Efficient industrial policy for innovation: If we could see further…

Public investment in science and technology is the centrepiece of many developed economies’ growth strategies. The rationale for these investments is that innovation generates positive externalities in the form of knowledge spillovers, and it is necessary to compensate for the (private) underinvestment in innovation (market failure).

A paper1 published in November 2021 develops a new framework to measure both direct and indirect knowledge spillovers from patent data, and a measure for the expected economic returns to subsidies —i.e. the sum of the private value and the externality generated by spillovers that can be used to efficiently allocate innovation support to different areas of innovative activity. They call it Industrial Strategy Index (IStraX).

Internal rates of return to a subsidy as estimated by IStraX (x-axis) for 8 countries (G7+China). Op. cit. Fig. 11

The graph shows two interesting (and intriguing) patterns

  • First, the average rates of returns vary strongly by country. While Japan, the United States and China show return rates well above 10%, France, Italy, Great Britain (and to a lesser extent Germany) show low return rates barely surpassing 5%.
  • Second, the correlation of IStraX in technology fields between countries is very low. In fact, many of these correlations are negative, and their (absolute) value rarely exceeds 0.5. These results suggest substantial benefits of tailoring industrial policy by country and leave little hope for a `one-size-fits-all’ approach.

But there is a lot more in the paper… Hidden and Illusory giants (explicit acknowlegment to Sir Isaac Newton’s famous quote)

This paper examines potential welfare gains of such vertical industrial policy for innovation. It develops measures of private and spillover value of patented innovations using global data on patents and their citations. Our new method identifies a large number ‘Hidden Giants’ – i.e. innovations scoring higher on our new spillover measure than on the traditional forward citation count measure – which are shown to be particularly prevalent among patents applied for by universities. The estimated distributions of private values by technology area are then used to parameterize a structural model of innovation. The model permits estimation of the marginal returns to technology-area-specific subsidies that reduce innovators’ R&D costs. Marginal returns are high when knowledge spillovers in the technology area are valuable, when private innovation costs are low, and when private values in a technology sector are densely distributed around the private cost. The results show large variation in the marginal returns to subsidy and suggest that targeted industrial policy would have helped mitigate underprovision of R&D over the time period studied. Variation in the extent to which knowledge spillovers are internalized within countries also makes a compelling case for supranational policy coordination, especially among smaller countries.

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(1) Guillard, Charlotte, Ralf Martin, Pierre Mohnen, Catherine Thomas, and Dennis Verhoeven. ‘Efficient Industrial Policy for Innovation: Standing on the Shoulders of Hidden Giants’. CEP Discussion Paper. Centre for Economic Performance, LSE, 4 November 2021. https://econpapers.repec.org/paper/cepcepdps/dp1813.htm.

Feature Image: Isaac Newton in WPAP, Yusrielo (detail).

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