Academic literature on the topic 'Tobit models'
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Journal articles on the topic "Tobit models"
Brockwell, A. E., and N. H. Chan. "Long-memory dynamic Tobit models." Journal of Forecasting 25, no. 5 (August 2006): 351–67. http://dx.doi.org/10.1002/for.992.
Full textBauer, Thomas K., and Mathias Sinning. "Blinder–Oaxaca decomposition for Tobit models." Applied Economics 42, no. 12 (May 2010): 1569–75. http://dx.doi.org/10.1080/00036840701721612.
Full textSmith, Douglas A., and Robert Brame. "Tobit Models in Social Science Research." Sociological Methods & Research 31, no. 3 (February 2003): 364–88. http://dx.doi.org/10.1177/0049124102239080.
Full textSigelman, Lee, and Langche Zeng. "Analyzing Censored and Sample-Selected Data with Tobit and Heckit Models." Political Analysis 8, no. 2 (December 16, 1999): 167–82. http://dx.doi.org/10.1093/oxfordjournals.pan.a029811.
Full textLee, Lung-fei. "Estimation of dynamic and ARCH Tobit models." Journal of Econometrics 92, no. 2 (October 1999): 355–90. http://dx.doi.org/10.1016/s0304-4076(98)00095-5.
Full textWei, Steven X. "A bayesian approach to dynamic tobit models." Econometric Reviews 18, no. 4 (January 1999): 417–39. http://dx.doi.org/10.1080/07474939908800353.
Full textKliber, Paweł, and Artur Stefański. "Econometric Models in Resident Value of Investment." Oeconomia Copernicana 4, no. 3 (September 30, 2013): 49–63. http://dx.doi.org/10.12775/oec.2013.022.
Full textGuo, Yanyong, Zhibin Li, and Tarek Sayed. "Analysis of Crash Rates at Freeway Diverge Areas using Bayesian Tobit Modeling Framework." Transportation Research Record: Journal of the Transportation Research Board 2673, no. 4 (March 21, 2019): 652–62. http://dx.doi.org/10.1177/0361198119837219.
Full textPowell, James L. "Symmetrically Trimmed Least Squares Estimation for Tobit Models." Econometrica 54, no. 6 (November 1986): 1435. http://dx.doi.org/10.2307/1914308.
Full textFlood, Lennart, and Urban Gråsjö. "A Monte Carlo simulation study of Tobit models." Applied Economics Letters 8, no. 9 (September 2001): 581–84. http://dx.doi.org/10.1080/13504850010027581.
Full textDissertations / Theses on the topic "Tobit models"
Chen, Chunxia. "Semi-parametric estimation in Tobit regression models." Kansas State University, 2013. http://hdl.handle.net/2097/15300.
Full textDepartment of Statistics
Weixing Song
In the classical Tobit regression model, the regression error term is often assumed to have a zero mean normal distribution with unknown variance, and the regression function is assumed to be linear. If the normality assumption is violated, then the commonly used maximum likelihood estimate becomes inconsistent. Moreover, the likelihood function will be very complicated if the regression function is nonlinear even the error density is normal, which makes the maximum likelihood estimation procedure hard to implement. In the full nonparametric setup when both the regression function and the distribution of the error term [epsilon] are unknown, some nonparametric estimators for the regression function has been proposed. Although the assumption of knowing the distribution is strict, it is a widely adopted assumption in Tobit regression literature, and is also confirmed by many empirical studies conducted in the econometric research. In fact, a majority of the relevant research assumes that [epsilon] possesses a normal distribution with mean 0 and unknown standard deviation. In this report, we will try to develop a semi-parametric estimation procedure for the regression function by assuming that the error term follows a distribution from a class of 0-mean symmetric location and scale family. A minimum distance estimation procedure for estimating the parameters in the regression function when it has a specified parametric form is also constructed. Compare with the existing semiparametric and nonparametric methods in the literature, our method would be more efficient in that more information, in particular the knowledge of the distribution of [epsilon], is used. Moreover, the computation is relative inexpensive. Given lots of application does assume that [epsilon] has normal or other known distribution, the current work no doubt provides some more practical tools for statistical inference in Tobit regression model.
