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Dynamic Tobit models

Andrew Harvey and Yin Liao

Cambridge Working Papers in Economics from Faculty of Economics, University of Cambridge

Abstract: Score-driven models provide a solution to the problem of modelling time series when the observations are subject to censoring and location and/or scale may change over time. The method applies to generalized-t and EGB2 distributions, as well as to the normal distribution. A set of Monte Carlo experiments show that the score-driven model provides good forecasts even when the true model is parameterdriven. The viability of the new models is illustrated by fitting them to data on Chinese stock returns.

Keywords: Censored distributions; dynamic conditional score model; EGARCH models; logistic distribution; generalized t distribution (search for similar items in EconPapers)
JEL-codes: C22 C24 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm and nep-ets
Date: 2019-02-02
Note: ach34
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