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The tricky business of forecasting technological change is usually done in one of three ways: by treating new technology as a featureless, exogenous shock (referring to “black box” type models); by describing technology in terms of experience or learning curves that improve cost performance; or by relying on the often wildly varying opinions of experts.

But these are all ways of describing in highly aggregated fashion what economists are seeing as outputs rather than what causes those changes. To really understand technological change, you need to examine its underlying drivers and the motivations of the people and firms making it happen, says economist Deborah Strumsky of UNC Charlotte.

Researchers invited to a six-week working group at SFI this summer are studying technology, especially alternative energy technologies, by building technological trophic networks akin to food webs describing feeding interactions in ecosystems. The food web-like approach enables them to place a particular technology within its ecosystem and study how it evolves.

Like food webs, these networks have hierarchical structures, but they are based on individual technologies’ distances from the natural resource-based inputs needed to create them.

The interesting dynamic in this approach, Strumsky says, is that innovations and improvements at higher levels of the network percolate through the lower levels of the system and play a role in enabling technological change.

“If anyone in the larger trophic structure finds a new way to save costs, then I benefit too,” she says.

Products that are very close to their natural resources, like coal, oil, and natural gas, get far less benefit from trophic improvements due to the short distance from their natural resource base. In contrast, rapid and consistent progress of many high-tech goods such as photovoltaics is a function of the length and complexity of their trophic structures.

This matches what we see in the real world, she says. “If you control for other factors, the price of coal hasn’t changed since the late 1800s. But costs of photovoltaics have fallen by orders of magnitude since the 1970s.”

Strumsky, SFI External Professor Doyne Farmer of Oxford University, and Jose Lobo of Arizona State University organized the working group, which is funded by an alternative energy grant from the U.S. Department of Energy, and by the Institute for New Economic Thinking and SFI.

The ultimate goal of the project, Strumsky says, is to develop quantitative forecasting methods that support improved decisionmaking in the allocation of research and development investments.

More about the working group here