Dynamic Tobit models
Andrew Harvey and
Cambridge Working Papers in Economics from Faculty of Economics, University of Cambridge
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)
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Persistent link: https://EconPapers.repec.org/RePEc:cam:camdae:1913
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