posted on 2010-02-05, 16:50authored byKevin Lee, Nilss Olekalns, Kalvinder K. Shields
A canonical model is described which reflects the real time informational context of
decision-making. Comparisons are drawn with ‘conventional’ models that incorrectly omit
market-informed insights on future macroeconomic conditions and inappropriately incorporate
information that was not available at the time. It is argued that conventional
models are misspecified and misinterpret news. However, neither diagnostic tests applied
to the conventional models nor typical impulse response analysis will be able to expose
these deficiencies clearly. This is demonstrated through an analysis of quarterly US data
1968q4-2006q1. However, estimated real time models considerably improve out-of-sample
forecasting performance, provide more accurate ‘nowcasts’ of the current state of the
macroeconomy and provide more timely indicators of the business cycle. The point is illustrated
through an analysis of the US recessions of 1990q3—1991q2 and 2001q1—2001q4