Journal ArticleDOI
Principal components estimation and identification of static factors
Jushan Bai,Serena Ng +1 more
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TLDR
In this article, conditions under which the latent factors can be estimated asymptotically without rotation were studied and the limiting distributions for the estimated factors and factor loadings when N and T are large and how identification of the factors affects inference based on factor augmented regressions.About:
This article is published in Journal of Econometrics.The article was published on 2013-09-01. It has received 279 citations till now. The article focuses on the topics: Factor analysis & Principal component analysis.read more
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Book ChapterDOI
Dynamic Factor Models, Factor-Augmented Vector Autoregressions, and Structural Vector Autoregressions in Macroeconomics
TL;DR: In this paper, the authors provide an overview of dynamic factor models (DFMs), their estimation, and their uses in empirical macroeconomics, including the use of DFMs for analysis of structural shocks.
Journal ArticleDOI
Factor Analysis as a Statistical Method
Journal ArticleDOI
Statistical analysis of factor models of high dimension
Jushan Bai,Kunpeng Li +1 more
TL;DR: In this paper, the authors considered the maximum likelihood estimation of factor models of high dimension, where the number of variables (N) is comparable with or even greater than the total number of observations (T) and developed an inferential theory to establish not only consistency but also the rate of convergence and limiting distributions.
Journal ArticleDOI
Empirical Asset Pricing via Machine Learning
TL;DR: The authors performed a comparative analysis of machine learning methods for the canonical problem of empirical asset pricing: measuring asset risk premia, and demonstrated large economic gains to investors using machine learning forecasts, in some cases doubling the performance of leading regression-based strategies from the literature.
Journal ArticleDOI
What Drives Oil Prices? Emerging Versus Developed Economies
TL;DR: In this article, the role of demand from emerging and developed economies as drivers of the real price of oil was explored using a FAVAR model that allows us to identify and compare demand from different groups of countries across the world.
References
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Journal ArticleDOI
Forecasting Using Principal Components From a Large Number of Predictors
James H. Stock,Mark W. Watson +1 more
TL;DR: In this paper, the authors consider forecasting a single time series when there are many predictors (N) and time series observations (T), and they show that the difference between the feasible forecasts and the infeasible forecasts constructed using the actual values of the factors converges in probability to 0 as both N and T grow large.
Journal ArticleDOI
Determining the Number of Factors in Approximate Factor Models
Jushan Bai,Serena Ng +1 more
TL;DR: In this article, the convergence rate for the factor estimates that will allow for consistent estimation of the number of factors is established, and some panel criteria are proposed to obtain the convergence rates.
Journal ArticleDOI
Inferential Theory for Factor Models of Large Dimensions
TL;DR: In this paper, the authors developed an inferential theory for factor models of large dimensions and derived the rate of convergence and the limiting distributions of the estimated factors, factor loadings, and common components.
Posted Content
Determining the number of factors in approximate factor models with global and group-specific factors
TL;DR: In this article, an extension of the well known Bai and Ng criteria is proposed for determining the number of global and group-specific factors for an approximate factor model, in a static representation, with a common component comprising global factors and factors specific to groups of variables.
Related Papers (5)
Forecasting Using Principal Components From a Large Number of Predictors
James H. Stock,Mark W. Watson +1 more