Results 1 to 10 of about 45,080 (138)
"Tobit Model with Covariate Dependent Thresholds" [PDF]
Computational Statistics & Data Analysis, 2010 Tobit models are extended to allow threshold values which depend on individuals' characteristics. In such models, the parameters are subject to as many inequality constraints as the number of observations, and the maximum likelihood estimation which ...
Koji Miyawaki, Yasuhiro Omori
core +3 more sources
Blinder-Oaxaca Decomposition for Tobit Models [PDF]
SSRN Electronic Journal, 2005 In this paper, a decomposition method for Tobit-models is derived, which allows the differences in a censored outcome variable between two groups to be decomposed into a part that is explained by differences in observed characteristics and a part ...
Mathias Sinning, Thomas Bauer
core +9 more sources
Journal of Econometrics, 2021 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Chesher, Andrew +2 more
openaire +5 more sources
Econometrics and Statistics, 2023 Score-driven models provide a solution to the problem of modelling 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.
Andew Harvey, Yin Liao
openaire +1 more source
Long-memory dynamic Tobit models [PDF]
Journal of Forecasting, 2006 We introduce a long-memory dynamic Tobit model, defining it as a censored version of a fractionally-integrated Gaussian ARMA model, which may include seasonal components and/or additional regression variables. Parameter estimation for such a model using standard techniques is typically infeasible, since the model is not Markovian, cannot be expressed ...
Brockwell, Anthony, N. H. Chan
openaire +1 more source
Forecasting with a Panel Tobit Model [PDF]
SSRN Electronic Journal, 2019 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 ...
Liu, Laura +2 more
openaire +4 more sources
Bayesian analysis of a Tobit quantile regression model [PDF]
, 2007 This paper develops a Bayesian framework for Tobit quantile regression. Our approach is organized around a likelihood function that is based on the asymmetric Laplace dis- tribution, a choice that turns out to be natural in this context.
Stander, J, Yu, K
core +1 more source
Kahramanmaraş Sütçü İmam Üniversitesi Doğa Bilimleri Dergisi, 2018 Bu calismada sinirli bagimli degiskenli modelleri aciklamada yaygin bicimde kullanilan Tobit Model incelenmistir. Calismanin amaci bagimli degiskeni s i nirli olan veri setlerinin parametre tahmin basamaklarini hem teorik olarak hem de bir uygulama ile anlatmaya calismaktir. Literatur tarama yontemi kullanilarak tobit model ana cizgileri ile anlatilmis,
KOÇ, Şeyma, ŞAHİN, Mustafa
openaire +3 more sources
Communications in Statistics - Theory and Methods, 2013 The main object of this article is to propose an extension of the tobit model for which the error distribution follows the power-normal distribution (Gupta and Gupta, 2008). Inference is dealt with by using the likelihood approach. Simulation studies and application to a real data set are used to demonstrate the usefulness of the extension.
Martinez-Florez, Guillermo +2 more
openaire +3 more sources
Tobit models in strategy research: Critical issues and applications [PDF]
Global Strategy Journal, 2019 AbstractResearch SummaryTobit models have been used to address several questions in management research. Reviewing existing practices and applications, we discuss three challenges: (a) assumptions about the nature of data, (b) apparent interchangeability between censoring and selection bias, and (c) potential violations of key assumptions in the ...
Mario Daniele Amore, Samuele Murtinu
openaire +2 more sources