Showing 1 - 10 of 1,957
Due to their well-known indeterminacies, factor models require identifying assumptions to guarantee unique parameter estimates. For Bayesian estimation, these identifying assumptions are usually implemented by imposing constraints on certain model parameters. This strategy, however, may result...
Persistent link: https://www.econbiz.de/10009632905
Due to their well-known indeterminacies, factor models require identifying assumptions to guarantee unique parameter estimates. For Bayesian estimation, these identifying assumptions are usually implemented by imposing constraints on certain model parameters. This strategy, however, may result...
Persistent link: https://www.econbiz.de/10009671882
Due to their well-known indeterminacies, factor models require identifying assumptions to guarantee unique parameter estimates. For Bayesian estimation, these identifying assumptions are usually implemented by imposing constraints on certain model parameters. This strategy, however, may result...
Persistent link: https://www.econbiz.de/10010338409
Quantile factor models (QFM) represent a new class of factor models for high-dimensional panel data. Unlike approximate factor models (AFM), which only extract mean factors, QFM also allow unobserved factors to shift other relevant parts of the distributions of observables. We propose a quantile...
Persistent link: https://www.econbiz.de/10012315850
Quantile factor models (QFM) represent a new class of factor models for high-dimensional panel data. Unlike approximate factor models (AFM), which only extract mean factors, QFM also allow unobserved factors to shift other relevant parts of the distributions of observables. We propose a quantile...
Persistent link: https://www.econbiz.de/10013314969
When specifying and estimating latent factor models, a common assumption made is one of factor pervasiveness, which requires that Γ'Γ/N converges to a positive definite matrix, as N → ∞, where Γ denotes the loading matrix of the factor model. This paper builds on the recent nascent...
Persistent link: https://www.econbiz.de/10014264564
This chapter presents a unified set of estimation methods for fitting a rich array of models describing dynamic relationships within a longitudinal data setting. The discussion surveys approaches for characterizing the micro dynamics of continuous dependent variables both over time and across...
Persistent link: https://www.econbiz.de/10014024953
This paper considers factor estimation from heterogenous data, where some of the variables are noisy and only weakly informative for the factors. To identify the irrelevant variables, we search for zero rows in the loadings matrix of the factor model. To sharply separate these irrelevant...
Persistent link: https://www.econbiz.de/10009674269
This paper considers factor estimation from heterogenous data, where some of the variables are noisy and only weakly informative for the factors. To identify the irrelevant variables, we search for zero rows in the loadings matrix of the factor model. To sharply separate these irrelevant...
Persistent link: https://www.econbiz.de/10012988804
We propose a new unified approach to identifying and estimating spatio-temporal dependence structures in large panels. The model accommodates global crosssectional dependence due to global dynamic factors as well as local cross-sectional dependence, which may arise from local network structures....
Persistent link: https://www.econbiz.de/10012421000