Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Technological interdependencies predict innovation dynamics   We propose a simple model where the innovation rate of a technological domain
depends on the innovation rate of the technological domains it relies on. Using
data on US patents from 1836 to 2017, we make out-of-sample predictions and
find that the predictability of innovation rates can be boosted substantially
when network effects are taken into account. In the case where a technology$'$s
neighborhood future innovation rates are known, the average predictability gain
is 28$\%$ compared to simpler time series model which do not incorporate
network effects. Even when nothing is known about the future, we find positive
average predictability gains of 20$\%$. The results have important policy
implications, suggesting that the effective support of a given technology must
take into account the technological ecosystem surrounding the targeted
technology.

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The categories of this paper are: hep-ph
21
The categories of this paper are: adap-org
19
The categories of this paper are: eess
14
The categories of this paper are: math-ph
12
The categories of this paper are: nucl-th
31
The categories of this paper are: ao-sci
15
The categories of this paper are: nucl-ex
24
The categories of this paper are: dg-ga
33
The categories of this paper are: plasm-ph
36
The categories of this paper are: cmp-lg
27
The categories of this paper are: comp-gas
9
The categories of this paper are: nlin
28
The categories of this paper are: alg-geom
6
The categories of this paper are: astro-ph
7
The categories of this paper are: hep-th
26
The categories of this paper are: bayes-an