Is agglomeration really good for growth? Global efficiency, interregional equity and uneven growth

Abstract

According to NEG literature, spatial concentration of industrial activities increases growth at the regional and aggregate level without generating regional growth differentials. This view is not supported by the data. We extend the canonical model with an additional sector producing non-tradable goods which benefits from localized knowledge spillovers coming from the R&D performing industrial sector. This view, motivated by the evidence, generates both an anti-growth and a pro-growth effect of agglomeration for both the deindustrializing and the industrializing regions and leads to two novel results: 1) when agglomeration takes place, growth is lower in the periphery; 2) agglomeration may have a negative effect on the growth rate of real income, both at the regional and at the aggregate level. Our conclusions have relevant policy implications: contrary to the standard view, current EU and US regional policies favouring industrial dispersion might be welfare-improving both at the regional and the aggregate level and may reduce regional income disparities

Does Urban Industrial Agglomeration Lead to the Improvement of Land Use Efficiency in China? An Empirical Study from a Spatial Perspective

“…Using panel data, [32] found that specialized agglomeration has a negative impact on the value-added growth of Chinese provinces. [33] found that agglomeration has a negative impact on the development of regional periphery and the growth rate of income at the areas of periphery and clusters. Clearly, under different circumstances, industrial agglomerations can cause different effects.…”

Introducing regional competitiveness and development: contemporary theories and perspectives

“…This means that rising incomes may be offset by rising prices, particularly those relating to housing, leading to individuals seeking cheaper housing in other locations, and similarly firms seeking lower cost bases. This means that regions can both diverge and converge over time (Cerina and Mureddu, 2014). What both groups of theories pay less attention to are cases where large changes take place due to new innovations that provide opportunities for previously less successful locations (Scott and Storper, 1987) or where pre-existing institutions may hinder previously successful regions from exploiting these innovations (Chinitz, 1961;Boschma and Frenken, 2006;Boschma and Martin, 2007).…”

Computational Trust Management in Economics Phenomena Research

“…It is a common situation in science, including economics, that even decades old theoretical models have to be improved to meet real data (see, e.g. Cerina, Mureddu 2014;Mori, Smith 2015;Bode, Mutl 2010). This method will probably be no exception.…”