getnfac: Determining The Number of Factors In Approximate Factor Model

In Stevo15025/PANICr: PANIC Tests of Nonstationarity

Determining The Number of Factors In Approximate Factor Model

Description

This function approximates the number of factors in an approximate factor model for large N by T matrices using the methods and criteria found in Bai and Ng (2002)

Usage

getnfac(x,kmax,criteria)

Arguments

x	A matrix containing the data.
kmax	An integer with the maximum number of common factors to search over. This methodology is weak to underestimation of the number of common factors so setting this value higher is preferred.
criteria	a character vector of length one with values of either IC1, IC2, IC3, AIC1, BIC1, AIC3, BIC3, or eigen. Choosing eigen makes the number of factors equal to the number of columns whose sum of eigenvalues is less than or equal to .5.

Details

This function approximates the number of factors in an approximate factor model. Amongst the penalty functions BIC(3) has been found to be strict against cross-sectional dependence and is recommended for panels with greater than 18 series. IC(1) is most commonly used. BIC(1) is not recommended for small N relative to T. AIC(3) and BIC(3) take into account the panel structure of the data. AIC(3) performs consistently across configurations of the data while BIC(3) performs better on large N data sets.

Value

ic Integer of the approximate number of factors based off of the chosen penalty function

lambda A matrix of the estimated factor loadings associated with common factors.

Fhat A matrix of the estimated common components

References

Jushan Bai and Serena Ng. 'Determining the Number of Factors in Approximate Factor Models.' Econometrica 70.1 (2002): 191-221. Print.

Stevo15025/PANICr documentation built on Sept. 7, 2024, 4:30 p.m.