Leiker, Antoinette. "A comparison study on the estimation in Tobit regression models." Kansas State University, 2012. http://hdl.handle.net/2097/13804.
Full textDepartment of Statistics
Weixing Song
The goal of this report is to compare various estimation procedures on regression models in which the dependent variable has a restricted range. These models, called Tobit models, are seeing an increase in use among economists and market researchers, specifically. Only the standard Tobit regression model is discussed in the report. First we will examine the five estimation methods discussed in Amemiya (1984) for standard Tobit model. These methods include Probit maximum likelihood, least squares, Heckman’s two-step, Tobit maximum likelihood, and the EM algorithm. We will examine the algorithm utilized in each method’s estimation process. We will then conduct simulation studies using these estimation procedures. Twelve scenarios have been considered consisting of three different truncation threshold on the response variable, two distributions of covariates, and the error variance known and unknown. The results are reported and a discussion of the goodness of each method follows. The study shows that the best method for estimating Tobit regression models is indeed the Tobit maximum likelihood estimation. Heckman’s two-step method and the EM algorithm also estimate these models well when the truncation rate is low and the sample size is large. The simulation results show that the Least squares estimation procedure is far less efficient than other estimation procedures.
Zhang, Yi. "Empirical minimum distance lack-of-fit tests for Tobit regression models." Kansas State University, 2011. http://hdl.handle.net/2097/12123.
Full textDepartment of Statistics
Weixing Song
The purpose of this report is to propose and evaluate two lack-of-fit test procedures to check the adequacy of the regression functional forms in the standard Tobit regression models. It is shown that testing the null hypothesis for the standard Tobit regression models amounts testing a new equivalent null hypothesis of the classic regression models. Both procedures are constructed based on the empirical variants of a minimum distance, which measures the squared difference between a nonparametric estimator and a parametric estimator of the regression functions fitted under the null hypothesis for the new regression models. The asymptotic null distributions of the test statistics are investigated, as well as the power for some fixed alternatives and some local hypotheses. Simulation studies are conducted to assess the finite sample power performance and the robustness of the tests. Comparisons between these two test procedures are also made.
O'LEARY, CHRISTOPHER JOSEPH. "AN ECONOMETRIC ANALYSIS OF UNEMPLOYMENT INSURANCE BENEFIT ADEQUACY (RATIONING CONSTRAINTS, TOBIT MODELS)." Diss., The University of Arizona, 1986. http://hdl.handle.net/10150/183901.
Full textSilva, Paulo Henrique Ferreira da. "Multivariate Copula-based SUR Tobit Models : a modified inference function for margins and interval estimation." Universidade Federal de São Carlos, 2015. https://repositorio.ufscar.br/handle/ufscar/7226.
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
In this thesis, we extend the analysis of multivariate Seemingly Unrelated Regression (SUR) Tobit models by modeling their nonlinear dependence structures through copulas. The capability in coupling together the diferent - and possibly non-normal - marginal distributions allows the exible modeling for the SUR Tobit models. In addition, the ability to capture the tail dependence of the SUR Tobit models where some data are censored (e.g., in econometric analysis, clinical essays, wide range of political and social phenomena, among others, data are commonly left-censored at zero point, or right-censored at a point d > 0) is another useful feature of copulas. Our study proposes a modified version of the (classical) Inference Function for Margins (IFM) method by Joe & Xu (1996), which we refer to as MIFM method, to obtain the (point) estimates of the marginal and copula association parameters. More specifically, we use a (frequentist) data augmentation technique at the second stage of the IFM method (the first stage of the MIFM method is equivalent to the first stage of the IFM method) to generate the censored observations and then estimate the copula parameter. This procedure (data augmentation and copula parameter estimation) is repeated until convergence. Such modification at the second stage of the usual method is justified in order to obtain continuous marginal distributions, which ensures the uniqueness of the resulting copula, as stated by Sklar (1959)'s theorem; and also to provide an unbiased estimate of the copula association parameter (the IFM method provides a biased estimate of the copula parameter in the presence of censored observations in the margins). Since the usual asymptotic approach, that is the computation of the asymptotic covariance matrix of the parameter estimates, is troublesome in this case, we also propose the use of resampling procedures (bootstrap methods, like standard normal and percentile by Efron & Tibshirani (1993), and basic bootstrap by Davison & Hinkley (1997)) to obtain con_dence intervals for the copula-based SUR Tobit model parameters.
