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Estimating DSGE models with unknown data persistence

Listed author(s):
  • Gianluca Moretti

    ()

    (Bank of Italy)

  • Giulio Nicoletti

    ()

    (Bank of Italy)

Registered author(s):

    Recent empirical literature shows that key macro variables such as GDP and productivity display long memory dynamics. For DSGE models, we propose a �Generalized� Kalman Filter to deal effectively with this problem: our method connects to and innovates upon data-filtering techniques already used in the DSGE literature. We show our method produces more plausible estimates of the deep parameters as well as more accurate out-of-sample forecasts of macroeconomic data.

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    File URL: http://www.bancaditalia.it/pubblicazioni/temi-discussione/2010/2010-0750/en_Tema_750.pdf
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    Paper provided by Bank of Italy, Economic Research and International Relations Area in its series Temi di discussione (Economic working papers) with number 750.

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    Date of creation: Mar 2010
    Handle: RePEc:bdi:wptemi:td_750_10
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