Bøger af Alberto Quadrio Curzio

This volume contains the proceedings of the international conference "e;Complexity and Industrial Clusters: Dynamics and Models in Theory and Practice"e;, organized by Fondazione Comunita e Innovazione and held in Milan on June 19 and 20, 2001 under the aegis of the Accademia Nazionale dei Lincei (founded in Rome in 1604), one of the oldest and most famous national academies of science in the world. Fondazione Comunita e Innovazione encourages research and the dissemination of knowledge about social, economic, cultural and civil issues. It promotes research and innovation related to local production systems and industrial districts, with special reference to: the interactions between large companies and SMEs (small and medium-size enterprises), the effects of industrial districts on the development and welfare of their communities and of neighbouring areas, the effects of globalisation on these local systems of productions. Fondazione Comunita e Innovazione was created in Milan in 1999. It supports studies, publications, and events, both on its own and in cooperation with corporations, research institutes, foundations, associations and universities. It also grants scientific sponsorship to research that is in line with its mission, as set forth in its by-laws. The founding member of the Fondazione is Edison (formerly Monted:son). The other subscribing members, in historical order, are: Ausimont, Tecnimont, Eridania, Accenture, and PricewaterhouseCoopers.

Sovereign Wealth Funds (SWFs) are state investment vehicles based on balance of payment surpluses. This book answers such key questions as: What defines a SWF? When and how did SWFs emerge? What investment strategies do SWFs pursue? What are the main financial, economic and political consequences of the operations of SWFs? And more.

Rent, resources, and technologies are crucial to understanding history and economics. Scarcity of resources, its interplay with technology, and the role of rent in explaining economic growth and income distribution are investigated by adopting a multi-sectoral and non-proportional model.