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A simple index of innovation with complexity

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  • Fernandez Donoso, Jose

Abstract

Patents are the main source of data on innovation. Since most of the innovative activity happens outside of the patenting system, and since patents −and innovations- have different quality, complexity, and impact on each market, unweighted sums of patents and proxies are an imperfect indicator of a country’s innovative activity. I generate two very simple indices of innovation (one dependent on the size of a country, and another that normalizes country-size), based on weighting patents and exports by a complexity measure. Each index captures the technological complexity of innovations inside and outside the intellectual property rights system. I empirically analyze the rankings of these innovation indices, and contrast the results with technological development, GDP, and the existing mainstream innovation index.

Suggested Citation

  • Fernandez Donoso, Jose, 2017. "A simple index of innovation with complexity," Journal of Informetrics, Elsevier, vol. 11(1), pages 1-17.
    • Handle: RePEc:eee:infome:v:11:y:2017:i:1:p:1-17
    DOI: 10.1016/j.joi.2016.10.009
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    1. Tang, Xuli & Li, Xin & Ding, Ying & Song, Min & Bu, Yi, 2020. "The pace of artificial intelligence innovations: Speed, talent, and trial-and-error," Journal of Informetrics, Elsevier, vol. 14(4).
    2. Travis J. Lybbert & Mingzhi Xu, 2022. "Innovation‐adjusted economic complexity and growth: Do patent flows reveal enhanced economic capabilities?," Review of Development Economics, Wiley Blackwell, vol. 26(1), pages 442-483, February.
    3. José Fernández Donoso & Fernando Hernández, 2017. "International protection of intellectual property rights: a stochastic frontier index," Serie Working Papers 41, Universidad del Desarrollo, School of Business and Economics.
    4. Trung V. Vu, 2022. "Linking LGBT inclusion and national innovative capacity," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 159(1), pages 191-214, January.
    5. Chen, Yang & Li, Weiwei & Yi, Pingtao, 2020. "Evaluation of city innovation capability using the TOPSIS-based order relation method: The case of Liaoning province, China," Technology in Society, Elsevier, vol. 63(C).
    6. Zhao, Lu-Tao & Liu, Zhao-Ting & Cheng, Lei, 2021. "How will China's coal industry develop in the future? A quantitative analysis with policy implications," Energy, Elsevier, vol. 235(C).

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