We propose a two-stage estimation procedure to identify the effects of time-invariant regressors in a dynamic version of the Hausman-Taylor model. We first estimate the coefficients of the time-varying regressors and subsequently regress the first-stage residuals on the time-invariant regressors...

This paper argues that any assessment on the intentional stance of fiscal policy should be based upon all the information available to policymakers at the time of fiscal planning. In particular, real-time data on the discretionary fiscal policy "instrument", the structural primary balance,...

This paper provides new evidence on the effects of government spending shocks and the fiscal transmission mechanism in the euro area for the period 1980-2008. Our contribution is two-fold. First, we investigate changes in the macroeconomic impact of government spending shocks using time-varying...

We develop a high-dimensional and partly nonlinear non-Gaussian dynamic factor model for the decomposition of systematic default risk conditions into a set of latent components that correspond with macroeconomic/financial, default-specific (frailty), and industry-specific effects. Discrete...

In this paper, we propose a time-varying parameter VAR model with stochastic volatility which allows for estimation on data sampled at different frequencies. Our contribution is twofold. First, we extend the methodology developed by Cogley and Sargent (2005), and Primiceri (2005), to a...

We propose a dynamic factor model for mixed-measurement and mixed-frequency panel data. In this framework time series observations may come from a range of families of parametric distributions, may be observed at different time frequencies, may have missing observations, and may exhibit common...

This paper provides new evidence on the effects of government spending shocks and the fiscal transmission mechanism in the euro area for the period 1980-2008. Our contribution is two-fold. First, we investigate changes in the macroeconomic impact of government spending shocks using time-varying...

We introduce a new dynamic clustering method for multivariate panel data char-acterized by time-variation in cluster locations and shapes, cluster compositions, and, possibly, the number of clusters. To avoid overly frequent cluster switching (flickering), we extend standard cross-sectional...

We investigate the dynamic properties of systematic default risk conditions for firms in different countries, industries and rating groups. We use a high-dimensional nonlinear non-Gaussian state space model to estimate common components in corporate defaults in a 41 country sample between...

We propose a novel framework to assess financial system risk. Using a dynamic factor framework based on state-space methods, we construct coincident measures (‘thermometers’) and a forward looking indicator for the likelihood of simultaneous failure of a large number of financial...