National innovation systems, economic complexity, and economic growth: country panel analysis using the US patent data

  • Keun LeeEmail author
  • Jongho Lee
Regular Article


This study examines the impacts of national innovation systems (NIS) and economic complexity index (ECI) on economic growth. A composite index of NIS is developed by using US patent data as a weighted sum of three, four or five variables among the following: concentration of assignees, localization, originality, diversification, and cycle time of technologies. Growth regressions confirm the significant and robust impacts of NIS3a, NIS4a, and NIS5 indices on economic growth. The common feature of these NIS indices is that they have the same component variables as their ingredients, and these are originality, cycle time, and technological diversification. NIS3s is the most parsimonious and powerful among all indices. The robustness of ECI is questionable because ECI loses significance after adding government expenditure and terms of trade variables into the regression model. Results confirm the overall importance of NIS in economic growth and justify policy efforts to improve NIS. This research is one of the first to generate a robust NIS index by using patent data only without many data requirements and free from the problem of cross-country comparability of underlying variables.


National innovation systems Economic complexity Economic growth Patents Index 

JEL classification

B52 C43 C81 O31 O34 O38 



  1. Abramovitz M (1986) Catching up, forging ahead, and falling behind. J Econ Hist 46:385–406CrossRefGoogle Scholar
  2. Acemoglu D, Johnson S, Robinson JA (2001) The colonial origins of comparative development: an empirical investigation. AER 91:1369–1401CrossRefGoogle Scholar
  3. Aghion P, Howitt P (1992) A model of growth through creative destruction. ECTA 60:323–351CrossRefGoogle Scholar
  4. Archibugi D, Coco A (2004) A new indicator of technological capabilities for developed and developing countries (ArCo). WD 32:629–654CrossRefGoogle Scholar
  5. Arellano M, Bover O (1995) Another look at the instrumental variable estimation of error-components models. J Econ 68:29–51CrossRefGoogle Scholar
  6. Barro RJ (2003) Determinants of economic growth in a panel of countries. Ann Econ Financ 4:231–274Google Scholar
  7. Castellacci F (2008) Technological paradigms, regimes and trajectories: manufacturing and service industries in a new taxonomy of sectoral patterns of innovation. Res Policy 37:978–994CrossRefGoogle Scholar
  8. Castellacci F (2011) Closing the technology gap? Rev Dev Econ 15:180–197CrossRefGoogle Scholar
  9. Castellacci F, Natera JM (2015) The convergence paradox: the global evolution of national innovation systems. In: Archibugi D, Filippetti A (eds) The handbook of global science, technology, and innovation. Wiley Blackwell, ChichesterGoogle Scholar
  10. Charnes A, Cooper WW, Rhodes E (1978) Measuring the efficiency of decision making units. Eur J Oper Res 2:429–444CrossRefGoogle Scholar
  11. Coe NM, Hess M, HWc Y, Dicken P, Henderson J (2004) ‘Globalizing’ regional development: a global production networks perspective. T I Brit Geogr 29:468–484CrossRefGoogle Scholar
  12. Cohen WM, Levinthal DA (1990) Absorptive capacity: a new perspective on learning and innovation. Adm Sci Q 35:128–152Google Scholar
  13. Colombage, S (2016) A grounded demolition of Richard Hausmann’s economic thinking for Lanka. Thuppahi’s Blog. Access 27 November 2016
  14. Cornell University, INSEAD, WIPO (2018) The global innovation index 2018: energizing the world with innovation. Ithaca, Fontainebleau, and GenevaGoogle Scholar
