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GliderGuider Donating Member (1000+ posts) Send PM | Profile | Ignore Thu Aug-23-07 11:04 AM
Original message
Energy and population
In a response to my post on this topic a couple of days ago, depakid wondered about the country-by-country breakdown of per capita energy use, and what it would show about the population dynamics with varying energy consumption. I already had the stats for total energy consumption, life expectancy and total fertility rate for over 60 countries, so it was a simple matter to do up the graphs. As I expected, there is quite a strong correlation between per capita total energy consumption and both TFR and life expectancy. This essentially proves that the Demographic Transition Model is valid if energy is used as a proxy for development.

Here are the graphs. Note that TOE stands for Tonnes of Oil Equivalent, which is the result of converting all forms of energy used into the equivalent amount of oil.





In both cases I excluded some outliers to clarify the general trend. In the case of life expectancy I excluded countries like South Africa where LE has been heavily impacted by AIDS. Also, oil-producing countries with anomalously high energy consumption like Kuwait, Qatar, UAE, Saudi Arabia, USA, Canada and Norway were excluded. I'm reasonably sure that these exclusions don't damage the underlying point too much, as they do not constitute a major fraction of the world's population.

On the other hand, they do need to be considered if we want to answer the question, "How much energy would the world need to produce in order to achieve an overall TFR of 2.1 or less?" This would be required if we want to stabilize or reduce the world population. It's not sufficient to just look at the 2.1 point on the TFR graph and multiply the TOE that represents by the total number of people there are today. Both population and energy use will grow slowly over time, and the bulge at the top of the energy-use list represented by the excluded high-use countries will tend to increase the total amount of energy required. After all, it's a free market for energy and these nations tend to be rich, so they will continue to consume a disproportionate amount of energy. That will tend to drive up the "average" amount of oil required to drive down fertility.

One analysis I've done suggests that we would need to boost global energy production by 2.5 to 3 times between now and 2050 to arrive at a stable population of about 9 or 10 billion. More work needs to be done on this aspect of the problem, but it seems clear that we will not be able to rescue our population by simply cranking out more energy.

This is doubly true given the impending decline of oil and natural gas production and the ongoing decline in net energy return for humanity's entire energy portfolio. In addition, the confounding factors of climate change and generalized ecological collapse will require that we produce yet more energy to permit our adaptation to these rapidly changing circumstances.

At some point reductions in national per capita energy availability will result in declining populations in the affected countries. My gut instinct tells me that this will be due to reductions in life expectancy: fertility may not continue to drop under those circumstances, but it is unlikely to rise again as we slide back down the energy curve. This would be due to the effect of "perceived shrinking economic opportunity" on fertility noticed by demographer Virginia Abernethy. As these effects make thheir way up the wealth scale, eventually the overall global population will be impacted.

Of course a concerted effort towards increasing women's education and empowerment and access to family planning would interact with the effect of rising per capita energy consumption. That should tend to steepen the TFR correlation trend line, but I wouldn't expect it to have much effect on life expectancy which is where the bulk of the population reduction action will have to happen.
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phantom power Donating Member (1000+ posts) Send PM | Profile | Ignore Thu Aug-23-07 11:19 AM
Response to Original message
1. Outliers are generally excluded if they are result of measurement error.
Edited on Thu Aug-23-07 11:45 AM by phantom power
I mean, it's always tricky, excluding things that muddle your straight line fitting.

Maybe the "fair" way to do it would be to weight data by population for all nations. Or, conceptually: fit with 6.5 billion data points.
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GliderGuider Donating Member (1000+ posts) Send PM | Profile | Ignore Thu Aug-23-07 11:25 AM
Response to Reply #1
2. Unfortunately, statistics was my least favourite couse in university.
As a result it was the one I attended least, and I learned just enough to skate by on the final. A quarter-century on, that doesn't leave much residue of insight or capability...
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phantom power Donating Member (1000+ posts) Send PM | Profile | Ignore Thu Aug-23-07 12:04 PM
Response to Reply #2
3. Excel might be able to do it. I'm borderline excell-illiterate.
I never know when it's faster to break out Numerical Recipes and derive a modification, or hunt down a pre-implemented solution in a mound of documentation.

Software is like thermodynamics. You can't win, you can't break even, and you can't get out of the game.
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