Accounting for Missing Values in Score- Driven Time-Varying Parameter Models

نویسندگان

  • André Lucas
  • Anne Opschoor
  • Julia Schaumburg
چکیده

We show that two alternative perspectives on how to deal with missing data in the context of the score-driven timevarying parameter models of Creal et al. (2013) and Harvey (2013) lead to precisely the same dynamic transition equations. As score-driven models encompass a wide variety of time-varying parameter models (including generalized autoregressive conditional volatility (GARCH) and duration (ACD) models), the results apply to a wide range of empirically relevant models as applied in economics and statistics.

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تاریخ انتشار 2016