  15. Desai M, Fukuda-Parr S, Johansson C, Sagasti F (2002) Measuring the technology achievement of nations and the capacity to participate in the network age. J Hum Dev Capabil 3:95-122Google Scholar
  16. Dosi, G, Pavitt K, Soete L (1990) The economics of technical change and international trade. LEM Book SeriesGoogle Scholar
  17. Dosi M, Fukuda-Parr S, Johansson C, Sagasti F (2002) Measuring the technology achievement of nations and the capacity to participate in the network age. J Hum Dev 3:95–122CrossRefGoogle Scholar
  18. Edquist C (1997) Systems of innovation approaches: their emergence and characteristics. In: Edquist C (ed) Systems of Innovation: technologies, institutions and organizations. Pinter/Cassell, LondonGoogle Scholar
  19. European Commission (2018) European innovation scoreboard. Publications Office of the European Union, LuxembourgGoogle Scholar
  20. Fagerberg J (1987) A technology gap approach to why growth rates differ. Res Policy 16:87–99CrossRefGoogle Scholar
  21. Fagerberg J (1988) International competitiveness. EJ 98:355–374Google Scholar
  22. Fagerberg J, Godinho M (2004) Innovation and catching-up. In: Fagerberg J, Mowery D (eds) The Oxford handbook of innovation. Oxford University Press, OxfordGoogle Scholar
  23. Fagerberg J, Srholec M (2008) National innovation systems, capabilities and economic development. Res Policy 37:1417–1435CrossRefGoogle Scholar
  24. Fagerberg J, Verspagen B (2002) Technology-gaps, innovation-diffusion and transformation: an evolutionary interpretation. Res Policy 31:1291–1304CrossRefGoogle Scholar
  25. Fidrmuc J (2004) Migration and regional adjustment to asymmetric shocks in transition economies. J Comp Econ 32:230–247CrossRefGoogle Scholar
  26. Filippetti A, Peyrache A (2011) The patterns of technological capabilities of countries: a dual approach using composite indicators and data envelopment analysis. WD 39:1108–1121CrossRefGoogle Scholar
  27. Freeman C, Clark J, Soete L (1982) Unemployment and technical innovation. Frances Pinter, LondonGoogle Scholar
  28. Furman JL, Porter ME, Stern S (2002) The determinants of national innovative capacity. Res Policy 31:899–933CrossRefGoogle Scholar
  29. Gerschenkron A (1962) Economic backwardness in historical perspective: a book of essays. Harvard University Press, CambridgeGoogle Scholar
  30. Hall, BH, Jaffe AB, Trajtenberg M (2001) The NBER patent citation data file: lessons, insights and methodological tools. NBER discussion paper series, 3094Google Scholar
  31. Hanson GH, Mataloni RJ Jr, Slaughter MJ (2005) Vertical production networks in multinational firms. REStat 87:664–678Google Scholar
  32. Hausmann R, Hidalgo CA, Bustos S, Coscia M, Chung S, Jimenez H, Simoes A, Yildirim MA (2011) The atlas of economic complexity: mapping paths to prosperity. MIT Press, CambridgeGoogle Scholar
  33. Hausmann R, Hidalgo CA, Bustos S, Coscia M, Simoes A, Yildirim MA (2014) The atlas of economic complexity: mapping paths to prosperity. MIT Press, CambridgeCrossRefGoogle Scholar
  34. Hotelling H (1933) Analysis of a complex of statistical variables into principal components. J Educ Psychol 24:417CrossRefGoogle Scholar
  35. Inoua, S (2016) A simple measure of economic complexity. arXiv preprint arXiv:1601.05012Google Scholar
  36. Jaffe AB, Trajtenberg M (2002) Patents, citations, and innovations: A window on the knowledge economy. MIT press, CambridgeGoogle Scholar
  37. Jaffe AB, Trajtenberg M, Henderson R (1993) Geographic localization of knowledge spillovers as evidenced by patent citations. QJE 108:577–598CrossRefGoogle Scholar
  38. Kim YK, Lee K (2015) Different Impacts of Scientific & Technological Knowledge on Economic Growth: Contrasting S&T Policy in East Asia and Latin America. Asian Econ Policy R 10:43-66Google Scholar
