Does Spatial Heterogeneity Matter in the EU Regions’ Convergence Income Process?

Abstract

This paper explores the role spatial heterogeneity in the EU regions' convergence income process. For this purpose we tested income convergence hypothesis of the 245 NUTS 2 European Union regions during the period 2003-2014. We used spatial econometric approach which allowed an explicit modelling of both spatial effects: spatial heterogeneity and spatial autocorrelation. Our results showed an appropriate consideration of the role of spatial effects. First, we found that the rate of economic growth in the region is not only affected by the exogenous characteristics of the region, but also potentially by the rate of economic growth in neighbouring regions. Secondly, estimated spatial regime model identified two spatial regimes-convergence clubs. The regions under the first spatial convergence regime included economically "weaker" regions (mainly regions of post-socialist countries, regions of Portugal, Spain, Greece and southern regions of Italy) and these regions are converging separately from the rest of regions of the EU.

Multiscale downside risk interdependence between the major agricultural commodities

“…We investigate extreme downside risk interdependence in a multifrequency framework because various market participants have different objectives and preferences. In that process, we use wavelet methodology, which is a nonlinear and energy preserving transformation method that projects original time‐series onto a sequence of basic functions (see e.g., Ahroum & Achchab, 2019; Bhuiyan et al, 2019; Kučerová & Poměnková, 2015). These functions are called wavelets and they can reflect different time‐horizons, without losing valuable empirical information.…”

Spatial Heterogeneity and Spillovers of Employment in the EU Regions

“…The spatial aspects have been already incorporated, e.g., in many studies dealing with regional income convergence (Qin et al, 2017;Chocholatá and Furková, 2017;Lolayekar and Mukhopadhyay, 2019) at which it is assumed that spatial spillover effects will have a significant impact on income convergence of regions. Also, we can find several studies that handle issue of spatial heterogeneity and their results indicate that economic behaviour is unstable in space, and income convergence is characterized by multiple local equilibrium states -convergence clubs (Qin et al, 2017;Papalia and Betarelli, 2012;Pan et al, 2015;Furková, 2020).…”

Impact of Covid‐19 on the convergence of GDP per capita in OECD countries

“…Agglomeration processes are more associated with the New Economic Geography, where Paul Krugman, among other authors, played a determinant role (Fujita et al, 2001). In these processes, increasing returns to scale for the manufacturing sector and constant returns for the agricultural sector are also expected.…”

“…Considering the diversity of realities within the European Union integration process (Furkova, 2020), the respective convergence/divergence trends have attracted the attention of several researchers (Olejnik, 2008), to assess the impacts on new member‐states (Smetkowski, 2015). However, there are other contexts that have deserved the consideration of academics who have carried out studies related to spatial dynamics, such as those from the following countries: Russia (Balash et al, 2020), Belarus (Celbis et al, 2018), Mexico (German‐Soto & Brock, 2015), Romania (Goschin, 2017), China (He et al, 2017), Great Britain (Henley, 2005), Tunisia (Labidi, 2019), the Iberian Peninsula (Martinho et al, 2020), the United States (Rey & Montouri, 1999), Colombia (Royuela & Adolfo Garcia, 2015) and Brazil (Silveira‐Neto & Azzoni, 2006).…”