This paper has adopted a Bayesian FAVAR approach to examine the monetary transmission mechanism in North Macedonia. The model is based on a broad data set that encompasses 140 monthly time series spanning between January 2010 and January 2019. In particular, the impact of policy on bank...

Monetary policy moves the yield curve. How much is due to expected interest rates vs. term premia? And does it matter for macroeconomic outcomes? Using an affine term structure model, we shed new light on these questions. Estimation is subject to restrictions addressing an estimation bias in...

The secular increase in globalization led to a substantial increase in the interconnectedness of global financial markets. This has important implications for the conduct of monetary policy, as central bank policies may diverge across countries, potentially affecting key transmission channels of...

Central banks have usually employed short-term rates as the main instrument of monetary policy. In the last decades, however, forward guidance has also become a central tool for monetary policy. In an innovative way this paper combines two sources of extraneous information - high frequency...

Sign-restricted Structural Vector Autoregressions (SVARs) are increasingly common. However, they usually result in a set of structural parameters that have very different implications in terms of impulse responses, elasticities, historical decomposition and forecast error variance decomposition...

We show that the contemporaneous and longer horizon impulse responses estimated using small-scale Proxy structural vector autoregressions (SVARs) can be severely biased in the presence of information insufficiency. Instead, we recommend the use of a Proxy Factor Augmented VAR (FAVAR) model that...

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...

In this paper we introduce the general setting of a multivariate time series autoregressive model with stochastic time-varying coefficients and time-varying conditional variance of the error process. This allows modeling VAR dynamics for non-stationary times series and estimation of time varying...

Following Giraitis, Kapetanios, and Yates (2014b), this paper uses kernel methods to estimate a seven variable time-varying (TV) vector autoregressive (VAR) model on the data set constructed by Smets and Wouters (2007). We apply an indirect inference method to map from this TV VAR to time...