estimate_factor: Estimates common factor(s) F.

Description

The estimator for F, see Anderson (1984), is equal to the first k eigenvectors (multiplied by sqrt(T) due to the restriction F'F/T = I) associated with first r largest eigenvalues of the matrix WW' (which is of size TxT).

Usage

estimate_factor(
  Y,
  X,
  beta_est,
  g,
  lgfg_list,
  k,
  kg,
  robust,
  method_estimate_beta,
  method_estimate_factors,
  initialise = FALSE,
  verbose = FALSE
)

Value

Return a list. The first element contains the k x T matrix with the k estimated common factors. The second element contains either the robust MacroPCA-based loadings or NA.

Arguments

Y: Y: NxT dataframe with the panel data of interest
X: X: NxTxp array containing the observable variables
beta_est: estimated values of beta
g: Vector with group membership for all individuals
lgfg_list: This is a list (length number of groups) containing FgLg for every group.
k: number of common factors to be estimated
kg: number of group specific factors to be estimated
robust: TRUE or FALSE: defines using the classical or robust algorithm to estimate beta
method_estimate_beta: defines how beta is estimated. Default case is an estimated beta for each individual. Default value is "individual." Possible values are "homogeneous", "group" or "individual".
method_estimate_factors: defines method of robust estimaton of the factors: "macro", "pertmm" or "cz"
initialise: indicator of being in the initialisation phase
verbose: when TRUE, it prints messages