@techreport{Pesaran2004Estimation,
abstract = {This paper presents a new approach to estimation and inference in panel data models with a
multifactor error structure where the unobserved common factors are (possibly) correlated
with exogenously given individual-specific regressors, and the factor loadings differ over the
cross section units. The basic idea behind the proposed estimation procedure is to filter the
individual-specific regressors by means of (weighted) cross-section aggregates such that
asymptotically as the cross-section dimension (N) tends to infinity the differential effects of
unobserved common factors are eliminated. The estimation procedure has the advantage that
it can be computed by OLS applied to an auxiliary regression where the observed regressors
are augmented by (weighted) cross sectional averages of the dependent variable and the
individual specific regressors. Two different but related problems are addressed: one that
concerns the coefficients of the individual-specific regressors, and the other that focusses on
the mean of the individual coefficients assumed random. In both cases appropriate estimators,
referred to as common correlated effects (CCE) estimators, are proposed and their asymptotic
distribution as N tends to infinity, with T (the time-series dimension) fixed or as N and T tends to infinity (jointly)
are derived under different regularity conditions. One important feature of the proposed CCE
mean group (CCEMG) estimator is its invariance to the (unknown but fixed) number of
unobserved common factors as N and T tends to infinity (jointly). The small sample properties of the
various pooled estimators are investigated by Monte Carlo experiments that confirm the
theoretical derivations and show that the pooled estimators have generally satisfactory small
sample properties even for relatively small values of N and T.},
author = {Mohammad Hashem Pesaran},
copyright = {http://www.econstor.eu/dspace/Nutzungsbedingungen},
keywords = {C33; C12; C13; 330; cross section dependence; large panels; common correlated effects; heterogeneity; estimation and inference; Sch\"{a}tztheorie; Inferenzstatistik; Panel; Theorie},
language = {eng},
number = {1331},
title = {Estimation and inference in large heterogeneous panels with a multifactor error structure},
type = {CESifo working papers},
url = {http://hdl.handle.net/10419/18696},
year = {2004}
}