Recovering Information from Incomplete or Partial Multisectoral Economic Data.
The problem of recovering the entries of a large matrix of expenditure, trade, or income flows from limited-incomplete multisectoral economic data is considered. Making use of some consistency and adding up restrictions, the problem is cast as a pure inverse problem and specified within a nonlinear optimization framework. Estimates of the unknown entries are provided along with an overall measure of uncertainty for the complete matrix and a measure of uncertainty for the individual elements. Artificial and real data are used to illustrate how the procedures may be applied and interpreted and to gauge performance under entropy and squared error measures. Copyright 1994 by MIT Press.
Year of publication: |
1994
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Authors: | Golan, Amos ; Judge, George ; Robinson, Sherman |
Published in: |
The Review of Economics and Statistics. - MIT Press. - Vol. 76.1994, 3, p. 541-49
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Publisher: |
MIT Press |
Saved in:
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