Determining potential output and the output gap-two inherently unobservable variables-is a major challenge for macroeconomists. This paper presents the R package sectorgap, which features a flexible modeling and estimation framework for a multivariate Bayesian state space model identifying...

We propose a multivariate Bayesian state space model to identify potential growth and the output gap consistent with the dynamics of the underlying production sectors of the economy and those of inflation and the labor market. Our approach allows us to decompose economic fluctuations and...

We propose a simple modification of the time series filter by Hamilton (2018b) that yields reliable and economically meaningful real-time output gap estimates. The original filter relies on 8-quarter ahead forecasts errors of an autoregression. While this approach yields a cyclical component of...

The authors contribute to the debate regarding the reliability of output gap estimates. As an alternative to the Hodrick-Prescott (HP) filter, they propose a simple modification of the filter proposed by Hamilton in 2018 that shares its favorable real-time properties, but leads to a more even...

The Global Financial Crisis established that policymakers should consider the stage of the financial cycle to better evaluate the cyclical position of the economy when designing monetary policy decisions. If financial variables are omitted from the estimations of the output gap, a common and...

Assessing potential output and the output gap is essential for policy-making and fiscal surveillance. The European Commission proposes a production function methodology that involves the estimation of two classes of Gaussian state space models. This paper presents the R package RGAP which...