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...

The goal of this paper is to construct leading indicators that anticipate inflation cycle turning points on a real time monitoring basis. As a first step, turning points of the IPCA inflation are determined using a periodic stochastic Markov switching model. These turning points are the event...

This paper proposes that an important tenet of monetary policy, as practiced by the Bundesbank, is how it communicates with the public. The results have implications for the conduct of monetary policy more generally. Indeed, recent Fed behavior may also be likened to the experience of the...

This paper analyzes the performance of central banks in 27 inflation targeting countries by examining their success in achieving their explicit inflation targets. For this purpose, we decompose the inflation gap, the difference between actual inflation and inflation target, into predictable and...

I compare the performance of the vector autoregressive (VAR) model impulse response function estimator with the Jordà (2005) local projection (LP) methodology. In a Monte Carlo experiment, I demonstrate that when the data generating process is a well-specified VAR, the standard impulse response...

We propose a methodology for producing forecast densities for economic aggregates based on disaggregate evidence. Our ensemble predictive methodology utilizes a linear mixture of experts framework to combine the forecast densities from potentially many component models. Each component represents...

We propose a methodology for producing forecast densities for economic aggregates based on disaggregate evidence. Our ensemble predictive methodology utilizes a linear mixture of experts framework to combine the forecast densities from potentially many component models. Each component represents...

In this paper we use U.S. real-time vintage data and produce combined density nowcasts for quarterly GDP growth from a system of three commonly used model classes. The density nowcasts are combined in two steps. First, a wide selection of individual models within each model class are combined...