Difference between revisions of "Partitioned Matrix"

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== Definition ==
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A '''Partitioned Matrix''' (or Block Matrix) is the general mathematical structure used prominently in the context of [[Multiregional Input-Output Model]]. It divides n industries in the  [[Input-Output Model]] into subgroups.
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== Usage ==
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A partioned matrix may group specific sectors within an economy or represent a sector-country decomposition in a [[Multiregional Input-Output Model]]. An MRIO model extends the standard IO matrix to a larger system where each industry in each country has a separate row and column.<ref>R.E. Miller and P.D. Blair, Input-Output Analysis: Foundations and Extensions, Second Edition, Cambridge University Press, 2009</ref>
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If a matrix is partitioned into four blocks, it can be inverted blockwise (Using the concet of the [[wikipedia:Schur complement | Schur Complement]]).
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== See Also ==
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* [[Aggregation Matrix]]
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== Further Resources ==
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* [https://www.openriskacademy.com/course/view.php?id=70 Crash Course on Input-Output Model Mathematics]
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* [https://www.openriskacademy.com/course/view.php?id=64 Introduction to Input-Output Models using Python]
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== References ==
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* [[wikipedia:Block matrix | Block Matrix @ Wikipedia]]
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<references/>
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[[Category:EEIO]]
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{{#set:Has Formula = HAS_FORMULA}}
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Latest revision as of 18:33, 16 November 2023

Definition

A Partitioned Matrix (or Block Matrix) is the general mathematical structure used prominently in the context of Multiregional Input-Output Model. It divides n industries in the Input-Output Model into subgroups.

Usage

A partioned matrix may group specific sectors within an economy or represent a sector-country decomposition in a Multiregional Input-Output Model. An MRIO model extends the standard IO matrix to a larger system where each industry in each country has a separate row and column.[1]

If a matrix is partitioned into four blocks, it can be inverted blockwise (Using the concet of the Schur Complement).

See Also

Further Resources

References

  1. R.E. Miller and P.D. Blair, Input-Output Analysis: Foundations and Extensions, Second Edition, Cambridge University Press, 2009