This paper applies the Model Confidence Set (MCS) procedure of Hansen, Lunde, and Nason (2003) to a set of volatility models. A MCS is analogous to confidence interval of a parameter in the sense that the former contains the best forecasting model with a certain probability. The key to the MCS...

In this study, we analyse the sustainability of fiscal policy of EU member countries within the panel cointegration and error-correction frameworks. Unlike the previous empirical papers in this area, we apply the test for panel cointegration between the primary budget deficit and the public debt...

This paper examines the effects of monetary policy shocks on UK regional economic growth and dispersion in a novel Constrained Mixed Frequency Vector Autoregressive framework. Compared to a standard MFVAR, the model partially accounts for missing quarterly observations for regional growth by...

Various inflation forecasting models are compared using a simulated out-of-sample forecasting framework. We focus on the question of whether monetary aggregates are useful for forecasting inflation, but unlike previous work we examine a wide range of forecast horizons and allow for estimated as...

We study the transmission of monetary shocks and monetary policy with a behavioral model, corrected for potential misspecification using the DSGE-VAR framework elaborated by DelNegro and Schorfheide (2004). In particular, we investigate if the central bank should react to movements in the...

A long tradition in macro finance studies the joint dynamics of aggregate stock returns and dividends using vector autoregressions (VARs), imposing the cross-equation restrictions implied by the Campbell-Shiller (CS) identity to sharpen inference. We take a Bayesian perspective and develop...

This paper estimates monetary policy shocks for Sweden between 1996-2019. I employ the Romer and Romer (2004) (R&R) approach and use annual forecasts of output growth and inflation to estimate monetary policy shocks. I complement the analysis with shocks from a recursive VAR including output,...

We bring together some recent advances in the literature on vector autoregressive moving-average models creating a relatively simple specification and estimation strategy for the cointegrated case. We show that in the cointegrated case with fixed initial values there exists a so-called final...

Many statistical applications require the forecast of a random variable of interest over several periods into the future. The sequence of individual forecasts, one period at a time, is called a path forecast, where the term path refers to the sequence of individual future realizations of the...

Inference on the long-run properties of a Vector Autoregression (VAR) consisting wholly of I(1) variables are made using Bayesian methods. In particular, the implications on the forecast and impulse response function distributions of directly estimating and restricting the drift parameters of...