Forecasting with a panel Tobit model

Laura Liu, Hyungsik Roger Moon and Frank Schorfheide

Quantitative Economics, 2023, vol. 14, issue 1, 117-159

Abstract: We use a dynamic panel Tobit model with heteroskedasticity to generate 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. In addition to density forecasts, 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 loan charge‐off rates for small banks.

Date: 2023
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Citations: View citations in EconPapers (5)

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https://doi.org/10.3982/QE1505

Related works:
Working Paper: Forecasting with a Panel Tobit Model (2022)
Working Paper: Forecasting with a Panel Tobit Model (2019)
Working Paper: Forecasting with a Panel Tobit Model (2019)
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Persistent link: https://EconPapers.repec.org/RePEc:wly:quante:v:14:y:2023:i:1:p:117-159

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