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BEGIN:VEVENT
UID:7ae6bce206e73c943f0bf02ca2de2dbf
CATEGORIES:Seminars
CREATED:20150211T181805
SUMMARY:Lunch Seminar: Marco Lippi - EIEF
DESCRIPTION;ENCODING=QUOTED-PRINTABLE:<p style="line-height: normal;"><strong><span style="font-size: 12pt; font-
 family: 'Times New Roman','serif';">Forecasting US Inflation with a Dynamic
  Factor Model</span></strong></p><p style="line-height: normal;"><span styl
 e="font-size: 12pt; font-family: 'Times New Roman','serif';">Abstract:</spa
 n></p><p style="line-height: normal;"><span style="font-size: 12pt; font-fa
 mily: 'Times New Roman','serif';">The paper studies the pseudo real-time fo
 recasting performance of three different factor models. We compare the meth
 od recently proposed by Forni et al. (2015) and Forni et al. (2014) with th
 ose proposed in Forni et al. (2005) and Stock and Watson (2002a) within a r
 eal data forecasting exercise. A large panel of macroeconomic and financial
  time series for the US economy which includes the Great Recession and the 
 subsequent recovery is employed. In a rolling window framework, we find tha
 t the first two methods, based on spectral estimation, outperform the third
 . Substantial gains from regularized combinations of different inflation fo
 recasts produced with the model in Forni et al. </span><span style="font-si
 ze: 12pt; font-family: 'Times New Roman','serif';">(2015) are also found.</
 span></p>
DTSTAMP:20260404T122129Z
DTSTART:20141209T130000Z
DTEND:20141209T140000Z
SEQUENCE:0
TRANSP:OPAQUE
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