Specialization, Knowledge Dilution, and Scale Effects in an IO-Based Growth Model

Peretto, Pietro F.; Smulders, J.A.

doi:10.2139/ssrn.137987

Cited by 8 publications

(4 citation statements)

References 30 publications

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“…As Jones himself (1995a) points out, such a result is not corroborated by the data and, therefore, it should be rejected on empirical grounds (Jones, 1995b). Recently, many works (Kortum, 1997;Aghion and Howitt, 1998, Chap.12;Dinopoulos and Thompson, 1998;Howitt, 1999;Peretto, 1998;Peretto and Smulders, 1998;Segerstrom, 1998;Young, 1998) attempted to find a key to this apparent riddle. But, unfortunately, despite the title of some of their papers, the result remains that a scale effect continues to show itself either in the real per-capita income level, or in the per-capita growth rate;…”

Section: Discussionmentioning

confidence: 99%

On Scale Effects, Market Power and Growth when Human and Technological Capital are Complements

Bucci

2000

SSRN Journal

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Section: Discussionmentioning

confidence: 99%

On Scale Effects, Market Power and Growth when Human and Technological Capital are Complements

Bucci

2000

SSRN Journal

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“…Recent theoretical works trying to eliminate the scale effect in an innovation-driven growth model include, among others, Kortum (1997), Aghion and Howitt (1998a: Ch. 12), Dinopoulos and Thompson (1998), Peretto (1998), Peretto and Smulders (1998), Segerstrom (1998), Young (1998), Howitt (1999, Bucci (2001), among others. Indeed, according to Aghion and Howitt (1998a), the increase in R&D investment has not been so high as data seem to suggest and consequently the scale effect predicted by some endogenous growth models is not to be considered as unreasonable as initially thought.…”

Section: Technology Scarce Inputs and The Interplay Betweenmentioning

confidence: 99%

Horizontal Innovation, Market Power and Growth

Bucci

2003

International Economic Journal

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I build a generalised model of horizontal product innovation and economic growth taking explicitly into account the most relevant insights stemming from the recent literature on this topic. What results from the analysis is that, when innovation is both deterministic and horizontal, the relationship between market power and aggregate growth is not robust at all. It is also found that not only technology, but also the inter-sectoral competition for the same resource affects growth. This is particularly relevant in terms of public policies aimed at the strategic allocation of skilled workers to the different sectors of the economy. [D43, L16, O31, O41]

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“…Increases in the steady-state level of R&D raise technology and income per capita at any point in time, but they do not raise the growth rate. 21 Young (1998), Aghion and Howitt (1998a, chap.12), Dinopoulos and Thompson (1998), Peretto (1998), and Peretto and Smulders (1998) remove the scale effects property by essentially the same mechanism as the one developed by exogenous Schumpeterian growth models. They introduced the concept of localized intertemporal R&D spillovers.…”

Section: Randd Racesmentioning

confidence: 99%

The dynamic effects of general purpose technologies on Schumpeterian growth

Petsas¹

2005

Entrepreneurships, the New Economy and Public Policy

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Abstract. General purpose technologies (GPTs) are drastic innovations, such as electrification, the transistor, and the Internet, that are characterized by the pervasiveness in use, innovational complementarities, and technological dynamism. The transitional and long-run dynamic effects of a GPT are analyzed within a quality-ladders model of scale-invariant Schumpeterian growth. The diffusion path of a GPT across a continuum of industries is governed by S-curve dynamics. The initial balanced growth equilibrium exhibits endogenous growth and no industry has adopted the new GPT. The final steady-state equilibrium, in which all industries have adopted the new GPT, exhibits a higher steady-state Schumpeterian growth and a higher per capita R&D. The model generates a unique, stable saddle-path. During the transition path, the measure of industries that adopt the new GPT increases, consumption per capita falls, and the interest rate increases. The growth rate of the stock market depends negatively on the rate of GPT diffusion process and the magnitude of the GPT-ridden R&D productivity gains, and positively on the rate of population growth. It also follows a U-shaped path during the diffusion process of the new GPT. Finally, the model generates transitional growth cycles of per-capita GNP.

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Specialization, Knowledge Dilution, and Scale Effects in an IO-Based Growth Model

Cited by 8 publications

References 30 publications

On Scale Effects, Market Power and Growth when Human and Technological Capital are Complements

On Scale Effects, Market Power and Growth when Human and Technological Capital are Complements

Horizontal Innovation, Market Power and Growth

The dynamic effects of general purpose technologies on Schumpeterian growth

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