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Forecasting with a Panel Tobit Model

Laura Liu, Hyungsik Roger Moon, Frank Schorfheide

arXiv 27 Oct 2021 · Econometrics · publishedQuantitative Economics (2023) · 13 citations (OpenAlex)

arXiv:2110.14117 · PDF · DOI · OpenAlex · Extracted main text

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.

Citation extraction

52
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distinct cited
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appendix boundary found by appendix_command · 63% of the source is main text. Read the extracted text to check this.

Most heavily cited references

The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.

ReferenceIntensityMentionsSectionsMain text
1Li and Zheng (2008) Semiparametric Bayesian Inference for Dynamic Tobit Panel Data Models with Unobserved Heterogeneity1.00053100%
2Baranchuk and Chib (2008) Assessing the role of option grants to CEOs: How important is heterogeneity?1.00053100%
3Ghosh (2017) Sector-specific Analysis of Non-performing Loans in the U.S. Banking System and their Macroeconomic Impact0.9416383%
4Liu (2021) Density Forecasts in Panel Data Models: A Semiparametric Bayesian Perspective self0.92843100%
5Wei (1999) A Bayesian Approach to Dynamic Tobit Models0.81142100%
6Chib (1992) Bayes Inference in the Tobit Censored Regression Model0.73732100%
7Ishwaran and James (2001) Gibbs Sampling Methods for Stick-Breaking Priors0.73732100%
8Liu, Moon, and Schorfheide (2020) Forecasting with Dynamic Panel Data Models self0.73732100%
9Botev (2017) The Normal Law under Linear Restrictions: Simulation and Estimation via Minimax Tilting0.64422100%
10Ghosh (2015) Banking-Industry Specific and Regional Economic Determinants of Non-performing Loans: Evidence from U.S. States0.64422100%

Showing the top 10 of 52 scored citations.

Cited by, within the corpus

arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.

Citing paperIntensityMentionsSections
1Binary Outcome Models with Extreme Covariates: Estimation and Prediction0.81142
2Bayesian Estimation of Panel Models under Potentially Sparse Heterogeneity0.64422
3Density Forecasts in Panel Data Models: A Semiparametric Bayesian Perspective0.40511
4Robust Empirical Bayes Confidence Intervals0.40511
50.5 in Robust Forecasting0.40511
6The Local to Unity Dynamic Tobit Model0.40511
72cm Optimal Estimation of Two-Way Effects under Limited Mobility0.40511
8Estimation of a Dynamic Tobit Model with a Unit Root0.40511
9Post-selection inference for network structure 10.40511