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Schumpeterian growth with technological interdependence: An application to US states

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  • Deeken, Tim

Abstract

In this paper, the Schumpeterian growth model developed by Ertur and Koch (2011) that includes spatial interactions between units of observation working via R&D spillovers is presented in detail. The implications of this model and three additional growth models with and without spatial interaction that are nested within this framework are tested for the US states econometrically. It is found that investments in R&D have a positive impact on steady-state income per worker in the Schumpeterian growth model without complex interaction between states, but this effect is absent in the model proposed by Ertur and Koch (2011), even though the estimate for the coefficient measuring interconnectedness between regions is positive and significant. This latter result is robust to alternative specifications of the interaction matrix.

Suggested Citation

  • Deeken, Tim, 2015. "Schumpeterian growth with technological interdependence: An application to US states," Working Paper Series in Economics 75, Karlsruhe Institute of Technology (KIT), Department of Economics and Business Engineering.
  • Handle: RePEc:zbw:kitwps:75
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    More about this item

    Keywords

    R&D spillovers; Schumpeterian growth; spatial econometrics;

    JEL classification:

    • O18 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Urban, Rural, Regional, and Transportation Analysis; Housing; Infrastructure
    • O47 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Empirical Studies of Economic Growth; Aggregate Productivity; Cross-Country Output Convergence
    • R11 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Regional Economic Activity: Growth, Development, Environmental Issues, and Changes
    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models

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