The Development of Trade Blocs in an Era of Globalisation

Abstract

This study investigates the economic geography of international trade during the period 1950-2005. We introduce a new trade bloc variable that relies on the intramax hierarchical clustering technique to identify endogenous trade blocs with annual trade flows. Multivariate analysis with gravity-equation-based variables is used to explain how mechanisms of globalisation have affected trade patterns over the past half century. In particular, proximity and economic integration agreements are key to explaining the persistence of region-based trade blocs in a globalising world economy.

Having the cake and eating it too: the benefits of decoupling Australia’s trade governance in Europe after Brexit and beyond

“…A similar conclusion was made by Kohl and Brouwer's (2014) study into the economic geography of international trade over the second half of the 20 th century, in which they demonstrate that, even if approached from a condition of globalisation, proximity and economic integration agreements are determinants of the persistence of region-based trading blocs. However, centrality of regions has greater bearing on trade then that of investment.…”

Untitled

“…Primere uporabe metode Intramax najdemo na zelo različnih ravneh in področjih modeliranja in analize FR (Drobne, 2016): od analize trga dela (Masser in Scheurwater, 1980;Feldman et al, 2006;Meredith et al, 2007;Watts, 2009;Landré, 2012;Landré in Håkansson, 2013;Koo, 2012), analize stanovanjskega trga (Goetgeluk in de Jong, 2007;Brown in Hincks, 2008;Jaegal, 2013), analize trga blaga (Brown in Pitfield, 1990), analize svetovnih trgovinskih regij (Poon, 1997;Kohl in Brouver, 2014), analize (Mitchell, Bill in Watts, 2007;Mitchell in Stimson, 2010;Mitchell in Watts, 2010;Mitchell in sod., 2013), analize telekomunikacijskih regij (Fisher et al, 1993), analize upravnih in statističnih regij (Nel, Krygsman in de Jong, 2008;Drobne in Bogataj, 2012a, 2012b, analize prometnih regij (Krygsman, de Jong in Nel, 2009) pa do analize storitvenih regij (Drobne in Bogataj, 2014 in podobnega. Drobne (2016) in Statistični urad RS (SURS, 2019a) so mnenja, da je zamisel FR v Sloveniji na makro ravni izvedena v dvanajstih statističnih regijah, ki pa se zaradi izkazovanja podatkov v časovnih serijah zelo redko spreminjajo.…”

Intramax and other objective functions: The case of Slovenia

“…In its relative simplicity and its implementation in publicly available software 4 , however, one sees the reason that the Intramax method has been used so many times to analyse FRs -of so many different kinds of interactions at very different levels of consideration, for example: labour market area delineation (Masser and Scheurwater, 1980;Feldman et al, 2005;Watts, 2009;Landré, 2012;Landré and Håkansson, 2013;Koo, 2012); housing market area delineation (Goetgeluk and de Jong, 2007;Brown and Hincks, 2008;Jaegal, 2013); commodity market delineation (Brown and Pitfield, 1990); world trade block delineation (Poon, 1997;Kohl and Brouver, 2014); functional economic region delineation (Mitchell et al, 2007(Mitchell et al, , 2013Mitchell and Stimson, 2010;Mitchell and Watts, 2010); telecommunication analysis (Fischer et al, 1993); to identify possible administrative or statistical regions (Nel et al, 2008;Bogataj, 2012a, 2012b); transport regions (Krygsman et al, 2009); in the (allocation) analysis of services Bogataj, 2014, 2015), and so forth.…”

“…However, it should be considered when using a different objective function than the original one (Koo, 2012), in a combination with other constraints (Drobne and Lakner, 2015, 201 when analysing some other data (e.g. financial flows; Kohl and Brouver, 2014). When the contiguity con is used, two BDUs/FRs that give the maximal value of the analysed objective function are aggregated onl they are contiguous (  = 1).…”