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Estimation of a Dynamic Tobit Model with a Unit Root

Anna Bykhovskaya, James A. Duffy

arXiv 13 Dec 2025 · Econometrics

arXiv:2512.12110 · PDF · DOI · OpenAlex · Extracted main text

Abstract

This paper studies robust estimation in the dynamic Tobit model under local-to-unity (LUR) asymptotics. We show that both Gaussian maximum likelihood (ML) and censored least absolute deviations (CLAD) estimators are consistent, extending results from the stationary case where ordinary least squares (OLS) is inconsistent. The asymptotic distributions of MLE and CLAD are derived; for the short-run parameters they are shown to be Gaussian, yielding standard normal t-statistics. In contrast, although OLS remains consistent under LUR, its t-statistics are not standard normal. These results enable reliable model selection via sequential t-tests based on ML and CLAD, paralleling the linear autoregressive case. Applications to financial and epidemiological time series illustrate their practical relevance.

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52
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108
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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
1Bykhovskaya, A (2023) Time series approach to the evolution of networks: prediction and estimation self1.00073100%
2de Jong, R. and Herrera, A. M (2011) Dynamic censored regression and the Open Market Desk reaction function1.00073100%
3Powell, James L (1984) Least absolute deviations estimation for the censored regression model1.00063100%
4Herce, Miguel A (1996) Asymptotic theory of LAD estimation in a unit root process with finite variance errors0.7373367%
5Bykhovskaya, Anna and Duffy, James A (2024) The local to unity dynamic Tobit model self0.66324729%
6Olsen, Randall J (1978) Note on the uniqueness of the maximum likelihood estimator for the Tobit model0.5112250%
7Xiao, Zhijie (2009) Quantile cointegrating regression0.51121100%
8Ramey, Valerie A and Zubairy, Sarah (2018) Government spending multipliers in good times and in bad: evidence from US historical data0.51121100%
9Aruoba, S. B. and Mlikota, M. and Schorfheide, F. and Villalvazo, S (2022) SVARs with occasionally-binding constraints0.40511100%
10Balke, Nathan S and Fomby, Thomas B (1997) Threshold cointegration0.40511100%

Showing the top 10 of 52 scored citations.