Factor Vector Autoregressive Estimation of Heteroskedastic Persistent and Non Persistent Processes Subject to Structural Breaks: New Insights on the US OIS SPreads Term Structure

In the paper a general framework for large scale modeling of macroeconomic and financial time series is introduced. The proposed approach is characterized by simplicity of implementation, performing well independently of persistence and heteroskedasticity properties, accounting for common deterministic and stochastic factors. Monte Carlo results strongly support the proposed methodology, validating its use also for relatively small cross-sectional and temporal samples. By means of the proposed approach, new insights on US money market dynamics during the subprime and euro area financial crises are achieved. Moreover, three common factors, bearing the interpretation of level, slope and curvature factors, are extracted from the term structure of OIS spreads; we find the latter conveying additional information, relatively to commonly used credit risk measures like the TED or the BAA-AAA corporate spreads, which might be exploited, also within a composite indicator, for the construction of a risk barometer and real-time macroeconomic forecasting.