A two-step estimator for large approximate dynamic factor models based on Kalman filtering
From MaRDI portal
Publication:58366
DOI10.1016/j.jeconom.2011.02.012zbMath1441.62671OpenAlexW2110515654MaRDI QIDQ58366
Lucrezia Reichlin, Domenico Giannone, Catherine Doz, Catherine Doz, Domenico Giannone, Lucrezia Reichlin
Publication date: September 2011
Published in: Journal of Econometrics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.jeconom.2011.02.012
Applications of statistics to economics (62P20) Factor analysis and principal components; correspondence analysis (62H25)
Related Items (48)
Learning Latent Factors From Diversified Projections and Its Applications to Over-Estimated and Weak Factors ⋮ Structural analysis with multivariate autoregressive index models ⋮ Two sample tests for high-dimensional autocovariances ⋮ Analytical approximation to the multidimensional Fokker–Planck equation with steady state ⋮ Taking DSGE models to the policy environment by Alvarez-Lois, Harrison, Piscitelli and Scott ⋮ Changes in the effects of monetary policy on disaggregate price dynamics ⋮ Robust High-Dimensional Volatility Matrix Estimation for High-Frequency Factor Model ⋮ Diffusion Index Model Specification and Estimation Using Mixed Frequency Datasets ⋮ A dynamic factor model with stylized facts to forecast volatility for an optimal portfolio ⋮ Inferences in panel data with interactive effects using large covariance matrices ⋮ Efficient estimation of heterogeneous coefficients in panel data models with common shocks ⋮ Global vs sectoral factors and the impact of the financialization in commodity price changes ⋮ Using principal component analysis to estimate a high dimensional factor model with high-frequency data ⋮ A fragmented-periodogram approach for clustering big data time series ⋮ Chinese Divisia monetary index and GDP nowcasting ⋮ On the penalized maximum likelihood estimation of high-dimensional approximate factor model ⋮ Ignoring cross-correlated idiosyncratic components when extracting factors in dynamic factor models ⋮ Hidden factor estimation in dynamic generalized factor analysis models ⋮ Consistent estimation of high-dimensional factor models when the factor number is over-estimated ⋮ Efficient estimation of approximate factor models via penalized maximum likelihood ⋮ Large dimensional latent factor modeling with missing observations and applications to causal inference ⋮ When are Google Data Useful to Nowcast GDP? An Approach via Preselection and Shrinkage ⋮ Factor Models for High-Dimensional Tensor Time Series ⋮ Periodic dynamic factor models: estimation approaches and applications ⋮ Statistical analysis of factor models of high dimension ⋮ Factor models in high-dimensional time series: A time-domain approach ⋮ Knowing factors or factor loadings, or neither? Evaluating estimators of large covariance matrices with noisy and asynchronous data ⋮ Consistent estimation of time-varying loadings in high-dimensional factor models ⋮ Dynamic factor analysis for short panels: estimating performance trajectories for water utilities ⋮ A two-step estimator for large approximate dynamic factor models based on Kalman filtering ⋮ Asymptotics of the principal components estimator of large factor models with weakly influential factors ⋮ Large Covariance Estimation by Thresholding Principal Orthogonal Complements ⋮ Maximum likelihood estimation for dynamic factor models with missing data ⋮ On factor models with random missing: EM estimation, inference, and cross validation ⋮ Long-term forecasting of El Niño events via dynamic factor simulations ⋮ Monetary, fiscal and oil shocks: evidence based on mixed frequency structural FAVARs ⋮ Weighted maximum likelihood for dynamic factor analysis and forecasting with mixed frequency data ⋮ Are disaggregate data useful for factor analysis in forecasting French GDP? ⋮ GDP nowcasting with ragged-edge data: a semi-parametric modeling ⋮ Forecasting key macroeconomic variables from a large number of predictors: a state space approach ⋮ Real-time nowcasting of nominal GDP with structural breaks ⋮ Threshold factor models for high-dimensional time series ⋮ Estimating change-point latent factor models for high-dimensional time series ⋮ MULTIVARIATE AR SYSTEMS AND MIXED FREQUENCY DATA: G-IDENTIFIABILITY AND ESTIMATION ⋮ dfms ⋮ Dynamic principal component analysis with missing values ⋮ Constructing Common Factors from Continuous and Categorical Data ⋮ Factor Extraction in Dynamic Factor Models: Kalman Filter Versus Principal Components
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- A two-step estimator for large approximate dynamic factor models based on Kalman filtering
- Are more data always better for factor analysis?
- Time series: theory and methods.
- The generalized dynamic factor model consistency and rates
- Are disaggregate data useful for factor analysis in forecasting French GDP?
- Maximum Likelihood "Confirmatory" Factor Analysis of Economic Time Series
- Forecasting Using Principal Components From a Large Number of Predictors
- OPENING THE BLACK BOX: STRUCTURAL FACTOR MODELS WITH LARGE CROSS SECTIONS
- Inferential Theory for Factor Models of Large Dimensions
- Determining the Number of Factors in Approximate Factor Models
- The Generalized Dynamic Factor Model
- Maximum Likelihood Estimation of Misspecified Models
This page was built for publication: A two-step estimator for large approximate dynamic factor models based on Kalman filtering