CRAN/E | BTtest

BTtest

Estimate the Number of Factors in Large Nonstationary Datasets

Installation

About

Large panel data sets are often subject to common trends. However, it can be difficult to determine the exact number of these common factors and analyse their properties. The package implements the Barigozzi and Trapani (2022) doi:10.1080/07350015.2021.1901719 test, which not only provides an efficient way of estimating the number of common factors in large nonstationary panel data sets, but also gives further insights on factor classes. The routine identifies the existence of (i) a factor subject to a linear trend, (ii) the number of zero-mean I(1) and (iii) zero-mean I(0) factors. Furthermore, the package includes the Integrated Panel Criteria by Bai (2004) doi:10.1016/j.jeconom.2003.10.022 that provide a complementary measure for the number of factors.

github.com/Paul-Haimerl/BTtest
Bug report File report

Key Metrics

Version 0.10.1
Published 2024-01-11 97 days ago
Needs compilation? yes
License MIT
License File
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Maintainer

Maintainer

Paul Haimerl

paul.haimerl@maastrichtuniversity.nl

Authors

Paul Haimerl

aut / cre

Material

README
NEWS
Reference manual
Package source

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

BTtest archive

Imports

Rcpp

LinkingTo

Rcpp
RcppArmadillo