Comparing Density Forecasts via Weighted Likelihood Ratio Tests

By Gianni Amisano, R. Giacomini. 2007

105 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/7ed49778182dc3d68fe5f68e84a2919e82683342

Citations in the corpus

• Nowcasting GDP in Real Time: A Density Combination Approach (2014, unknown): “To measure the density fit for each model through the evaluation period, we use the logarithmic score (see Amisano and Giacomini 2007; Hall and Mitchell 2007).”
• Real-Time Inflation Forecasting in a Changing World (2009, unknown): “Amisano and Giacomini (2007) used a DGP in which a random walk model and a Phillips curve model, calibrated on data, have equal finite-sample predictive power for the conditional mean of inflation, while imposing identical conditional variance across all models and inflation.”
• Dynamic Conditional Correlation: On Properties and Estimation (2013, unknown): “Step 1 consists of a set of N univariate fittings; Step 2 is easy to compute after Step 1; finally, Step 3 is a maximization in two variables.”
• Bayesian VARs : specification choices and forecast accuracy (2011, unknown): “To provide a rough gauge of the statistical significance of differences in average log scores, we use the Amisano and Giacomini (2007) t-test of equal means, applied to the log score for each model relative to the baseline forecast.”
• Multivariate Rotated ARCH Models (2014, unknown): “Using a quasi-likelihood criterion is valid for non-nested and misspeci ed models; see Cox (1961) and Vuong (1989) for in-sample model comparison, and Amisano and Giacomini (2007) for out-of-sample model selection.”
• Combining density forecasts using focused scoring rules (2017, unknown): “A well-founded proper scoring rule is the log score function (see, Amisano & Giacomini, 2007; Mitchell & Hall, 2005, among others).”
• Quantile aggregation of density forecasts (2014, unknown): “In case (1) where data are very persistent (ρ1 = 0.”
• Advances in Forecasting Under Instability (2012, unknown): “If there is no serial correlation in the data, only the …rst component in (6) and (7) is relevant.”
• Generalised Density Forecast Combinations (2015, unknown): “In order to facilitate interpretation of the weights, which might be helpful in some applications, we draw on Amisano & Giacomini (2007) and Diks et al. (2011) who consider weighted scoring rules and suggest the following restricted variant of our method.”
• Forecasting with DSGE Models (2010, unknown): “…increasingly more important role with both important methodological developments (see, e.g., Diebold, Gunther, and Tay, 1998; Christoffersen, 1998; Amisano and Giacomini, 2007) and interesting empirical applications (Diebold, Tay, and Wallis, 1999; Clements and Smith, 2000; Adolfson, Lindé, and…”
• Do Return Prediction Models Add Economic Value (2012, unknown): “First, we allow for a time-varying mean (TVM), but hold volatility constant through the following model: rt+1 = β0 + β1xt + εt+1, εt+1 ∼ N(0, σ(2)), (2)”
• A MIDAS Approach to Modeling First and Second Moment Dynamics (2016, unknown): “To measure the importance of such differences, we follow Amisano and Giacomini (2007), Geweke and Amisano (2010), and Hall and Mitchell (2007) and compute the average log-score differential (LSD) LSD i = t τ =t (LS i,τ − LS RW,τ ) , (38) where LS i,τ (LS RW,τ ) denotes the log-score of model i…”
• Macroeconomic Forecasting and Structural Change (2010, unknown): “Journal of the European Economic Association, 6(2-3):621-633.”