Are more data always better for factor analysis

By Jean Boivin, Serena Ng. 2006

904 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Management Science and Operations Research

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Citations in the corpus

Principal Components and Regularized Estimation of Factor Models (2017, background): “Boivin and Ng (2006) considers re-weighting each series by the standard-deviation of the idiosyncratic error, obtained from a preliminary (unweighted) estimation of the factor model.”
Sufficient Forecasting Using Factor Models (2015, background): “Boivin and Ng (2006) pointed out that the relevance of factors is important to the forecasting power, and may lead to improved forecast.”
Introducing the Euro-STING: Short Term INdicator of Euro Area Growth (2010, methodology): “u1t = b1u1t 1 + :::+ bm2u1t m2 + u1 t ; (9)”
A two-step estimator for large approximate dynamic factor models based on Kalman filtering (2011, methodology): “This estimator has been considered in Forni and Reichlin (2000), Boivin and Ng (2004), Forni, Hallin, Lippi and Reichlin (2005).”
Asymptotics of the principal components estimator of large factor models with weakly influential factors (2012, methodology): “He explains how to nd x directly from system (7).”
Bayesian VARs : specification choices and forecast accuracy (2011, positive): “For example, Boivin and Ng (2006) suggest that pre-selecting the variables that are included in a factor model according to their relationship with the target variable of interest can improve the forecasting precision.”
Tracking the Slowdown in Long-Run GDP Growth (2017, background): “14 As for the possible inclusion of disaggregated series within each category, Boivin and Ng (2006) argue that the presence of strong correlation in the idiosyncratic components of disaggregated series of the same category will be a source of misspecification that can worsen the performance of the m”
Forecasting with Factor-Augmented Regression: A Frequentist Model Averaging Approach, Second Version (2013, neutral): “Alternative methods are available to estimate F , such as the GLStype estimators considered by Boivin and Ng (2006), Forni et al. (2005), Stock and Watson (2005), Breitung and Tenhofen (2011), Choi (2012), and Doz et al.”
Markov-switching dynamic factor models in real time (2018, neutral): “y T+1=T = 1 1 3 h (i;j) T+1jT (1) + 2 3 h (i;j) T+1jT (2) + h (i;j) T+1jT (3) + 2 3 h (i;j) T+1jT (4) + 1 3 h (i;j) T+1jT (5) + 1 3 h (i;j) T+1jT (13) + 2 3 h (i;j) T+1jT (14) + h (i;j) T+1jT (15) + 2 3 h (i;j) T+1jT (16) + 1 3 h (i;j) T+1jT (17) ; (43) It is worth noting that including a missing ob”
EXTRACTING NONLINEAR SIGNALS FROM SEVERAL ECONOMIC INDICATORS (2012, neutral): “8 According to the Markov-chain properties of the model described in (1) to (3), prob(st = 1jI1;t; I2;t) = prob(st = 1jy1;t; :::; yN;t) and prob(st = 1jI1;t) = prob(st = 1jy1;t; :::; yN 1;t): Then, the inference computed from the set of N indicators can be expressed as”
DSGE Models in a Data-Rich Environment (2006, neutral): “This is a standard unobserved component model in which gt and νt can be separately identified only from the restricted dynamics of the system (12)—(13).”
Analyzing International Business and Financial Cycles using Multi-Level Factor Models: A Comparison of Alternative Approaches (2016, methodology): “As argued by Boivin and Ng (2006) the efficiency of the Principal Component (PC) estimator may deteriorate substantially if groups of variables are included that do not provide any information about the factors, that is, the corresponding factor loadings of some subgroups of variables are equal to…”
Nowcasting GDP and Inflation: The Real Time Informational Content of Macroeconomic Data Releases (2005, neutral): “With most practitioners of monetary policy commonly interested in inflation 12Different versions of such an estimator were proposed by Boivin and Ng (2003), Forni and Reichlin (2001), Forni, Hallin, Lippi, and Reichlin (2003). and growth at the quarterly frequency (in part because this is the…”
Estimating and Forecasting the Euro Area Monthly National Accounts from a Dynamic Factor Model (2010, positive): “Boivin and Ng (2006) have argued that using smaller data sets may improve the forecasts.”
OPENING THE BLACK BOX: STRUCTURAL FACTOR MODELS WITH LARGE CROSS SECTIONS (2009, background): “Printed in the United States of America. doi:10.1017/S026646660809052X”
Now-Casting and the Real-time Data Flow (2013, neutral): “An alternative approach consists in selecting the variables using statistical criteria as suggested in Boivin and Ng (2006); Bai and Ng (2008).”