Least Squares Model Averaging

By B. Hansen. 2007

846 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/890746b6294c6799abdf26b70b4b22dedbf5ee35

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Citations in the corpus

A Model-Averaging Approach for High-Dimensional Regression (2014, methodology): “…Kass and Raftery 1995; Raftery, Madigan, and Hoeting 1997; Hoeting et al. 1999; Fernandez, Ley, and Steel 2001), the Mallows Cp model averaging (Hansen 2007; Wan, Zhang, and Zou 2010; see also Mallows 1973), Bayesian model averaging using predictive measures (Eklund and Karlsson 2007),…”
Estimating the Armington elasticity: The importance of study design and publication bias (2020, methodology): “Following Hansen (2007), we use Mallow’s criterion for model averaging and the approach of Amini & Parmeter (2012) towards the orthogonalization of the covariate space.”
Generalized Least Squares Model Averaging (2016, positive): “Thus, at least in our simulation design, we deduce that our method can reduce risk more than model selection methods examined in the simulation experiments of Hansen (2007) and Hansen and Racine (2012).”
Bonferroni-Based Size-Correction for Nonstandard Testing Problems (2017, positive): “10 interest may lie on the boundary of its parameter space (e.g., Andrews and Guggenberger, 2010a), tests on model-averaged estimators (e.g., Hansen, 2007), tests on certain types of shrinkage estimators (e.g., Hansen, 2011), tests in autoregressive models that may contain a unit root (e.g., AG and…”
Jackknife model averaging for quantile regressions (2015, positive): “In a seminal article, Hansen (2007) proposes selecting the model weights in least squares model averaging by minimizing the Mallows’ criterion over a set of discrete weights.”
Weighted‐Average Least Squares (WALS): A Survey (2016, methodology): “Additional comparisons between WALS, standard BMA, and a modified version of the Mallows model-average (MMA) estimator of Hansen (2007) are provided by Amini and Parmeter (2012) using data from three earlier studies on growth empirics.”
Inverse groundwater modeling for hydraulic conductivity estimation using Bayesian model averaging and variance window (2008, methodology): “These information criteria include the Akaike information criterion (AIC) [Akaike, 1973, 1974], the corrected Akaike information criterion (AICc) [Sugiura, 1978; Hurvich and Tsai, 1989], Mallows’ criterion [Mallows, 1973; Hansen, 2007], the Bayesian information criterion (BIC) [Schwarz, 1978], Hanna”
Forecasting with Factor-Augmented Regression: A Frequentist Model Averaging Approach, Second Version (2013, methodology): “In the context of independent observations this has been established for Mallows selection by Li (1987) and for Mallows combination by Hansen (2007).”
A flexible semiparametric forecasting model for time series (2015, methodology): “JEL subject classifications: C14, C22.”
Optimal Weight Choice for Frequentist Model Average Estimators (2011, methodology): “Hansen (2007) concentrated on the estimation of μ∗ = H + Bυ, and evaluated the performance of ̂mma, the MMA estimator of , in terms of the criterion R∗ = E‖Ĥmma − μ∗‖2, which is the risk of the estimator of the prediction vector.”
Focused Information Criteria, Model Selection, and Model Averaging in a Tobit Model With a Nonzero Threshold (2012, background): “More recently, Hansen (2007, 2008) and Wan, Zhang, and Zou (2010) investigated the properties of a frequentist model average estimator based on the Mallows criterion in linear regression.”
Distribution Theory of the Least Squares Averaging Estimator (2013, neutral): “Buckland, Burnham, and Augustin (1997) suggest selecting the weights using the exponential AIC.”
Are Any Growth Theories Robust (2008, background): “including Candolo, Davison, and Demétrio (2003); see also Hjort and Claeskens (2003) and Hansen (2006) for development of statistical theory.”
STRUCTURAL THRESHOLD REGRESSION (2016, positive): “apply to linear models (e.g., Brock and Durlauf, 2001; Hansen, 2007) to threshold regression.”
Averaging estimators for autoregressions with a near unit root (2010, background): “We have found that the AMSE and forecast risk are only a function of the local-to-unity parameter c and the order of the trend function p, and is affected by the autoregressive order k only by an intercept shift.”
Model averaging in ecology: a review of Bayesian, information-theoretic, and tactical approaches for predictive inference (2018, methodology): “Instead, Mallows’ model averaging (MMA) has been shown to yield the lowest mean squared error for linear models (Hansen 2007, Schomaker et al. 2010).”
TESTING FOR A UNIT ROOT IN THE PRESENCE OF A POSSIBLE BREAK IN TREND (2009, background): “an unknown point in the sample, and by Harvey et al. (2007a) and Perron and Yabu (2007) for unit root tests where it is uncertain as to whether the data contain a constant and linear trend or simply a constant.”