RECOVERING INFORMATION FROM INCOMPLETE OR PARTIAL MULTISECTORAL ECONOMIC DATA
成果类型：
Article
署名作者：
GOLAN, A; JUDGE, G; ROBINSON, S
署名单位：
University of California System; University of California Berkeley
刊物名称：
REVIEW OF ECONOMICS AND STATISTICS
ISSN/ISSBN：
0034-6535
DOI：
10.2307/2109978
发表日期：
1994-08
页码：
541-549
关键词：
摘要：
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.
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