Using real-time data I estimate out-of-sample forecast uncertainty about the Federal Funds Rate. Combining a Taylor rule with a model of economic fundamentals I disentangle economically interpretable components of forecast uncertainty: uncertainty about future economic conditions and uncertainty...

This paper uses real-time data for the U.S. to estimate out-of-sample forecast uncertainty about the Federal Funds Rate. By combining a Taylor rule with an unobserved components model of economic fundamentals I separate forecast uncertainty into economically interpretable components that...

This paper studies uncertainty about out-of-sample interest rate forecasts implied by an estimated Taylor rule. It is shown that the Taylor rule leads to a decomposition of forecast uncertainty into an element that depends on uncertainty about the future state of the economy and another element...

We use a Taylor rule with time-varying policy coefficients in combination with an unobserved components model for the output gap to estimate the uncertainty about future values of the Federal Funds Rate. The model makes it possible to separate ex-ante interest rate uncertainty into three...

The forecasting of government revenues is extremely important for an adequate budget execution, since a good accuracy in the estimation allows the stipulation of an expenditure level that meets the demands of the population. Using data released by the National Council of Treasury Policy, the...

In this paper, the application of two different unobserved factor models to a data set from Estonia is presented. The small-scale state-space model used by Stock and Watson (1991) and the large-scale static principal components model used by Stock and Watson (2002) are employed to derive common...

The Stock--Watson coincident index and its subsequent extensions assume a static linear one-factor model for the component indicators. Such assumption is restrictive in practice, however, with as few as four indicators. In fact, such assumption is unnecessary if one poses the index construction...

This article presents a new filter for state-space models based on Bellman's dynamic programming principle applied to the posterior mode. The proposed Bellman filter generalises the Kalman filter including its extended and iterated versions, while remaining equally inexpensive computationally....

The forecasting of government revenues is extremely important for an adequate budget execution, since a good accuracy in the estimation allows the stipulation of an expenditure level that meets the demands of the population. Using data released by the National Council of Treasury Policy, the...