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A New Index Measure of Technological Capabilities for Developing Countries

Author

Listed:
  • Nabaz T. Khayyat

    (TEMEP, College of Engineering, Seoul National University)

  • Jeong-Dong Lee

    (TEMEP, College of Engineering, Seoul National University)

Abstract

This study is conducted to develop a new measurement tool to analyze the extent of innovation by developing nations. The role of science and technology in enhancing the rate of innovation is also investigated. The existing methods for measuring innovation such as Technology Index (WEF), Technology Achievement Index (UNDP), Industrial Development Scorecard (UNIDO), ArCo (Archibugi and Coco) and Science and Technology Index (RAND Corporation) are compared and based on their limitations a new tool with higher advantage is developed. The new index labeled as Technology Creation Index (TC-index) is decomposed into six distinct components. The index is estimated for 61 developing countries from Asia, North and South America and Africa. The countries are classified into three groups based on their extent of innovation derived from principal component analysis to assess the country group heterogeneity. The results suggest that in construction of the TC-index patents granted, human development index, local availability of specialized training and resources, foreign direct investment inflows, number of citations per science and education articles, secondary gross enrollment rate and science and education journals are identified as the main contributors to the higher rate of innovation in developing nations.

Suggested Citation

  • Nabaz T. Khayyat & Jeong-Dong Lee, 2012. "A New Index Measure of Technological Capabilities for Developing Countries," TEMEP Discussion Papers 201291, Seoul National University; Technology Management, Economics, and Policy Program (TEMEP), revised Jun 2012.
    • Handle: RePEc:snv:dp2009:201291
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    File URL: http://temep-repec.my-groups.de/DP-91.pdf
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    References listed on IDEAS

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    1. Andres, Antonio Rodriguez & Otero, Abraham & Amavilah, Voxi Heinrich, 2021. "Using Deep Learning Neural Networks to Predict the Knowledge Economy Index for Developing and Emerging Economies," MPRA Paper 109137, University Library of Munich, Germany.

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    More about this item

    Keywords

    Innovation measurement; technological infrastructure; diffusion of innovations; human skills; economic and social indicators.;
    All these keywords.

    JEL classification:

    • C19 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Other
    • C49 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Other
    • I32 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Measurement and Analysis of Poverty
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
    • O30 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - General
    • O32 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Management of Technological Innovation and R&D

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