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Accounting for missing values in score-driven time-varying parameter models

Andre Lucas, Anne Opschoor, Julia Schaumburg
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.
Year of publication:
2016-08-29
Authors: Lucas, André ; Opschoor, Anne ; Schaumburg, Julia
Publisher: Amsterdam : Tinbergen Institute
Subject: generalized autoregressive score models | missing completely at random | Expectation-Maximization
freely available
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