Recovering precision from seemingly redundant rounded data

Irwin L. Collier; Badi H. Baltagi

doi:10.1002/for.3980090505

Recovering precision from seemingly redundant rounded data

Research output: Contribution to journal › Article › peer-review

Abstract

Economic time series from the socialist economies of Eastern Europe and the Soviet Union are often not available. Instead, a matrix of rounded growth indexes for different base years is published. Using the constrained least squares and feasible GLS estimators developed in this paper, it is possible to predict the true matrix of growth indexes with greatly improved accuracy.

Original language	English (US)
Pages (from-to)	457-465
Number of pages	9
Journal	Journal of Forecasting
Volume	9
Issue number	5
DOIs	https://doi.org/10.1002/for.3980090505
State	Published - 1990
Externally published	Yes

Keywords

Constrained least squares
Generalized least squares
Index
Numbers
Rounding errors
Socialist economic data

ASJC Scopus subject areas

Computer Science Applications
Statistics, Probability and Uncertainty
Modeling and Simulation
Strategy and Management
Management Science and Operations Research

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10.1002/for.3980090505

Cite this

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title = "Recovering precision from seemingly redundant rounded data",

abstract = "Economic time series from the socialist economies of Eastern Europe and the Soviet Union are often not available. Instead, a matrix of rounded growth indexes for different base years is published. Using the constrained least squares and feasible GLS estimators developed in this paper, it is possible to predict the true matrix of growth indexes with greatly improved accuracy.",

keywords = "Constrained least squares, Generalized least squares, Index, Numbers, Rounding errors, Socialist economic data",

author = "Collier, {Irwin L.} and Baltagi, {Badi H.}",

year = "1990",

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AB - Economic time series from the socialist economies of Eastern Europe and the Soviet Union are often not available. Instead, a matrix of rounded growth indexes for different base years is published. Using the constrained least squares and feasible GLS estimators developed in this paper, it is possible to predict the true matrix of growth indexes with greatly improved accuracy.

KW - Constrained least squares

KW - Generalized least squares

KW - Index

KW - Numbers

KW - Rounding errors

KW - Socialist economic data

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Recovering precision from seemingly redundant rounded data

Abstract

Keywords

ASJC Scopus subject areas

Access to Document

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