agg.sector takes specified sectors and creates a "new" joint sector. This produces a new
InputOutput object. Note the Leontief Inverse and Ghoshian Inverse are elements. There is deliberately no warning if the sector does not occur in all regions. See
Caution: Inverting large matrices will take a long time. R does a computation roughly every 8e-10 second. The number of computations per matrix inversion is n^3 where n is the dimension of the square matrix. For n = 5000 it should take 100 seconds.
agg.sector(io, sectors, newname = "newname")
Character. Specific sectors to be aggregated. Can either be a character that exactly matches the name of the sector in
Character. The name to give to the new aggregated sector.
Creates the aggregation matrix to pre (and/or post when appropriate) to aggregate the matrices in the
InputOutput object. Say you have 1 region with n sectors and you wish to aggregate sectors i and i+1. A diagonal matrix is converted into a n-1xn matrix where rows i and i+1 are additively combined together. This matrix is then used to create new aggregated tables. The "new" sector is then stored in location i. See Blair and Miller 2009 for more details.
InputOutput object is created. See
John J. P. Wade, Ignacio Sarmiento-Barbieri
Blair, P.D. and Miller, R.E. (2009). "Input-Output Analysis: Foundations and Extensions". Cambridge University Press
Nazara, Suahasil & Guo, Dong & Hewings, Geoffrey J.D., & Dridi, Chokri, 2003. "PyIO. Input-Output Analysis with Python". REAL Discussion Paper 03-t-23. University of Illinois at Urbana-Champaign. (http://www.real.illinois.edu/d-paper/03/03-t-23.pdf)
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