Dynamic Tobit models

Andew Harvey and Yin Liao

Econometrics and Statistics, 2023, vol. 26, issue C, 72-83

Abstract: Score-driven models provide a solution to the problem of modeling 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. Explanatory variables can be included, making static Tobit models a special case. A set of Monte Carlo experiments show that the score-driven model provides good forecasts even when the true model is parameter-driven. 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)
Date: 2023
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecosta:v:26:y:2023:i:c:p:72-83

DOI: 10.1016/j.ecosta.2021.08.012

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