id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
work_c4lxulprjva3tf3xvg4q34lx3i	Álvaro Herrero	Unsupervised neural models for country and political risk analysis	2011	53	.pdf	application/pdf	17429	1222	57	on neural projection models, which support data analysis in the context of country and political risk well distributed, both in large and in small countries, and with relatively low and high levels of political risk. MNEs in this group are found in small Latin American countries with higher levels of risk, namely El Salvador, This group includes several countries with very low security and tax policy risk levels, around average labour Group 2 includes countries with slightly below average risk levels in all the different aspects analysed. Finally, the last group also includes developing countries –for instance, Burundi, Congo, Togo and Tanzaniawith high scores in security, tax policy and market labour risks. As in the previous case, this group includes countries characterized by low levels of economic and institutional In general, countries are distributed into groups with similar levels of economic, political and institutional 	./cache/work_c4lxulprjva3tf3xvg4q34lx3i.pdf	./txt/work_c4lxulprjva3tf3xvg4q34lx3i.txt