2010-06-23 12:06

Correlation between US GDP and fossil transport fuels: 0.96

There is nothing controversial with the strong linkage between economic growth and the consumption of fossil fuels, at least for transports. I have earlier shown the high correlation between Swedish economic growth and the consumption of gasoline, diesel and jet fuel kerosene.

It is about time to do the same thing for the US.

The correlation between GDP and the sum of the consumption of fossil transport fuels is extremely high, 0.96. Like in Sweden, the correlation is even higher for diesel, 0.98, and lower for jet fuel kerosene.

A comparison between the two countries follows.

Correlation between GDP and all fossil transport fuel consumption
US: 0.96
Sweden: 0.95

Correlation between GDP and diesel consumption
US: 0.98
Sweden: 0.98

Correlation between GDP and gasoline consumption
US: 0.92
Sweden: 0.87

Correlation between GDP and jet fuel kerosene consumption
US: 0.76
Sweden: 0.89

For some reason the correlation between economic growth and jet fuel kerosene is higher in Sweden than the US.

Let me present a solution to the problem with an economy strongly dependent of transports fueled by fossil fuels as in both the US and in Sweden. Send the economy into a more or less permanent recession in order to keep pace with declining oil production in the aftermath of global peak oil.

Maybe not what unrealistic cornucopians would like to see as a solution?

Eternal growth is not possible in a finite world.
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4 kommentarer:

  1. Herregud... Så med andra ord kommer allting braka fint och smidigt när bränslet börjar sina. Chocken bör ju bli otroligt stor för länderna som inte är redo.

  2. The author makes a mistake in assuming correlations tell us about causality. Probably this is the situation:

    Weak economy implies little fuel consumption
    Strong economy implies large fuel consumption
    Low price implies high consumption
    High price implies low consumption (through use of other fuels or weaker economy)

  3. And you just made assumptions about causality on your own. By mentioning the word "probably" I guess you can give us just that, with what probability can you say that your assumption is correct, and why?

  4. What are the eia source codes that you used for the data?