Structural vector autoregressive (VAR) models are in frequent use for impulse response analysis. If cointegrated variables are involved, the corresponding vector error correction models offer a convenient framework for imposing structural long-run and short-run restrictions. Occasionally it is...

Vector autoregressions (VARs) are flexible time series models that can capture complex dynamic interrelationships among macroeconomic variables. However, their dense parameterization leads to unstable inference and inaccurate out-of-sample forecasts, particularly for models with many variables....

We study a model in which prices respond slowly to shocks because firms must pay a fixed cost to observe the determinants of the profit maximizing price, as pioneered by Caballero (1989) and Reis (2006). We extend their analysis to the case of random tran- sitory variation in the firm’s...

We model the pricing decisions of a multi-product firm that faces a fixed 'menu' cost: once the cost is paid, the firm can adjust the price of all its products. We characterize analytically the steady state firm’s decision in terms of the structural parameters: the variability of the flexible...

This paper proposes methods for estimation and inference in multivariate, multi-quantile models. The theory can simultaneously accommodate models with multiple random variables, multiple confidence levels, and multiple lags of the associated quantiles. The proposed framework can be conveniently...

We investigate the interdependence of the default risk of several Eurozone countries (France, Germany, Italy, Ireland, the Netherlands, Portugal, and Spain) and their domestic banks during the period between June 2007 and May 2010, using daily credit default swaps (CDS). Bank bailout programs...