Infrastructure and Growth in a Spatial Framework: Evidence from the EU regions

Abstract

This paper examines the return to infrastructure in the European Union regions in a spatial framework. It innovates on the earlier literature on infrastructure and growth by a combination of regional focus, disaggregation of infrastructure types and consideration of spatial dependence. Different types of infrastructure capital are considered as determinants of economic performance at the Nomenclature des Unités Territoriales Statistiques level. To account for growth spillovers among regions, a spatial Durbin model is estimated. The results confirm the important role of infrastructure and identify the highest rates of return as associated with telecommunication, quality and accessibility of transportation networks, with a positive impact of roads and railways.

Notes

For a review of early contributions, including those of Munnell (1990, 1991)and Morrison and Schwartz (1994), see Gramlich (1994) and Sturm (1998). For recent surveys, see Agenor and Moreno-Dodson (2006), Romp and de Haan (2007) and Straub (2008).

See Appendix 1 for a list of regions and countries in our sample.

EU Funds are transferred from the EU to Member States and tied to assistance to regional or national programmes.

Base year: 1998. Linear depreciation rate of 2.5%.

Measured as individuals who ordered goods or services over the Internet for private use (Eurostat).

On this issue, see Le Gallo and Ertur (2003) and Ertur and Koch (2006).

This method provides sample draws from posterior distribution of model parameters and allows for inference on the estimates of direct, indirect and total effects. Implementation of this method was done using LeSage'e econometric toolbox for Matlab and is based on the work of LeSage and Pace (2009).

The estimated indirect effect is positive, but recalling that the effect of time to market on GDP is negative implies that the actual spillover exerts a negative effect.