Balance, Manhattan norm and Euclidean distance of industrial policies for the US
Abstract The design of policy controls oriented to stimulate specific industrial activities highlights a set of problems that involve the choice of the macro variables that make up the policy control, the determination of their aggregate amount as well as their sectoral composition and their inner balance. In a multi-sectoral framework these issues require a careful identification of the relationship between the scale (aggregate value) and structure (inner composition) of both the policy control and policy target. The Macro Multiplier approach identifies the complete set of aggregate scalars that are hidden within the complexity of the multi industry relations and how they are strictly linked with predetermined structures both of the policy control and of the policy target. The application exercise is performed on an Input-Output table for the US for the year 2007, the applied exercise focuses on the government strategies for the "Manufacture of Motor vehicles" sector.
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- Maurizio Ciaschini & Rosita Pretaroli & Claudio Socci, 2009.
"A Convenient Multisectoral Policy Control For Ict In The Us Economy,"
Wiley Blackwell, vol. 60(4), pages 660-685, November.
- Maurizio Ciaschini & Rosita Pretaroli & Claudio Socci, 2007. "A convenient multi sectoral policy control for ICT in the USA economy," Working Papers 11-2007, Macerata University, Department of Studies on Economic Development (DiSSE), revised Mar 2009.
- Shiro Takeda, 2010. "A computable general equilibrium analysis of the welfare effects of trade liberalization under different market structures," International Review of Applied Economics, Taylor & Francis Journals, vol. 24(1), pages 75-93.
- repec:ebl:ecbull:v:28:y:2004:i:18:p:a0 is not listed on IDEAS
- Ciaschini, Maurizio & Socci, Claudio, 2007. "Final demand impact on output: A macro multiplier approach," Journal of Policy Modeling, Elsevier, vol. 29(1), pages 115-132. Full references (including those not matched with items on IDEAS)
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