GLS Estimation of Dynamic Factor Models

By J. Breitung, J. Tenhofen. 2011

68 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/fbc7d42f73ce809663a152b45f39ba5210f54eab

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Economics and Econometrics

1. Jushan Bai
2. Kunpeng Li
3. Serena Ng
4. Jianqing Fan
5. Mark W. Watson
6. James H. Stock
7. Yuan Liao
8. Peng Wang

In Finance

1. Jushan Bai
2. Serena Ng
3. Mark W. Watson
4. James H. Stock
5. Yuan Liao
6. Jianqing Fan
7. Kunpeng Li
8. Peng Wang

Citations in the corpus

• Dynamic Factor Models, Factor-Augmented Vector Autoregressions, and Structural Vector Autoregressions in Macroeconomics (2016, background): “sized, and Monte Carlo evidence in Breitung and Tenhofen (2011) suggests that the size distortions could be large if the idiosyncratic disturbances are highly serially correlated.”
• Efficient Estimation of Approximate Factor Models (2012, background): “Additional literature on factor analysis includes, e.g., Bai and Ng (2002), Wang (2009), Dias, Pinherio and Rua (2008), Breitung and Tenhofen (2011), Han (2012), etc; most of these studies are based on the PCA method.”
• Identification and Estimation of Dynamic Factor Models (2012, background): “Thus we may draw δ according to (11) and construct the associated loading matrix Λ (δ).”
• Analyzing International Business and Financial Cycles using Multi-Level Factor Models: A Comparison of Alternative Approaches (2016, methodology): “Third, in models with heteroskedastic or autocorrelated errors, the sequential LS technique can be used to compute the implied ML estimator that is equivalent to minimizing the weighted sum of squared residuals (cf. Breitung and Tenhofen (2011)), which is equivalent to the (pseudo) ML estimator.”
• PROJECTED PRINCIPAL COMPONENT ANALYSIS IN FACTOR MODELS (2014, background): “See, for instance, Stock and Watson (2002), Bai (2003), Bai and Ng (2002), Breitung and Tenhofen (2011), Choi (2012), Lam and Yao (2012), among others., The factor model (1.1) has also been extensively studied in the statistics literature.”
• Maximum Likelihood Estimation and Inference for Approximate Factor Models of High Dimension (2016, methodology): “The principal component analysis of Bai (2003) and the two-step estimators of Breitung and Tenhofen (2011) and Choi (2012) do not investigate this rotational property.”
• STATISTICAL ANALYSIS OF FACTOR MODELS OF HIGH DIMENSION (2012, unknown): “[9] considers a two-step approach by treating both the factors and the factor loadings as the parameters of interest.”
• An Overview on the Estimation of Large Covariance and Precision Matrices (2015, unknown): “See, for instance, Stock and Watson (2002); Bai (2003); Bai and Ng (2002); Fan et al. (2008); Breitung and Tenhofen (2011); Onatski (2012); Lam and Yao (2012); Fan et al. (2013), among others.”
• Identification and Bayesian Estimation of Dynamic Factor Models (2015, methodology): “The generalized least-square estimator for nondynamic factor models was studied by Breitung and Tenhofen (2011) and Choi (2012).”