EVALUATING T HE BANK OF ENGLAND D ENSITY FORECASTS OF INFLATION

By Michael P. Clements. 2004

149 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/1d98bc49e2466c676734e44d533cf8aa84b54053

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Citations in the corpus

Combining inflation density forecasts (2010, methodology): “Equal weights (EW): Equal weights for combining densities have been proposed in the literature by Hendry & Clements (2004) and Wallis (2005).”
Real-Time Density Forecasts From Bayesian Vector Autoregressions With Stochastic Volatility (2011, methodology): “These tests, which have better power than tests based on the uniformity of the PITs, have been used in recent studies such as Clements (2004) and Jore, Mitchell, and Vahey (2010).”
Evaluating Probabilistic Forecasts with scoringRules (2017, background): “Clements MP (2004). “Evaluating the Bank of England Density Forecasts of Inflation.”
Evaluating the Calibration of Multi-Step-Ahead Density Forecasts Using Raw Moments (2015, methodology): “Finally, in several applications like those by Clements (2004), Mitchell and Hall (2005), Jore, Mitchell, and Vahey (2010), Bache et al. (2011), and Aastveit et al. (2011) one finds a variant of the test by Berkowitz (2001) adapted to the case of serially correlated INTs.”
Regression diagnostics meets forecast evaluation: conditional calibration, reliability diagrams, and coefficient of determination (2021, methodology): “…Bank of England forecasts of inflation rates have been checked for reliability by Wallis (2003), who considered probabilistic calibration, by Clements (2004) in terms of probabilistic, mean, and threshold calibration, by Galbraith and van Norden (2012), who considered probabilistic and mean…”
Alternative tests for correct specification of conditional predictive densities (2019, background): “4See for instance Clements (2004) for a discussion on the Bank of England fan charts. pattern: the uncertainty surrounding output growth forecasts is constant across horizons, while it depends on the horizon for interest rates.”
Comparing Density Forecasts Using Threshold- and Quantile-Weighted Scoring Rules (2011, methodology): “The Bank of England’s Monetary Policy Committee (MPC) has issued probabilistic forecasts of inflation rates and gross domestic product every quarter since February 1996 and November 1997, respectively, using fan charts to visualize the deciles of the predictive distributions (Wallis 2003, 2004; Clem”
Combining forecast densities from VARs with uncertain instabilities (2010, methodology): “That is, we use the same economic variables, and their respective measures.”
The Evolution of Forecast Density Combinations in Economics (2018, methodology): “Pauwels and Vasnev (2016) provide further analysis of (7) and document the properties of this optimization problem; Conflitti et al. (2015) provide an iterative algorithm for (7) that enables the optimal combination to be viable even when the number of density forecasts, N , combined is large.”
Likelihood-based scoring rules for comparing density forecasts in tails (2011, background): “…obtained from a variety of sources, including statistical time series models (Clements and Smith, 2000), professional forecasters (Diebold et al., 1999), and central banks and other institutions producing so-called ‘fan charts’ for these variables (Clements, 2004; Mitchell and Hall, 2005).”