Efficient estimation of factor models with time and cross-sectional dependence (replication data)

DOI

This paper studies the efficient estimation of large-dimensional factor models with both time and cross-sectional dependence assuming (N,T) separability of the covariance matrix. The asymptotic distribution of the estimator of the factor and factor-loading space under factor stationarity is derived and compared to that of the principal component (PC) estimator. The paper also considers the case when factors exhibit a unit root. We provide feasible estimators and show in a simulation study that they are more efficient than the PC estimator in finite samples. In application, the estimation procedure is employed to estimate the Lee-Carter model and life expectancy is forecast. The Dutch gender gap is explored and the relationship between life expectancy and the level of economic development is examined in a cross-country comparison.

Identifier
DOI https://doi.org/10.15456/jae.2022326.0705140873
Metadata Access https://www.da-ra.de/oaip/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai:oai.da-ra.de:775433
Provenance
Creator Heinemann, Alexander
Publisher ZBW - Leibniz Informationszentrum Wirtschaft
Publication Year 2017
Rights Creative Commons Attribution 4.0 (CC-BY); Download
OpenAccess true
Contact ZBW - Leibniz Informationszentrum Wirtschaft
Representation
Language English
Resource Type Collection
Discipline Economics