Fabio Verona

Un)anticipated monetary policy in a DSGE model with a shadow banking system

Motivated by the U.S. events of the 2000s, we address whether a too low for too long interest rate policy may generate a boom-bust cycle. We simulate anticipated and unanticipated monetary policies in state-of-the-art DSGE models and in a model with bond financing via a shadow banking system, in which the bond spread is calibrated for normal and optimistic times. Our results suggest that the U.S. boom-bust was caused by the combination of (i) interest rates that were too low for too long, (ii) excessive optimism and (iii) a failure of agents to anticipate the extent of the abnormally favourable conditions.

Investment Dynamics with Information Costs

Investment in physical capital at the micro level is infrequent and large, or lumpy. The most common explanation for this is that firms face non-convex physical adjustment costs. The model developed in this paper shows that information costs make investment lumpy at the micro level, even in the absence of non-convex adjustment costs. When collecting and processing information is costly, the firm optimally chooses to do it sporadically and to be inactive most of the time. This behavior results in infrequent and possibly large capital adjustments. The model fits plant-level investment rate moments well, and it also matches some higher order moments of aggregate investment rates.

Lumpy investment in sticky information general equilibrium

In this paper, I introduce lumpy micro-level capital adjustment into a sticky information general equilibrium model. Lumpy adjustment arises because of inattentiveness in capital investment decisions instead of the more common assumption of non-convex adjustment costs. The model features inattentiveness as the only source of stickiness. I find that the model with lumpy investment yields business cycle dynamics which differ substantially from those of an otherwise identical model with frictionless investment and are much more consistent with the empirical evidence. These results therefore strengthen the case in favour of the relevance of microeconomic investment lumpiness for the business cycle. Keywords: sticky information, general equilibrium, lumpy investment, business cycle JEL classification: D83, E10, E22, E32

Financial Shocks and Optimal Monetary Policy Rules

We assess the performance of optimal Taylor-type interest rate rules, with and without reaction to financial variables, in stabilizing the macroeconomy following financial shocks. We use a DSGE model that comprises both a loan and a bond market, which best suits the contemporary structure of the U.S. financial system and allows for a wide set of financial shocks and transmission mechanisms. Overall, we find that targeting financial stability – in particular credit growth, but in some cases also financial spreads and asset prices – improves macroeconomic stabilization. The specific policy implications depend on the policy regime, and on the origin and the persistence of the financial shock.

The equity risk premium and the low frequency of the term spread

We extract cycles in the term spread (TMS) and study their role for predicting the equity risk premium (ERP) using linear models. The low frequency component of the TMS is a strong and robust out-of-sample ERP predictor. It obtains out-of-sample R-squares (versus the historical mean benchmark) of 1.98% and 22.1% for monthly and annual data, respectively. It forecasts well also during expansions and outperforms several variables that have been proposed as good ERP predictors. Its predictability power comes exclusively from the discount rate channel. Contrarily, the high and business-cycle frequency components of the TMS are poor out-of-sample ERP predictors.