Advances in Using Vector Autoregressions to Estimate Structural Magnitudes
This paper surveys recent advances in drawing structural conclusions from vector autoregressions (VARs), providing a unified perspective on the role of prior knowledge. We describe the traditional approach to identification as a claim to have exact prior information about the structural model and propose Bayesian inference as a way to acknowledge that prior information is imperfect or subject to error. We raise concerns from both a frequentist and a Bayesian perspective about the way that results are typically reported for VARs that are set-identified using sign and other restrictions. We call attention to a common but previously unrecognized error in estimating structural elasticities and show how to correctly estimate elasticities even in the case when one only knows the effects of a single structural shock.
IWH Medium-Term Projection The IWH medium-term projection shows: If Germany wants to stick to both its current debt...
Centre for Evidence-based Policy Advice
Centre for Evidence-based Policy Advice (IWH-CEP) ...
Data Protection Policy ...
IWH FDI Micro Database
IWH FDI Micro Database The IWH FDI Micro Database (FDI = Foreign Direct...
What Explains International Interest Rate Co-Movement? ...
Advances in Using Vector Autoregressions to Estimate Structural Magnitudes ...
Info Graphs Sometimes pictures say more than a thousand words. Therefore, we selected...
The Effects of Sovereign Risk: A High Frequency Identification Based on News Ticker Data
IWH Discussion Papers,
This paper uses novel news ticker data to evaluate the effect of sovereign risk on economic and financial outcomes. The use of intraday news enables me to derive policy events and respective timestamps that potentially alter investors’ beliefs about a sovereign’s willingness to service its debt and thereby sovereign risk. Following the high frequency identification literature, in the tradition of Kuttner (2001) and Guerkaynak et al. (2005), associated variation in sovereign risk is then obtained by capturing bond price movements within narrowly defined time windows around the event time. I conduct the outlined identification for Italy since its large bond market and its frequent coverage in the news render it a suitable candidate country. Using the identified shocks in an instrumental variable local projection setting yields a strong instrument and robust results in line with theoretical predictions. I document a dampening effect of sovereign risk on output. Also, borrowing costs for the private sector increase and inflation rises in response to higher sovereign risk.