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Working Paper
Federal reserve forecasts: asymmetry and state-dependence
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 depends on the phase of the business cycle: The Greenbook forecasts of output growth are too pessimistic in recessions and too optimistic in expansions. The change in monetary policy that occured in the late 1970s has been attributed in the literature to the Fed coming to terms with the difficulties in ...
Working Paper
Minimum Distance Estimation of Dynamic Models with Errors-In-Variables
Empirical analysis often involves using inexact measures of desired predictors. The bias created by the correlation between the problematic regressors and the error term motivates the need for instrumental variables estimation. This paper considers a class of estimators that can be used when external instruments may not be available or are weak. The idea is to exploit the relation between the parameters of the model and the least squares biases. In cases when this mapping is not analytically tractable, a special algorithm is designed to simulate the latent predictors without completely ...
Working Paper
Asymmetry, Complementarities, and State Dependence in Federal Reserve Forecasts
Forecasts are a central component of policy making; the Federal Reserve''s forecasts are published in a document called the Greenbook. Previous studies of the Greenbook''s inflation forecasts have found them to be rationalizable but asymmetric if considering particular sub-periods, e.g., before and after the Volcker appointment. In these papers, forecasts are analyzed in isolation, assuming policymakers value them independently. We analyze the Greenbook fore- casts in a framework in which the forecast errors are allowed to interact. We find that allowing the losses to interact makes the ...
Working Paper
Multivariate forecast evaluation and rationality testing
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 recently proposed by Elliott, Komunjer, and Timmermann (2005). Following their methodology, we derive a GMM test for multivariate forecast rationality that allows the forecast errors to be dependent, and takes into account forecast estimation uncertainty. We use our test to study the rationality of ...