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Forecasting with a Panel Tobit Model

Laura Liu (), Hyungsik Moon () and Frank Schorfheide ()

No 26569, NBER Working Papers from National Bureau of Economic Research, Inc

Abstract: We use a dynamic panel Tobit model with heteroskedasticity to generate point, set, and density forecasts for a large cross-section of short time series of censored observations. Our fully Bayesian approach allows us to flexibly estimate the cross-sectional distribution of heterogeneous coefficients and then implicitly use this distribution as prior to construct Bayes forecasts for the individual time series. We construct set forecasts that explicitly target the average coverage probability for the cross-section. We present a novel application in which we forecast bank-level charge-off rates for credit card and residential real estate loans, comparing various versions of the panel Tobit model.

JEL-codes: C11 C14 C23 C53 G21 (search for similar items in EconPapers)
Date: 2019-12
New Economics Papers: this item is included in nep-ban, nep-for and nep-ore
Note: EFG ME
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