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...

The paper investigates the linkages between temperature anomalies, radiative forcing and ENSO. By means of a new flexible trend modeling approach, we uncover a nonlinear linkage between radiative forcing and global temperature anomalies. The nonlinear trend closely tracks the low frequency...

Concurrent with the rapid development of the market for catastrophe (cat) bonds, a steady decline in their risk premia has been observed. Whether the latter trend is consistent with the evolution of natural disasters risk is an open question. Indeed, a large share of outstanding risk capital in...