Least-squares forecast averaging

By B. Hansen. 2008

301 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/8c8a11c3e71b4cd25ff11469db92e5e01457f5c1

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Citations in the corpus

Generalized Least Squares Model Averaging (2016, unknown): “Moreover, Hansen (2008) cleverly illustrates the close connection between Mallows’ Cp and prediction risk.”
Variable Selection in Predictive Regressions (2013, methodology): “This is the method of model averaging pioneered by Bates and Granger (1969), reviewed in Timmermann (2006), and further developed in Hansen (2008); Hansen and Racine (2012).”
Jackknife model averaging for quantile regressions (2015, unknown): “Hansen (2008, 2009, 2010) extends his MMA method to the forecast combination literature, to models with structural break, and to models with a near unit root, respectively.”
Least squares model averaging by Mallows criterion (2010, methodology): “Hansen (2007, 2008)) also noted this problem.”
Model averaging by jackknife criterion in models with dependent data (2013, methodology): “…a fully-fledged frequentist standpoint were made by Buckland et al. (1997), Yang (2001), Hjort and Claeskens (2003, 2006), Yuan and Yang (2005), Hansen (2007, 2008), Goldenshluger (2009), Schomaker et al. (2010), Wan et al. (2010), Liang et al. (2011), Zhang and Liang (2011), Zhang et al.…”
Transferability of hydrological models and ensemble averaging methods between contrasting climatic periods (2016, methodology): “…that using a multimodel ensemble is superior to relying on an individual model, the best way of combining ensemble members remains an area of active research [e.g., Shamseldin et al., 1997; Abrahart and See, 2002; Ajami et al., 2006; Hansen, 2008; Diks and Vrugt, 2010; Arsenault et al., 2015].”
The Forecast Combination Puzzle: A Simple Theoretical Explanation (2016, methodology): “This is the case in Bates and Granger (1969) and it remains the case in later contributions, important and insightful as they may be, such as Hansen (2008), Elliott (2011), Liang et al. (2011), and Hsiao and Wan (2014).”
To Combine Forecasts or to Combine Information? (2010, methodology): “3See, for example, Granger and Ramanathan (1984), Deutsch, Granger, and Teräsvirta (1994), Shen and Huang (2006), and Hansen (2006).”
Is there an optimal forecast combination (2014, unknown): “Following Hansen (2008), we generate the coe¢cients of xkt as k = r p 1 p k; (39) k = k K + 1 1 k K + 1 = KX k=1 " k K + 1 1 k K + 1 #2 ; (40) = k + K + 1 k = KX k=1 k2( + ) K + 1 k 2 (41) where p takes on the value on the grid of f0:1; 0:2; :::; 0:9g which are the third rows of Table 1.”
Forecasting with Factor-Augmented Regression: A Frequentist Model Averaging Approach, Second Version (2013, unknown): “This result is similar to the theory of Hansen (2008) for forecast combination without estimated factors.”
Focused Information Criteria, Model Selection, and Model Averaging in a Tobit Model With a Nonzero Threshold (2012, methodology): “Some goodness-of-fit measures for Tobit models also have been developed by Amemiya (1981), Heckman (1984), Dhrymes (1986), and Laitila (1993).”
Forecasting: theory and practice (2020, background): “…goes back to Bates and Granger (1969) and a summary of more recent work is provided in (Timmermann, 2006), while the ability of such methods to improve prediction accuracy is extensively documented (see, for example, Stock and Watson, 2004; Hansen, 2008; Guidolin and Timmermann, 2009, inter alia).”
Averaging estimators for autoregressions with a near unit root (2010, unknown): “1c + (1 w) 2 ET2 0c + 2w(1 w)E (T0cT1c) + k which is ( 22 ).”
INFERENCE AFTER MODEL AVERAGING IN LINEAR REGRESSION MODELS (2018, unknown): “Bayesian model averaging has a long history, and has been widely used in statistical and economic analysis; see Hoeting et al. (1999) for a literature review.”