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Growth, heterogeneous technological interdependence,and spatial externalities: Theory and Evidence

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  • Miranda, Karen
  • Manjón Antolín, Miguel C.
  • Martínez Ibáñez, Oscar

Abstract

We present a growth model with interdependencies in the heterogeneous technological progress, physical capital and stock of knowledge that yields a growth-initial equation that can be taken to the data. We then use data on EU-NUTS2 regions and a correlated random effects specification to estimate the resulting spatial Durbin dynamic panel model with spatially weighted individual e ects. QML estimates support our model against simpler alternatives that impose a homogeneous technology and limit the sources of spatial externalities. Also, our results indicate that rich regions tend to have higher "unobserved productivity" and are likely to stay rich because of the strong time and spatial dependence of the GDP per capita. Poor regions, on the other hand, tend to enjoy "unobserved productivity" spillovers but are like to stay poor unless they increase their saving rates. Keywords: correlated random effects, Durbin model, economic growth, spatial panel data. JEL Classification: C23, O47

Suggested Citation

  • Miranda, Karen & Manjón Antolín, Miguel C. & Martínez Ibáñez, Oscar, 2018. "Growth, heterogeneous technological interdependence,and spatial externalities: Theory and Evidence," Working Papers 2072/307363, Universitat Rovira i Virgili, Department of Economics.
  • Handle: RePEc:urv:wpaper:2072/307363
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    References listed on IDEAS

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    More about this item

    Keywords

    Anàlisi de dades de panel; Creixement econòmic; 33 - Economia;
    All these keywords.

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • O47 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Empirical Studies of Economic Growth; Aggregate Productivity; Cross-Country Output Convergence

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