Comparing Information in Forecasts from Econometric Models

By R. Fair, Robert J. Shiller. 1990

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Citations in the corpus

Optimal combination forecasts for hierarchical time series (2011, background): “…there has also been some interest in the potential improvements in forecast accuracy that are possible by aggregating component forecasts rather than simply forecasting the aggregate itself (e.g., Fair & Shiller 1990, Zellner & Tobias 2000, Marcellino et al. 2003, Espasa et al. 2002, Hubrich 2005).”
Modeling Conditional Volatility of the Indian Stock Markets (2005, methodology): “Fair and Shiller (1989, 1990) propose a regression-based method which is subsequently followed by Day and Lewis (1992) for examining the informational content of forecasts.”
Macroeconomic forecasting in the Euro area: Country specific versus area-wide information (2003, methodology): “Looking across variables and forecast horizons, the most accurate forecasts are produced by pooling country-speci&c univariate autoregressions, a method called “autoregressive components” by Fair and Shiller (1990). If we restrict attention to multivariate models, the forecasts based on estimated fa”
Model Selection Tests for Nonlinear Dynamic Models (2002, unknown): “1 9 · Findley (1990) notes that comparing the (in-sample) log-likelihood values is also equivalent to comparing the one-step MSEP when the competing models are Gaussian ARMA or ARIMA models.”
Asymptotics for out of sample tests of Granger causality (2007, methodology): “…(1980) provide an intuitive argument that out-of-sample methods are more closely aligned with the spirit of the original concept of Granger causality.2 They also, along with Fair and Shiller (1990), argue that out-of-sample inference may be robust to model selection biases and overfitting.”
Comparing Predictive Accuracy (1995, background): “That, of course, is the well-known message of the forecast combination and encompassing literatures; see, for example, Clemen (1989), Chong and Hendry (1986), and Fair and Shiller (1990).”
Optimal combinations of realised volatility estimators (2009, methodology): “Finally, we conduct a set of tests related to idea of forecast encompassing; see Chong and Hendry (1986) and Fair and Shiller (1990).”
The Use and Abuse of Real-Time Data in Economic Forecasting (2000, unknown): “1 As the sample period over which the forecasting equation is estimated is extended, the vintage of the data used to estimate the equation is updated.”
A real-time data set for macroeconomists (2001, background): “Data revisions are important because they may a-ect policy decisions or the manner in which such decisions depend on the most recent data, as Maravall and Pierce (1986) investigated some years ago.”
How useful are the forecasts of intergovernmental agencies? The IMF and OECD versus the consensus (2001, methodology): “Third, Harvey et al. (1997) show that in Equation 1, under the alternative hypothesis of signi® cant diŒerences in forecast mean square errors, the variance of the residuals depends on the level of the independent variable, so that cov .”
Does age structure forecast economic growth (2007, unknown): “Short run forecasts of single country growth rates using autoregression or vector autoregression models are common (Brischetto and Voss, 2000; Clements and Hendry, 1998; Fair and Shiller, 1990; Robertson and Tallman, 1999; Stock and Watson, 1998), but forecasts of cross-country variation in economic”
Stock Return Predictability and Model Uncertainty (2002, unknown): “The second scheme, the recursive (Fair and Shiller, 1990), uses all available data in the sense that the model parameters are first estimated based on data from 1 to P , next with data from 1 to P + 1, . . ., and finally with data from 1 to T − 1.”