% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/est_ife.R
\name{ife_estimator}
\alias{ife_estimator}
\title{Interactive Fixed Effects (IFE) Estimator}
\description{
Implements the iterative principal-components estimator of Bai (2009)
for panel data with interactive fixed effects:
\deqn{y_{it} = \alpha_i + \beta' x_{it} + \lambda_i' f_t + u_{it},}
where \eqn{f_t} is an \eqn{r}-vector of unobserved common factors and
\eqn{\lambda_i} is unit \eqn{i}'s vector of factor loadings. Unlike CCE
(which proxies \eqn{f_t} via cross-sectional averages), IFE estimates
\eqn{f_t} and \eqn{\lambda_i} directly via principal components on the
residual matrix.
}
\details{
The algorithm iterates between:
\enumerate{
\item Given \eqn{(\hat\beta, \hat\alpha_i)}, compute residuals
\eqn{\hat e_{it}} and extract the first \eqn{r} principal components
as \eqn{\hat f_t}, with loadings \eqn{\hat\lambda_i}.
\item Given \eqn{(\hat f_t, \hat\lambda_i)}, re-estimate
\eqn{\hat\beta} and \eqn{\hat\alpha_i} by pooled OLS on the
defactored data.
}
until convergence. The number of factors \eqn{r} can be specified or
selected by information criteria (BIC3 of Bai & Ng 2002).

\strong{Important:} IFE estimates a \strong{common} (pooled) \eqn{\beta}, not
heterogeneous unit-specific slopes. If you need heterogeneous slopes,
use CCE/DCCE instead.
}
\keyword{internal}
