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PRODID:https://www.diw.de/de/diw_01.c.806339.de/veranstaltungen.html
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UID:diw_01.c.942635.en
LOCATION:Francine D. Blau Room,DIW Berlin,3.3.002b,Anton-Wilhelm-Amo-Strasse 58,10117 Berlin
SUMMARY:Proxy Vector Autoregressive Analysis
DESCRIPTION:23. 3.: 10
a.m.-1 p.m. and 2-5 p.m.

24. 3.: 10
a.m.-1 p.m. // In modern empirical macroeconomics, structural vector autoregressions (SVARs) are routinely used to trace out the responses of macroeconomic variables to structural shocks. These structural shocks could be monetary policy shocks, tax shocks, oil price shocks, and many others. For example, central banks use SVARs to analyse the effects of interest movements on the economy. A crucial step in this model class is identification, meaning the step from pure correlation among variables towards causal statements. One way to achieve identification is the use of external instruments or proxies. These proxies are potentially noisy measurements of the shocks of interest. In this Masterclass we are going to investigate methods to include proxies in SVARs, so-called Proxy VARs.  Several issues related to Proxy VARs will be discussed. First, we are going to compare the standard VAR approach to a popular alternative, local projections. Second, we will investigate Bayesian approaches for estimation. Third, we are going to investigate the role of heteroskedasticity in this model class. Fourth, we are going to illustrate some of these issues using real data related to the global oil market and US monetary policy.
DTSTART;VALUE=DATE:20260322T220000Z
DTEND;VALUE=DATE:20260324T220000Z
DTSTAMP:20250427T220000Z
URL:https://www.diw.de/en/diw_01.c.942635.en/events/proxy_vector_autoregressive_analysis.html
ORGANIZER;CN=Laura Starck:mailto:lstarck@diw.de
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