Equation 2 · Who Builds 2100? The Demographic Engine of Technological Evolution
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Symbol n
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What the article says around this equation
where n is the growth rate of the population of researchers, measures how much easier or harder each new idea makes the next one to find (values below 1 are required for the model’s growth path to be stable at all — the discipline’s own name for this is diminishing returns to knowledge accumulation), and measures how much duplicated research effort — different teams stumbling onto the same idea — dilutes each additional researcher’s marginal contribution. The formula says something that should be intuitive from the fitness-landscape framing: if the population of people searching for new technology stops growing, n falls toward zero, and the long-run growth rate of ideas falls…
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where n is the growth rate of the population of researchers, measures how much easier or harder each new idea makes the next one to find (values below 1 are required for the model’s growth path to be stable at all — the discipline’s own name for this is diminishing returns to knowledge accumulation), and measures how much duplicated research effort — different teams stumbling onto the same idea — dilutes each additional researcher’s marginal contribution. The formula says something that should be intuitive from the fitness-landscape framing: if the population of people searching for new technology stops growing, n falls toward zero, and the long-run growth rate of ideas falls with it, one for one, unless something else changes or .
Sources cited in the article section
- [3] Are Ideas Getting Harder to Find? ↗
- [4] The Past and Future of Economic Growth: A Semi-Endogenous Perspective ↗
These citations give research context. Read each source to check which claims it supports.
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