Distance, scale and growth

Increasing returns to scale is essential to both spatial economics and macroeconomic growth. Spatial externalities imply external local increasing returns that generate an uneven spatial distribution of economic activity. While non-rival knowledge also implies increasing returns – in order to endogenise growth – this is not a spatial micro- foundation. Spatial theories of growth must be carefully specified to avoid unintended conclusions about the spatial economy and scale effects. This is demonstrated with a spatial endogenous growth model without scale effects that includes a spatial mechanism that facilitates agglomeration economies for innovation. In this class of models that combine spatial mechanisms with endogenous growth without scale effects, local increasing returns to scale imply that productivity, growth and interest rates are functions of the economy’s spatial distribution, but not its scale.

Increasing returns to scale is the basis for many powerful results in economics and economic geography. But the limitations of assumptions about returns to scale in economic growth theories are often ignored when applied to geography. This leads to an unintentional bias favoring scale and mistaken conclusions about geography, scale and growth. Alternatively, this bias is used as a convenient modeling trick by urban economists to describe agglomeration economies for innovation without examining the spatial mechanisms that actually create agglomeration economies. I discuss techniques to focus on the distinctly geographic mechanisms that define returns to scale at appropriate spatial scales.

This article builds an understanding of regional innovation specialisation by developing a multi-sector model with endogenous growth through quality improving innovations and spillovers from related technologies. The model provides an approach to incorporate the relatedness literature within the mainstream theoretical frameworks of endogenous growth and economic geography. Each firm’s technology sector and the location of other firms play a role in each firm’s ability to improve its own technology. As a result, firms prefer to co-locate in technologically compatible clusters. Without relying on scale assumptions, the model for the first time coherently links related variety knowledge spillovers to mainstream urban economic frameworks and demonstrates that clustering is possible in both core and peripheral areas.

The so‐called “new growth theory” is characterized by the now Nobel Prize winning insight that ideas are a nonrival input to and output from endogenous investment in innovation. Nonrivalry implies increasing returns to scale, but this also unintentionally creates an empirically disputed scale effect that a growing population implies an ever‐increasing growth rate. Empirical evidence supports fully‐endogenous growth without scale effects, but theoretical issues sustain the decades‐long dispute over exactly how to negate the scale effect. This article surveys theoretical approaches to resolving the scale effect and shows how four generations of endogenous growth theory are defined by the maturing of modeling techniques for constraining increasing returns. The synthesis suggests that the dispute over scale effects is really a narrative about how the powerful application of increasing returns has followed a standard theoretical development pattern. This implies that a fourth generation is now emerging that negates the scale effect while retaining fully‐endogenous growth without relying on assumptions of linearity. Instead, the market response to excessive increasing returns to innovation constrains explosive growth by expanding the market, rather than by a linear assumption. This latest class of endogenous growth models may be the final chapter to resolving the long‐running dispute.

In this paper we model growth using a scale-neutral approach to innovation allowing differences between regions to emerge due to regional mechanisms. In this model, agglomeration is growth enhancing as the scale effect for innovation arises from greater access to knowledge rather than any assumed scale effects in growth-modelling techniques. Furthermore, entrepreneurs are assumed to choose the location of firms endogenously so as to minimize the costs of innovation, transport and living. The effects of such mechanisms are such that any policies that increase knowledge spillovers between locations will enhance growth and equality, but may be destabilizing for agglomeration.