PCA2: Stata module to apply Principal Component Analisys (PCA) to standard and GMM-style instrumental variables

Maria Bontempi and Irene Mammi

Statistical Software Components from Boston College Department of Economics

Abstract: pca2 applies the Principal Component Analysis (PCA) to a set of different variables, or to a set of GMM-style lags of the same variable, or to a set of lags of different variables. PCA is aimed at data reduction and consists of an eigenvalue-eigenvector decomposition of the correlation or covariance matrix of the variables in order to obtain a set of orthogonal linear combinations of the original variables that account for most of the variability in the original data.

Language: Stata
Requires: Stata version 9
Keywords: principal components; GMM-style lags; instrumental variables (search for similar items in EconPapers)
Date: 2015-11-15
Note: This module should be installed from within Stata by typing "ssc install pca2". The module is made available under terms of the GPL v3 (https://www.gnu.org/licenses/gpl-3.0.txt). Windows users should not attempt to download these files with a web browser.
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http://fmwww.bc.edu/repec/bocode/p/pca2.ado program code (text/plain)
http://fmwww.bc.edu/repec/bocode/p/pca2.hlp help file (text/plain)
http://fmwww.bc.edu/repec/bocode/p/pca2_table1.do sample do-file (text/plain)
http://fmwww.bc.edu/repec/bocode/p/pca2_table1.dta sample data file (application/x-stata)

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