The holiday light market is now dominated by energy-efficient LEDs. According to BC Hydro:
The big difference is that they use up to 90 per cent less energy than incandescent lights, which means your holiday lighting charges could be as much as 90 per cent less than if you used incandescent lights only.
The charges could be 90 percent less. But will they be?
I'm writing this on March 8th. When I look out the window, I see my neighbour's holiday lights still shining brightly, even though we're closer to Easter than Christmas. Yes, I have a few lights up too.
In environmental economics, this phenomenon is called the rebound effect. But it's just basic economics - a reduction in price will increase the quantity demanded.
A refrigerator, for example, is on 24 hours a day anyways, and many people have only enough room in their home for one fridge. Because there is limited scope to increase refrigerator use, more energy-efficient fridges would be expected to lead to substantial energy savings.
But what about lighting? A recent paper by Jeff Tsao and co-authors shows the exponential growth of light consumption over three centuries in the U.K. The vertical axis has a logarithmic scale. This diagram shows that light consumption at the end of the 20th century was 100 times greater than light consumption at the beginning of the century.
This diagram documents the rapid increase in lighting consumption, but it doesn't tell us about the demand for lighting. That increase in consumption could reflect population growth, increased income, or decreased lighting costs.
Tsao and co-authors are physicists, not economists. If they were economists, they might say something like: with Cobb-Douglas preferences, the demand for lighting is given by:
where q=quantity demanded, Y=income, and p=price of lighting. This demand function implies that expenditures on lighting, p*q, is a constant portion of GDP.
Because they are physicists, Tsao et al write it slightly differently:
φ = β (gdp/CoL)
where φ=per capita light consumption, and CoL is the cost of lighting. But it's just a standard Cobb-Douglas demand function, with slightly different notation.
They argue that this relationship provides a good fit to the available data on light consumption, with a value of β = 0.0072:
Tsao et al's research was reported in The Economist: "They predict that the introduction of solid-state lighting could increase the consumption of light by a factor of ten within two decades."
Now this is one of those instances when intermediate micro comes in handy.
Recall that Tsao et al assume Cobb-Douglas preferences. They are assuming that consumers devote a constant fraction of their income to lighting (CoL*φ = β*gdp). So it's hardly surprising that they predict a 90% decrease in the cost of lighting will increase the quantity demanded ten-fold. Given their assumptions, they could not possibly have obtained any other result.
In their defence one might say "but the data fit their assumed functional form pretty well." Unfortunately, it is very difficult to determine the right underlying functional form from just a few observations, most of which are piled one on top of another.
Tsao et al's results matter, because the size of the rebound effect is the subject of passionate debate. My sense is that some people feel that the existence of rebound effects undermines the case for development and adoption of new, more energy efficient technologies. Yet intermediate micro (or even Econ 1000) shows that this is wrong. As the first picture in this post shows, rebound effects make consumers better off, by increasing their 'consumer surplus', the difference between the benefits they get from consuming a good and the price they actually have to pay for it. Indeed, the bigger the rebound effect, the bigger the increase in the consumer surplus from the adoption of new technologies.
As for me, I'm just waiting for the snow to melt, and watching to see when the last of the winter lights get taken down.