Cluster and Discriminant Analysis on Time-Series as a Research Tool

Galbraith, James K.; Lu, Jack

doi:10.2139/ssrn.228678

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Cluster and Discriminant Analysis on Time-Series as a Research Tool

INEQUALITY AND INDUSTRIAL CHANGE: A GLOBAL VIEW, Chapter 16, James K. Galbraith and Maureen Berner, eds., Cambridge University Press, 2001

16 Pages Posted: 12 Jun 2000 Last revised: 25 Apr 2011

See all articles by James K. Galbraith

James K. Galbraith

University of Texas at Austin - Lyndon B. Johnson School of Public Affairs; Levy Economics Institute of Bard College

Jack Lu

Intellectual Property Market Advisory Partners(IPMAP), LLC

Date Written: January 1, 1999

Abstract

This paper presents a procedure for studying industrial performance and related issues such as changes in the wage structure. This procedure combines cluster analysis and discriminant analysis as a package, and applies this package to time series data. This enables us to organize industrial data into groups with similar wage or performance histories and then to extract summary time-series showing the main pattern of variation in performance between groups.

Keywords: cluster, discriminant, time-series

JEL Classification: C1, C4, C63, E32, J31, L13, L16, O38

Suggested Citation: Suggested Citation

Galbraith, James K. and Lu, Jack, Cluster and Discriminant Analysis on Time-Series as a Research Tool (January 1, 1999). INEQUALITY AND INDUSTRIAL CHANGE: A GLOBAL VIEW, Chapter 16, James K. Galbraith and Maureen Berner, eds., Cambridge University Press, 2001, Available at SSRN: https://ssrn.com/abstract=228678 or http://dx.doi.org/10.2139/ssrn.228678