getnfac: 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 found in Bai and Ng (2002)

Usage

getnfac(x,kmax,jj)

Arguments

A NxT matrix containing the data.

kmax

The maximum number of common factors used to compute the criterion function for the estimate of ic, the number of common factors. This methedology is weak to underestimation of the number of common factors. It is suggested that overestimation is prefer

an Integer 1 through 8. Choices 1 through 7 are respectively, IC(1), IC(2), IC(3), AIC(1), BIC(1), AIC(3), and BIC(3), respectively. Choosing 8 makes the number of factors equal to the number of columns whose sum of eigenvalues is less than or equal t

Value

ic The approximate number of factors based off of the chosen. penalty function lambda Estimated factor loadings associated with common factors. Fhat Estimated common component

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 large matrices. IC(1), IC(2), and IC(3) . AIC(1) will not work for all N and T. BIC(1) will not work for small N relative to T. AIC(3) and BIC(3) take into account the panel structure of the data. AIC(3) performs in consistently across configurations of the data while BIC(3) may not perform well for some configurations.

References

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