Capítulo 3 Descripción de Módulos de E/S binarias
3.5 Características y diagramas de cableado de los módulos de salidas con
This section summarises the similarities and differences between economic geography and endogenous growth, particularly examining the role of innovation. While many aspects have already been described in the previous sections, the purpose of this section is to bring the three areas together as a foundation for developing the models presented in the rest of the thesis.
2.4.1
Similarities
The techniques used in endogenous growth models and NEG have many similarities. In endogenous growth models with horizontal innovation, consumers have a love for variety (Baldwin et al., 2003). Similarly, both models have monopolistic competition and increasing returns. This gives firms and agents incentives about how to invest in innovative activities or where to locate. This eventually led to the development of endogenous growth models that
combine features of the NEG. The fundamental use of Dixit-Stiglitz competition means modelling approaches are particularly compatible.1 Product variety models (horizontal innovation) work well with core-periphery models in the NEG and growth literature (Baldwin et al., 2003). Chapter 3 describes how endogenous growth theory has been combined with the NEG in this way. These similarities suggest there are further opportunities for combining the two areas of literature.
The systems of innovation literature also has similarities with both endogenous growth and NEG. Both systems of innovation and endogenous growth models recognise that the source of growth is innovation. They also recognise the circular causality that innovation develops knowledge which is used in developing further innovations. This is referred to in the literature on economic dynamics as a positive feedback loop. This recognition of innovation within endogenous growth models suggests future models could benefit further from the insights of the innovation systems literature. While some models just assume that innovation occurs with a proxy for knowledge as an input, models should also take account of how knowledge is used, created and geographically constrained.
Similarly, the innovation and economic geography literatures recognise regional differ- ences, agglomeration and the importance of cities. Modelling techniques, such as those used with other spatial phenomenon like transport costs, could be similarly applied to innovation inputs. As such, endogenous growth models can benefit from findings in both the innovation and economic geography literatures. For example, some endogenous growth models include human capital and economic geography also considers the spatial distribution of this production factor. While NEG models include trade and transport costs these can also be brought into endogenous growth models as is shown in Chapter 3.
2.4.2
Differences
However, there are also key differences that cannot be so easily combined. Endogenous growth models with vertical innovations assume firms with monopoly power. However, models with horizontal innovation and models in the NEG use monopolistic competition and have not previously accounted for the Schumpeterian effect of creative destruction. Up until now there has been no progress to combine Schumpeterian or quality ladders models (vertical innovation) with the core-periphery model. As far as the author is aware, the models presented in Chapters 4 and 5 are the first endogenous growth models with quality improvements or creative destruction to incorporate two regions and spatial externalities. In this type of model, creative destruction allows the innovating firm to achieve a higher profit than their competitors with depreciated varieties and the innovator would have a preference for production in a larger region.
1A full exploration of the contributions that followed from the publication of Dixit and Stiglitz (1977)
Economic geography offers implications for innovation and economic growth. Martin and Sunley (1998) note the limitations of endogenous growth theory when applied to regional development. Human capital, technological progress and economic growth are all uneven in spatial economics. Future growth theories need to include the implications of economic geography in both the growth outcomes and the inputs to technological progress. The dissemination of innovations, technology and knowledge across regions, between countries and throughout the economy is affected by the geographic characteristics of those economies. Core-periphery models have difficulty including geographical mechanisms for knowledge spillovers. Inequality between regions in these models is largely because of transport costs and does not recognise the other advantages of cities and agglomeration. Future models should take account of the implications offered by the systems of innovation literature to geographically model knowledge spillover mechanisms. To develop a mechanism for knowledge spillovers is challenging. Understanding that knowledge is largely tacit, knowledge spillovers are highly localised. Knowledge transfer is highly dependent on interaction and face-to-face contact as in McCann (2007) which presents a mechanism for showing how firms and agents choose location and their level of innovation through the intensity of face-to-face contact.
Furthermore, innovation as a concept is difficult to model within endogenous growth theories due to its nature. It is a broad concept generally referring to some knowledge inputs and potentially a profit motive. But the many kinds of innovations, the different ways inputs develop into innovations, and the multi-stage process from basic science and invention to its application as an innovation and its development as a market, are far too complex for endogenous growth theory to fully account for in an elegant and tractable model. Introducing some complexity requires the use of simulations to understand the effects on growth from a better understanding of innovation.
Despite this complexity, the models presented in this thesis in Chapters 4 to 6 add new understandings of innovation to endogenous growth theory in three elegant and mostly tractable theoretical models. Where necessary to aid understanding, the results of simple simulations are included along with analysis of the implications for economic growth and policy.