The Fed's policy rule shifts during different phases of the business cycle, particularly in relation to monetary easing and tightening phases. This finding is established through a dynamic mixture model, which estimates regime-dependent Taylor-type rules using US quarterly data from 1960 to...

The Fed's policy rule switches during the different phases of the business cycle. This finding is established using a dynamic mixture model to estimate regime-dependent Taylor-type rules on US quarterly data from 1960 to 2021. Instead of exogenously partitioning the data based on tenures of the...

Blanchard (2005) suggested that active interest rate policy might induce unstable dynamics in highly-indebted economies. We examine this in a dynamic general equilibrium model where Calvo-type price rigidities provide a rationale for inflation stabilization. Unstable dynamics can occur when the...

We analyse the impact of interactions between monetary and fiscal policy on macroeconomic stability. We find that in the presence of sovereign default beliefs a monetary policy, which aims to stabilize inflation through an active interest rate policy, will destabilize the economy if the feedback...

We examine monetary policy options for a small open economy where sovereign default might occur due to intertemporal insolvency. Under interest rate policy and floating exchange rates the equilibrium is indetermined. Under a fixed exchange rate the equilibrium is uniquely determined and...

Blanchard (2005) suggested that active interest rate policy might induce unstable dynamics in highly-indebted economies. We examine this in a dynamic general equilibrium model where Calvo-type price rigidities provide a rationale for inflation stabilization. Unstable dynamics can occur when the...

We investigate the asymptotic behavior of the WALS estimator, a model-averaging estimator with attractive finite-sample and computational properties. WALS is closely related to the normal location model, and hence much of the paper concerns the asymptotic behavior of the estimator of the unknown...

We propose a novel observation-driven modeling framework that allows for time variation in the model's parameters using a proximal-parameter (ProPar) update. The ProPar update is the solution to an optimization problem that maximizes the logarithmic observation density with respect to the...

All parameters in structural vector autoregressive (SVAR) models are locally identified when the structural shocks are independent and follow non-Gaussian distributions. Unfortunately, standard inference methods that exploit such features of the data for identification fail to yield correct...

This paper addresses the poor performance of the Expectation-Maximization (EM) algorithm in the estimation of low-noise dynamic factor models, commonly used in macroeconomic forecasting and nowcasting. We show analytically and in Monte Carlo simulations how the EM algorithm stagnates in a...