
Discovering different patterns inside SubSaharan countries defining more homogeneous clusters to simulate specific trade policies
de Arce, Rafael; de Vicente, Saúl; Mahía, Ramón; Medina, Eva; David, Anda (2014), Discovering different patterns inside SubSaharan countries defining more homogeneous clusters to simulate specific trade policies. https://basepub.dauphine.fr/handle/123456789/17776
Type
Document de travail / Working paperDate
2014Series title
NOPOOR Working PaperSeries number
10Pages
39
Metadata
Show full item recordAuthor(s)
de Arce, Rafaelde Vicente, Saúl
Universidad Autonoma Metropolitana-I [UAM]
Mahía, Ramón
Medina, Eva
Universidad Autonoma Metropolitana-I [UAM]
David, Anda
Abstract (EN)
"Free trade areas (FTA) initiatives (and/or academic simulations) to stimulate economic growth in African Sub-Saharan countries (SSC) have demonstrated wide heterogeneous results depending on the economic structure of each country. The value added chain structure plays a crucial role determining the real effect of such type of measures as economic triggers (see Mohan et Al, 2013). Additionally, the lack of statistical information is certainly a problem when trying to analyse the effect of these policies for the majority of the SSC. With the aim of use Computable General Equilibrium Models (CGE) for this goal (as usual), Social Accounting Matrices (SAM) are required and, unfortunately, they are not often available but for a reduced amount of countries in this subcontinent. In order to partially solve this problem, we propose a comparison between the data recorded in these SAMs and another database containing socioeconomic information. Taking into account the availability of World Bank Development Indicators (WDI) for all of the SSC, the aim of this investigation is to create a bridge between the selected 8 countries with available SAM and the rest of the countries without these matrices, as a useful tool to conduct macroeconomic simulations of FTA (or other) and its effect on poverty for each SSC using a ‘kind of’ economic structure archetype associated to the most similar country or countries in the area. "Subjects / Keywords
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