This paper proposes a method for comparing and combining conditional quantile forecasts in an out-of-sample framework. We construct a Conditional Quantile Forecast Encompassing (CQFE) test as a Wald-type test of superior predictive ability. Rejection of CQFE provides a basis for combination of...

This paper proposes a method for comparing and combining conditional quantile forecasts based on the principle of 'encompassing'. Our test for conditional quantile forecast encompassing (CQFE) is a test of superior predictive ability, constructed as a Wald-type test on the coefficients of an...

We jointly test the rationality of the Federal Reserve’s Greenbook forecasts of infiation, unemployment, and output growth using a multivariate nonseparable asymmetric loss function. We find that the forecasts are rationalizable and exhibit directional asymmetry. The degree of asymmetry...

This paper derives necessary and sufficient conditions for nonparametric transformation models to be (i) correctly specified, and (ii) identified. Our correct specification conditions come in a form of partial differential equations; when satisfied by the true distribution, they ensure that the...

This paper establishes the identifiability of the parameters of the Box-Cox model under restrictions that do not require the disturbance in the model to be independent of the explanatory variables. The proposed restrictions are semiparametric in nature: they restrict the support of the...

This paper derives primitive conditions for global identification in nonlinear simultaneous equations systems. Identification is semiparametric in the sense tht it is based on a set of unconditional moment restrictions. Our contribution to the literature is twofold. First, we derive a set of...

In this paper, we propose a new family of multivariate loss functions that can be used to test the rationality of vector forecasts without assuming independence across individual variables. When only one variable is of interest, the loss function reduces to the flexible asymmetric family...

Empirical studies using survey data on expectations have frequently observed that forecasts are biased and have concluded that agents are not rational. We establish that existing rationality tests are not robust to even small deviations from symmetric loss and hence have little ability to tell...

This paper derives sufficient conditions for global identification in nonlinear models characterized by a finite number of unconditional moment restrictions. The main contribution of this paper is to provide a set of assumptions that are alternative to those of Gale-Nikaidô-Fisher-Rothenberg,...