Working Paper: CEPR ID: DP3821
Authors: Graham Elliott; Ivana Komunjer; Allan G. Timmermann
Abstract: In situations where a sequence of forecasts is observed, a common strategy is to examine ?rationality? conditional on a given loss function. We examine this from a different perspective - supposing that we have a family of loss functions indexed by unknown shape parameters, then given the forecasts can we back out the loss function parameters consistent with the forecasts being rational even when we do not observe the underlying forecasting model? We establish identification of the parameters of a general class of loss functions that nest popular loss functions as special cases and provide estimation methods and asymptotic distributional results for these parameters. The methods are applied in an empirical analysis of IMF and OECD forecasts of budget deficits for the G7 countries. We find that allowing for asymmetric loss can significantly change the outcome of empirical tests of forecast rationality.
Keywords: Asymmetric loss; IMF; Macroeconomic forecasting; OECD
JEL Codes: C10; E00
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| loss function parameters (C51) | optimality of forecasts (C53) |
| asymmetric loss function (D81) | systematic overpredictions of budget deficits (H68) |
| forecast errors (C53) | forecasters' asymmetric loss functions (C53) |
| assumptions about the loss function (C51) | results of rationality tests (D01) |