  39. Lee K (2013) Schumpeterian analysis of economic catch-up: knowledge, path-creation, and the middle-income trap. Cambridge University Press, CambridgeCrossRefGoogle Scholar
  40. Lee K, Kim B-Y (2009) Both institutions and policies matter but differently for different income groups of countries: determinants of long-run economic growth revisited. WD 37:533–549CrossRefGoogle Scholar
  41. Lucas RE Jr (1988) On the mechanics of economic development. J Monet Econ 22:3–42CrossRefGoogle Scholar
  42. Lundvall B-Å (1992) National systems of innovation: toward a theory of innovation and interactive learning. Anthem Press, LondonGoogle Scholar
  43. Malerba F (2005) Sectoral systems of innovation: a framework for linking innovation to the knowledge base, structure and dynamics of sectors. Econ Innovat New Tech 14:63-82Google Scholar
  44. Mankiw NG, Romer D, Weil DN (1992) A contribution to the empirics of economic growth. QJE 107:407–437CrossRefGoogle Scholar
  45. Marshall MG, Gurr TR, Jaggers K (2017) Polity IV project: Political regime characteristics and transitions, 1800-2016. Center for Systemic PeaceGoogle Scholar
  46. Melyn, W, Moesen W (1991) Towards a synthetic indicator of macroeconomic performance: unequal weighting when limited information is available. K.U. Leuven Public Economics Research Papers 17Google Scholar
  47. Nardo, M, Saisana M, Saltelli A, Tarantola S, Hoffman A, Giovannini E (2005) Handbook on constructing composite indicators. OECD Statistics Working Papers 03Google Scholar
  48. Nelson RR (1993) National Innovation Systems: a comparative analysis. Oxford University Press, OxfordGoogle Scholar
  49. Ohkawa K, Rosovsky H (1973) Japanese economic growth: trend acceleration in the twentieth century. Stanford University Press, StanfordGoogle Scholar
  50. Orefice G, Rocha N (2014) Deep integration and production networks: an empirical analysis. World Econ 37:106–136CrossRefGoogle Scholar
  51. Palmer J, Richards I (1999) Get knetted: network behaviour in the new economy. J Knowl Manag 3:191–202CrossRefGoogle Scholar
  52. Pearson K (1901) LIII. On lines and planes of closest fit to systems of points in space. Lond.Edinb.Dubl.Phil.Mag. 2:559–572CrossRefGoogle Scholar
  53. Romer PM (1990) Endogenous technological change. J Polit Econ 98:S71–S102CrossRefGoogle Scholar
  54. Sala-i-Martin XX (1997) I just ran four million regressions. AER 87:178-183Google Scholar
  55. Schölkopf B, Smola A, Müller KR (1997) Kernel principal component analysis. In International Conference on Artificial Neural Networks. Springer, Berlin Heidelberg, pp.583-588Google Scholar
  56. Schumpeter JA (1934) The theory of economic development. Harvard University press, CambridgeGoogle Scholar
  57. Solow RM (1956) A contribution to the theory of economic growth. Q J Econ 70:65-94Google Scholar
  58. Toya H, Skidmore M (2007) Economic development and the impacts of natural disasters. Econ Lett 94:20–25CrossRefGoogle Scholar
  59. Trajtenberg M, Henderson R, Jaffe A (1997) University versus corporate patents: a window on the basicness of invention. Econ Innov New Technol 5:19–50CrossRefGoogle Scholar
  60. USPTO (1976-2017) Patent Grant Red Book (Full Text)Google Scholar
  61. Verspagen B (1991) A new empirical approach to catching up or falling behind. Struct Chang Econ Dyn 2Google Scholar
  62. World Bank (2017) World development indicators. The World BankGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of EconomicsSeoul National UniversitySeoulSouth Korea
  2. 2.Barun ICT Research CenterYonsei UniversitySeoulSouth Korea

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