inverse.important {ioanalysis} | R Documentation |
Inverse.Important Coefficients
Description
Calculates the inverse-important coefficients as in Blair and Miller (2009)
Usage
inverse.important(io, i, j, delta.aij)
Arguments
io |
An |
i |
Integer. The row component of the change in the matrix of technical input coefficients |
j |
Integer. The column component of the change in the matrix of technical input coefficients |
delta.aij |
Integer. By how much aij should change by |
Details
The inverse-important coefficients is the change in the Leontief matrix due to a specified change in one element of the matrix of technical input coefficients (A). This uses the formula:
\Delta L = \frac{\Delta a_{ij}}{1-l_{ji}\Delta a_{ij}} F_1(i,j)
where F_1(X,Y) is the first order field of influence.
Value
Returns the change in the Leontief matrix due the change in one element of the matrix of technical input coefficients. To find the new Leontief inverse induced by this change, use io$L + inverse.important().
Author(s)
John J. P. Wade, Ignacio Sarmiento-Barbieri
References
Blair, P.D. and Miller, R.E. (2009). "Input-Output Analysis: Foundations and Extensions". Cambridge University Press
Examples
data(toy.IO)
class(toy.IO)
i <- 3
j <- 4
delta.aij <- 0.5
II <- inverse.important(toy.IO, i, j, delta.aij)