You are not currently logged in.
Access JSTOR through your library or other institution:
If You Use a Screen ReaderThis content is available through Read Online (Free) program, which relies on page scans. Since scans are not currently available to screen readers, please contact JSTOR User Support for access. We'll provide a PDF copy for your screen reader.
Recovering Information from Incomplete or Partial Multisectoral Economic Data
Amos Golan, George Judge and Sherman Robinson
The Review of Economics and Statistics
Vol. 76, No. 3 (Aug., 1994), pp. 541-549
Published by: The MIT Press
Stable URL: http://www.jstor.org/stable/2109978
Page Count: 9
Since scans are not currently available to screen readers, please contact JSTOR User Support for access. We'll provide a PDF copy for your screen reader.
Preview not available
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.
The Review of Economics and Statistics © 1994 The MIT Press