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Are linear models really unuseful to describe business cycle data?

Lopes, Artur C. B. da Silva; Zsurkis, Gabriel Florin - 2017

need to use nonlinear models to describe business cycle dynamic behaviour. Their approach is model (estimation)-free, based … frequently useful. Contrarily to common knowledge, nonlinear business cycle variation does not seem to be a universal … nonlinear dynamics for some further countries is obtained indirectly, through unit root tests, but this can hardly be invoked to …

Persistent link: https://www.econbiz.de/10011596878

Can Confidence Indicators Be Useful to Predict Short Term Real GDP Growth?

Mourougane, Annabelle; Roma, Moreno - 2021

We investigate the usefulness of the European Commission confidence indicators in forecasting real GDP growth rates in the short-run in selected euro areas countries (Belgium, Spain, Germany, France, Italy and the Netherlands) which account for almost 90% of the euro area. We estimate a linear...

Persistent link: https://www.econbiz.de/10013320245

Selecting primal innovations in DSGE models

Ferroni, Filippo; Grassi, Stefano; León-Ledesma, Miguel A. - 2017

DSGE models are typically estimated assuming the existence of certain primal shocks that drive macroeconomic fluctuations. We analyze the consequences of estimating shocks that are "non-existent" and propose a method to select the primal shocks driving macroeconomic uncertainty. Forcing these...

Persistent link: https://www.econbiz.de/10012030335

Sparse trend estimation

Crump, Richard K.; Gospodinov, Nikolaj; Wieman, Hunter - 2023

The low-frequency movements of many economic variables play a prominent role in policy analysis and decision-making. We develop a robust estimation approach for these slow-moving trend processes, which is guided by a judicious choice of priors and is characterized by sparsity. We present some...

Persistent link: https://www.econbiz.de/10013548955

A Composite Likelihood Approach for Dynamic Structural Models

Canova, Fabio - 2019

We describe how to use the composite likelihood to ameliorate estimation, computational, and inferential problems in dynamic stochastic general equilibrium models. We present a number of situations where the methodology has the potential to resolve well-known problems. In each case we consider,...

Persistent link: https://www.econbiz.de/10012898448

Fundamental shock selection in DSGE models

Ferroni, Filippo; Grassi, Stefano; León-Ledesma, Miguel A. - 2015

DSGE models are typically estimated assuming the existence of certain structural shocks that drive macroeconomic fluctuations. We analyze the consequences of introducing nonfundamental shocks for the estimation of DSGE model parameters and propose a method to select the structural shocks driving...

Persistent link: https://www.econbiz.de/10010517720

Selecting primal innovations in DSGE models

Ferroni, Filippo; Grassi, Stefano; León-Ledesma, Miguel A. - 2017

DSGE models are typically estimated assuming the existence of certain primal shocks that drive macroeconomic fluctuations. We analyze the consequences of estimating shocks that are \non-existent" and propose a method to select the primal shocks driving macroeconomic uncertainty. Forcing these...

Persistent link: https://www.econbiz.de/10011774976

Sparse Trend Estimation

Crump, Richard K.; Gospodinov, Nikolaj; Wieman, Hunter - 2023

Persistent link: https://www.econbiz.de/10014257843

Measures of the Output Gap in the Euro-Zone: An Empirical Assessment of Selected Methods

Döpke, Jörg; Chagny, Odile - 2001

The paper discusses some widely used methods for estimating output gaps based on aggregated data for the eurozone. Though these methods exhibit some common features, an empirical comparison demonstrates that the various techniques differ substantially. In particular, the correlation of output...

Persistent link: https://www.econbiz.de/10010260457

Estimating the output gap after COVID : an application to Colombia

Granados, Camilo; Parra-Amado, Daniel - 2023

This study examines whether and how important it is to adjust output gap frameworks during the COVID-19 pandemic and similar unprecedentedly large-scale episodes. Our proposed modelling framework comprises a Bayesian Structural Vector Autoregresion with an identification setup based on a...

Persistent link: https://www.econbiz.de/10014232751