Estatística multivariada aplicada ao estudo de variáveis macroeconômicas

Authors

  • Maria Emilia Camargo Departamento de Estatística, Centro de Ciências Naturais e Exatas - CCNE Universidade Federal de Santa Maria - UFSM, Santa Maria, RS.
  • Adriano Mendonça Souza Departamento de Estatística, Centro de Ciências Naturais e Exatas - CCNE Universidade Federal de Santa Maria - UFSM, Santa Maria, RS.

DOI:

https://doi.org/10.5902/2179460X26506

Abstract

The objective of this research is to explain the methodology of principal components in a structured way, by showing its applicability of reducing the dimensionality of the number of variables without losing the originality of the set. An analysis was made of the economic variables which represent Monetary and Price Policies, Economical Activities, Investment Variables and the current account of the Balance of Payments, from January 1985 to December 1991. A forecast was made for the period from January to December of 1992, using the adjusted models obtained from Principal Components and Box-Jenkins methodologies.

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References

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BOX, G. E.; JENKINS, G. M. (1976). Time séries analysis, forecasting and control. San Francisco. Holden Day.

MARDIA, K. W., KENT, 1. T.; BIBBY, 1. M. (1979). Multivariate analysis. Academic, Londres, p. 521.

MORRISON, D. F. (1976). Multivariate statistical methods. McGraw, New York, 2a. ed. 515 pag. 1976.

PINTO, L. A. M. S. (1981). Componentes Principais: Um teste para a efriciência de previsão a curto prazo. Dissertação de Mestrado. Departamento de Engenharia Industrial da PUCIRJ. Rio de Janeiro.

Published

1995-12-11

How to Cite

Camargo, M. E., & Souza, A. M. (1995). Estatística multivariada aplicada ao estudo de variáveis macroeconômicas. Ciência E Natura, 17(17), 33–42. https://doi.org/10.5902/2179460X26506

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