Artykuły udostępnione publicznie: - Jushan BaiWięcej informacji
Dostępne w jakimś miejscu: 21
Identification and Bayesian estimation of dynamic factor models
J Bai, P Wang
Journal of Business & Economic Statistics 33 (2), 221-240, 2015
Upoważnienia: Research Grants Council, Hong Kong
Panel data models with grouped factor structure under unknown group membership
T Ando, J Bai
Journal of Applied Econometrics 31 (1), 163-191, 2016
Upoważnienia: US National Science Foundation
Clustering huge number of financial time series: A panel data approach with high-dimensional predictors and factor structures
T Ando, J Bai
Journal of the American Statistical Association 112 (519), 1182-1198, 2017
Upoważnienia: US National Science Foundation
Maximum likelihood estimation and inference for approximate factor models of high dimension
J Bai, K Li
Review of Economics and Statistics 98 (2), 298-309, 2016
Upoważnienia: US National Science Foundation, National Natural Science Foundation of China
Econometric analysis of large factor models
J Bai, P Wang
Annual Review of Economics 8 (1), 53-80, 2016
Upoważnienia: US National Science Foundation, Research Grants Council, Hong Kong
Matrix completion, counterfactuals, and factor analysis of missing data
J Bai, S Ng
Journal of the American Statistical Association 116 (536), 1746-1763, 2021
Upoważnienia: US National Science Foundation
Estimation and inference of FAVAR models
J Bai, K Li, L Lu
Journal of Business & Economic Statistics 34 (4), 620-641, 2016
Upoważnienia: US National Science Foundation, National Natural Science Foundation of China
Approximate factor models with weaker loadings
J Bai, S Ng
Journal of Econometrics 235 (2), 1893-1916, 2023
Upoważnienia: US National Science Foundation
Quantile co-movement in financial markets: A panel quantile model with unobserved heterogeneity
T Ando, J Bai
Journal of the American Statistical Association 115 (529), 266-279, 2020
Upoważnienia: US National Science Foundation
Rank regularized estimation of approximate factor models
J Bai, S Ng
Journal of Econometrics 212 (1), 78-96, 2019
Upoważnienia: US National Science Foundation
Dynamic spatial panel data models with common shocks
J Bai, K Li
Journal of Econometrics 224 (1), 134-160, 2021
Upoważnienia: National Natural Science Foundation of China
Estimation and inference of change points in high-dimensional factor models
J Bai, X Han, Y Shi
Journal of Econometrics 219 (1), 66-100, 2020
Upoważnienia: US National Science Foundation
Testing panel cointegration with unobservable dynamic common factors that are correlated with the regressors
J Bai, JL Carrion‐i‐Silvestre
The Econometrics Journal 16 (2), 222-249, 2013
Upoważnienia: Government of Spain
Factor-based imputation of missing values and covariances in panel data of large dimensions
E Cahan, J Bai, S Ng
Journal of Econometrics 233 (1), 113-131, 2023
Upoważnienia: US National Science Foundation
Unbalanced panel data models with interactive effects
J Bai, Y Liao, J Yang
The Oxford Handbook of Panel Data, edited by Badi Baltagi, 149-170, 2015
Upoważnienia: National Natural Science Foundation of China
Quasi-maximum likelihood estimation of break point in high-dimensional factor models
J Duan, J Bai, X Han
Journal of Econometrics 233 (1), 209-236, 2023
Upoważnienia: National Natural Science Foundation of China, Research Grants Council, Hong Kong
Cross-sectional dependence in panel data models: A special issue
J Bai, B Baltagi, H Pesaran
JOURNAL OF APPLIED ECONOMETRICS 31, 1-3, 2016
Upoważnienia: UK Economic and Social Research Council
Bayesian and maximum likelihood analysis of large-scale panel choice models with unobserved heterogeneity
T Ando, J Bai, K Li
Journal of Econometrics 230 (1), 20-38, 2022
Upoważnienia: National Natural Science Foundation of China
The likelihood ratio test for structural changes in factor models
J Bai, J Duan, X Han
Journal of Econometrics 238 (2), 105631, 2024
Upoważnienia: National Natural Science Foundation of China
Selecting the regularization parameters in high-dimensional panel data models: Consistency and efficiency
T Ando, J Bai
Econometric Reviews 37 (3), 183-211, 2018
Upoważnienia: US National Science Foundation
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