Is there regional convergence between Morocco and its OECD partner countries in terms of well-being?

Morocco wants its 12 regions to play the role as the main lever of its public policies to initiate harmonized spatial multidimensional development. In the context of this goal and Morocco’s openness over the past two decades to bilateral and multilateral cooperation in an effort toward regional integration, this article studies the convergence of 389 regions in 36 countries(Morocco and 35 of its partner member countries in the Organization for Economic Co-operation and Development(OECD)) between 2000 and 2019 in terms of well-being. To this end, we considered the territorial dimension of β-convergence models for well-being and its four domains(economic, social, environmental, and governance). Then, we adapted the absolute β-convergence model by taking into account the existence of spatial heterogeneity according to five specifications of spatial models. Thus, apart from environmental domain, we found that β-convergence of regions is significant for well-being and three of its domains(economic, social, and governance). These convergences are made by a spatially autocorrelated error model(SEM). However, the speed and period of convergence are relatively low for social domain, partly explaining the very exacerbated tensions at the territorial level. The fastest convergence was achieved in governance domain, followed by economic domain. This suggests that emerging countries must pay particular attention to national public action in favor of social cohesion at the territorial level. The lack of convergence in environmental domain calls for common actions for all countries at the supranational level to protect the commons at the territorial level.

SPATIAL-TEMPORAL DYNAMICS OF REGIONAL CONVERGENCE AT COUNTY LEVEL IN JIANGSU

The dynamics of regional convergence include spatial and temporal dimensions. Spatial Markov chain can be used to explore how regions evolve by considering both individual regions and their geographic neighbors. Based on per capita GDP data set of 77 counties from 1978 to 2000, this paper attempts to investigate the spatial-temporal dynamics of regional convergence in Jiangsu. First, traditional Markov matrix for five per capita GDP classes is constructed for later comparison. Moreover, each region’s spatial lag is derived by averaging all its neighbors’ per capita GDP data. Conditioning on per capita GDP class of its spatial lag at the beginning of each year, spatial Markov transition probabilities of each region are calculated accordingly. Quantitatively, for a poor region, the probability of moving upward is 3.3% if it is surrounded by its poor neighbors, and even increases to 18.4% if it is surrounded by its rich neighbors, but it goes down to 6.2% on average if ignoring regional context. For a rich region, the probability of moving down ward is 1.2% if it is surrounded by its rich neighbors, but increases to 3.0% if it is surrounded by its poor neighbors, and averages 1.5% irrespective of regional context. Spatial analysis of regional GDP class transitions indicates those 10 upward moves of both regions and their neighbors are unexceptionally located in the southern Jiangsu, while downward moves of regions or their neighbors are almost in the northern Jiangsu. These empirical results provide a spatial explanation to the "convergence clubs" detected by traditional Markov chain.

The Evolution and Differentiation of Economic Convergence of Resource-based Cities in Northeast China

A key target of the overall strategy implementation for regional development since the 18th Party Congress of China has involved taking measures to narrow regional disparities. This is because resource-based cities' economic development has fallen below general levels due to resource exhaustion and an unbalanced industrial structure, among other factors. Further, an economic gap has long existed between Northeast China's large number of resource-based cities and non-resource-based cities. This article comprehensively studies the economic convergence of Northeast China's resource-based cities and non-resource-based cities from 1996 to 2015 by using a dynamic panel to analyze not only the economic development of different industries and types of cities, but also the main factors that influence economic development. The empirical results demonstrate that economic convergence exists in both resource-based and non-resource-based cities, but the economic gap between them has clearly narrowed since the implementation of a strategy to revitalize the Northeast's old industrial base. Shrinking cities are the fastest to converge, as mature cities are slower and regenerating cities are the slowest; regarding industry structure, the secondary industry dominates the economy in mature and shrinking cities, and the tertiary industry in regenerating cities. The primary stimulus in resource-based cities' economic development involves upgrading the industrial structure and investing in human capital. As China faces a ‘new normal' economy, resource-based cities in Northeast China should restructure the economy and perfect their market system to avoid again widening the economic gap.