دانشیار دانشکدة اقتصاد دانشگاه تهران
عنوان مقاله [English]
The empirical literature about economic growth has extensively shown that a country’s economic growth is indeed affected by the performance of its neighbors and influenced by its geographical position. This paper is to consider the "convergence theory" and the geographical dimension of a set of data in the estimation of the convergence and uses "spatial econometrics to estimate a growth model" that includes cross-country interdependence. Based on the OIC state members and its available 38 observations over two decades (1980?2000), it is shown that the unconditional ?-convergence model prevails the spillover effects among the OIC countries which are very important for growth. Since, the estimation by ordinary least squares leads to inefficient estimators and invalid statistical inferences, the maximum likelihood method is used to correct the spatially autocorrelated errors. Using spatial econometric methods and a distance based weight matrix, it is estimated that an alternative specification, which can take into account the spatial autocorrelation leading to highlight a geographic spillover effect: the mean growth rate of a region does not have positive and statistically valid influences by those of neighboring regions. It is found that spatial relationships across countries are not quite relevant and the convergence theory can not help the OIC state members. So, other international policies such as establishing a common market as a core or as a growth pole is needed to work with the peripheral and semi peripheral countries in the region.
JEL Classification: R58, R11