential to a culture. Without it, we just become one big ant hill.
BTW what came first the joule or the watt-second?
Property taxes, however, are relatively low compared to neighboring New Jersey. Overall, the cost of living is not all that much different from neighboring equivalent areas in PA, MD, and NJ, particularly since real estate prices are now more in line with those states.
The absence of a sales tax is nice, but unfortunately DE has a de facto sales tax on cars by means of a registration 'fee' that is a certain percentage of the imputed value of the vehicle.
I really don't think there is all that much cross-border traffic from neighboring states to take advantage of the absence of sales tax. Anyway, that traffic would show up in the statistics for the neighboring states rather than DE.
State governments generally get the amount of money out of you that they want to, by one means or another. However, property taxes in NJ are really horrendous.
DE is an incorporation haven soley because it's incorporation laws are purposely lax and because it has a rather well developed corporate law system. It is also a good place to register a pleasure boat, which is why you can go to almost any marina on the East Coast and see boats with Wilmington, DE as their 'home port'.
First, it seems to me that time spent driving is by and large wasted. If we eliminate time spent with family or other pursuits as an alternative, there are two choices: spend the time commuting or spend the time working. Therefore, the greater the aggregate miles driven by a workforce, the lower the productivity (at least comparing similar workforces). If you include personal time, greater time behind the wheel inevitably means more money spend on daycare, restaurants, etc.
Second, I did some very minimal research on obesity rates versus miles driven per year among various OECD countries. Here in the U.S. we of course are the champions--greatest number of miles driven per year and highest obesity rate--and there appears to be a pretty consistent correlation. The more miles you drive, the fatter you are. It seems to me that this would also correlate to more health problems, more money spent on health care--and therefore lower productivity.
The best advice that I can give Americans is the following: (1) start trying to live on 50% of less of your current income and (2) try to reduce the distance between your job and where you live to as close to zero as possible.
(Not many hybrids down there, but the handful of Texans who commented on my Prius were all hybrid-friendly. I suppose the big SUV or pick-up is pretty expensive to run these days.)
Sales have definitely dropped from the late nineties, and of course SUV sales have plummeted 13.5% nationwide(1st Qt) but currently:
According to R. L. Polk & Co., 57 percent of new-car registrations in Texas last year were pickups and SUVs...Ford's F-Series pickups alone accounted for 8.9 percent of new cars registered with the state
And the last sentence:
"Apparently, the interest in gas-guzzler SUVs is more than just waning. It has disappeared."
A suburbanite who commutes through heavy traffic every day to work may not be able to easily change where/when, but they can certainly change what they drive - perhaps slashing gas usage by 50%.
Country dwellers might car-pool to the big box store, increasing passenger-miles while decreasing VMT.
etc.
Of course, gas prices high enough to drive that kind of adaptation are certainly going to trigger some "restructuring" as some fuel uses are discarded. Such economic turmoil could be called out as a GDP-VMT linkage, but it's really an after-affect.
Try removing the vehicle mile component from state GDP. Otherwise, you have vehicle miles on both sides of your model (imagine a state where the only economic activity was driving; the GDP and vehicle miles would perfectly correlate, violating assumptions of OLS regression).
This should make your model more robust, though the "fit" may decline (because you are reducing the identity component from the equation).
What you end up with is a relation between non-driving GDP (actual economic productivity?) and vehicle miles travelled (wasteful commuting?)
The answer none of us know, which I think your graphs attempt to answer, is how much GDP will actually be removed by "peak oil."
My not so humble opinion is that we get a feel with the graphs and etc., but that there are so many feedback loops, operating at so many different levels, that we won't know until we see it play out.
We proved (by experience) that the 2005 gas story didn't cause an economic stall ... but that is all we know. (I think important in that it paired high prices with a preceived one-time cause of hurricanes).
Some have suggested that it could be that one state has a few big cities and little population elsewhere, while the other state has lots of small towns spread around. The first state will drive less and be richer than the second, due to the benefits of city living (which are enormous and often unrecognized (especially around here where we see some pretty romantic and unrealistic IMO "back to the land" visions)).
Another factor could be that poor people need to save money so they will drive farther to find better prices, going to Walmart instead of the corner store for example.
Or perhaps poor people tend to be less competent and efficient at economic planning (which is one reason they are poor) and so they inadvertantly waste more of their resources, including by driving unnecessarily.
plus, the R2 is QUITE low for models of aggregated data on states...there's a lot of noise in there.
Remember, also there's a lot of stuff going on at the lowest unit of analysis, the individual (but the data's not available, I know I know)...still, I would caution everyone not to pull an ecological fallacy and say anything about individual behavior based on this aggregate level data. You can only compare state A to state B, not the people in those states or their behaviors.
Are you saying that you would generally expect R<sup>2</sup> to be low for aggregate data on states, so it's not surprising that these are low? Or that these R<sup>2</sup> in particular strike you as quite low relative to what you would expect?
So, that leads me to ask you to run a multivariate regression with all three in the equation...or at least a correlation matrix of all of the variables you're talking about.
and usually it is quite easy to find high correlations/R2 with aggregate data (because you are eliminating much of the stochasticity of those crazy human beings by aggregating them)...
"and usually it is quite easy to find high correlations/R2 with aggregate data (because you are eliminating much of the stochasticity of those crazy human beings by aggregating them)."
Well, but any such correlations we find should be more likely to be real right - noise effects will have averaged away?
Automobiles cost money. They are not free. They need gas, insurance, tires, maintenance, all of which are not free. You have to spend your valuable time in the vehicle being unproductive and, more importantly, being miserable. Automobiles degrade the environment. Highways degrade the land. Pollution degrades the air. Metals from catalytic converters poison the land.
Yeah, you can use graphs and statistics to compare some tiny little slice of reality and come to pretty much any conclustion you want. But it avoids the holistic issue -- the inherent degrading of EVERYTHING that the easy-motoring culture represents. That is what makes people poor. Money is not a clean sky. It is not clean water. It is not an uncluttered landscape. It is not a close relationship with the land, with family, friends and neighbors. Poor is having to live in, no, to be trapped in this immensely evil automobile hell we have built through our silly worship of all things tech, all things "efficient," and all things business.
These sorts of specious analyses which purport to somehow enlighten are in fact part of the problem. By excising the horrible interconnected negative aspects of the automobile culture and using a limited slice to somehow speak to how "poor" one might be if one drives this much or that much is a sad, sad testament to our lack of imagination, our unwillingness to confront the basic holistic problems, including overshoot and global warming, and the inherently bad logic of the limitless growth, high-tech society.
The hobbyist nature of these statistical analyses bespeaks the inherent flaw of humanity -- the willingness to count the bolts on the prow of the Titanic even as we glide towards certain ecological, social, economic and personal doom.
So sad.
(It's probably worth mentioning that I have spent a number of years living in a quite rural area (Humboldt Co, CA), and currently live in the city (San Francisco). Strictly for myself, I preferred the country for many of the reasons you mention. However, the city is a better place to support and educate a family so I'm here for now. I have also lived in cohousing communities in pursuit of that "close relationship" you mention. However, it would be foolish not to recognize that that it is a choice most people are not going to make.
So there is a strong flavor in your comments of wanting to impose your values on the great majority of Americans with different values.