Abstract
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.
Original language | English |
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Pages (from-to) | 1107-1122 |
Number of pages | 16 |
Journal | Journal of Applied Econometrics |
Volume | 32 |
Issue number | 6 |
DOIs | |
Publication status | Published - 2017 |
Keywords
- LEE-CARTER MODEL
- PRINCIPAL COMPONENTS
- PANEL-DATA
- MORTALITY
- NUMBER