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

Andre Lucas, Anne Opschoor and Julia Schaumburg
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Anne Opschoor: VU University Amsterdam, the Netherlands
Julia Schaumburg: VU University Amsterdam, the Netherlands

No 16-067/IV, Tinbergen Institute Discussion Papers from Tinbergen Institute

Abstract: We show that two alternative perspectives on how to deal with missing data in the context of the score-driven time-varying parameter models of Creal, Koopman, Lucas (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.

Keywords: generalized autoregressive score models; missing completely at random; Expectation-Maximization (search for similar items in EconPapers)
JEL-codes: C52 C53 (search for similar items in EconPapers)
Date: 2016-08-29
New Economics Papers: this item is included in nep-ecm
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Citations: View citations in EconPapers (5)

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Journal Article: Accounting for missing values in score-driven time-varying parameter models (2016)
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Persistent link: https://EconPapers.repec.org/RePEc:tin:wpaper:20160067

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