In this paper we analyze a hybrid small-scale New-Keynesian model with an arbitrary frequency of the agents synchronized decision making. We study the impact of various demand and supply shocks on the dynamics of the model variables. We show that the corresponding impulse-response functions of...

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...

The research work presented below addresses the possible concern of central bank independence through the development and application of econometric models. The complexity of the modelling has allowed a step further in corroborating that financial independence is not only linked to the...

The Hodrick-Prescott filter is a popular tool in macroeconomics for decomposing a time series into a smooth trend and a business cycle component. The last few years have witnessed global events, such as the Global Financial Crisis, the COVID-19 pandemic, and the war in Ukraine, that have had...

Monetary policy research using time series methods has been criticized for using more information than the Federal Reserve had available in setting policy. To quantify the role of this criticism, we propose a method to estimate a VAR with real-time data while accounting for the latent nature of...

Output gap estimates are subject to a wide range of uncertainty owing to data revisions and the difficulty in distinguishing between cycle and trend in real time. This is important given the central role in monetary policy of assessments of economic activity relative to capacity. We show that...

This paper investigates how the ordering of variables affects properties of the time-varying covariance matrix in the Cholesky multivariate stochastic volatility model.It establishes that systematically different dynamic restrictions are imposed whenthe ratio of volatilities is time-varying....

This paper investigates how the ordering of variables affects properties of the time-varying covariance matrix in the Cholesky multivariate stochastic volatility model. It establishes that systematically different dynamic restrictions are imposed when the ratio of volatilities is time-varying....