54th Congress of the European Regional Science Association: "Regional development & globalisation: Best practices", 26-29 August 2014, St. Petersburg, Russia
The relation between infrastructure and economic growth has been largely investigated in the literature, but the empirical evidence found has proven to be controversial. This paper aims to empirically analyze the impact of infrastructure stocks on economic growth. In spite of there being theoretical justification for taking infrastructure into account in studies on economic growth and equity, there is a difficulty in obtaining infrastructure data at a more disaggregated regional level. Frequently, the decisions on infrastructure investment are taken in the sphere of the federal government or of the state governments. Due to this, the data are usually available only at the state level. In view of this, there are two alternatives for doing an analysis of income convergence for Brazil. One alternative would be to do the income convergence analysis only at the state level. However, the sample size would be small (n=27), making it not reach the asymptotic properties of the estimators, among other limitations. The other alternative would be to perform the analysis of income convergence only at the municipal level. However, as much information on infrastructure is available at the state level, the researcher would take his chance of omitting variables of infrastructure relevant to analysis, creating bias and inconsistency to the estimator. In order to circumvent this problem, we propose a spatial multilevel model with two geographical levels, controlling for fixed effects and spatial dependence. The multilevel approach is justified when attempting to reconcile this hierarchical structure of necessary data in order to perform the analysis of conditional income convergence, including infrastructure as an important determinant. A model of conditional convergence is specified at the municipal level, whereas some first level coefficients are specified as being dependent on infrastructure stocks at the state level. The results revealed that road infrastructure stock is a relevant conditional variable in the convergence equation. More importantly, the control for fixed effects and spatial autocorrelation largely influences the estimated value of the beta. Based on our estimate of the beta, it is possible to point out the existence of an overestimation of this convergence parameter in the Brazilian literature on this research topic.
economic growth infrastructure spatial dependence multilevel spatial model