Nesta tese de doutorado, consideramos os chamados modelos SUR (da expressão Seemingly Unrelated Regression) Tobit multivariados e estendemos a análise de tais modelos ao empregar funções de cópula para modelar estruturas com dependência não linear. As cópulas, dentre outras características, possuem a importante habilidade (vantagem) de capturar/modelar a dependência na(s) cauda(s) do modelo SUR Tobit em que alguns dados são censurados (por exemplo, em análise econométrica, ensaios clínicos e em ampla gama de fenômenos políticos e sociais, dentre outros, os dados são geralmente censurados à esquerda no ponto zero, ou à direita em um ponto d > 0 qualquer). Neste trabalho, propomos uma versão modificada do método clássico da Inferência para as Marginais (IFM, da expressão Inference Function for Margins), originalmente proposto por Joe & Xu (1996), a qual chamamos de MIFM, para estimação (pontual) dos parâmetros do modelo SUR Tobit multivariado baseado em cópula. Mais especificamente, empregamos uma técnica (frequentista) de ampliação de dados no segundo estágio do método IFM (o primeiro estágio do método MIFM é igual ao primeiro estágio do método IFM) para gerar as observações censuradas e, então, estimamos o parâmetro de dependência da cópula. Repetimos tal procedimento (ampliação de dados e estimação do parâmetro da cópula) até obter convergência. As razões para esta modificação no segundo estágio do método usual, são as seguintes: primeiro, construir/obter distribuições marginais contínuas, atendendo, então, ao teorema de unicidade da cópula resultante de Sklar (Sklar, 1959); e segundo, fornecer uma estimativa não viesada para o parâmetro da cópula (uma vez que o método IFM produz estimativas viesadas do parâmetro da cópula na presença de observações censuradas nas marginais). Tendo em vista a dificuldade adicional em calcular/obter a matriz de covariâncias assintótica das estimativas dos parâmetros, também propomos o uso de procedimentos de reamostragem (métodos bootstrap, tais como normal padrão e percentil, propostos por Efron & Tibshirani (1993), e básico, proposto por Davison & Hinkley (1997)) para a construção de intervalos de confiança para os parâmetros do modelo SUR Tobit baseado em cópula.
Sousa, Mário Fernando de. "Two essays on Birnbaum-Saunders regression models for censored data." Universidade Federal de Goiás, 2016. http://repositorio.bc.ufg.br/tede/handle/tede/7235.
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES
This work aims to fill a gap in the literature on modeling asymmetric and censored data. The main objective is to provide a contribution by developing two models, which will be presented in two papers, respectively. In the first paper, we develop the tobit-Birnbaum-Saunders model, a variation of the standard tobit model. We discuss estimation based on the maximum likelihood method, residuals, diagnostic techniques and an empirical application. In the second paper, we propose the use of a mixture between the Birnbaum-Saunders and Bernoulli distributions. The objective is to generalize the tobit-Birnbaum-Saunders model in order to consider the possibility of partial observations below a cutoff point. For the mixture model, we carry out a Monte Carlo simulation study and an empirical application. The results show that, in both cases, the Birnbaum-Saunders distribution provides the best results.
Este trabalho visa preencher uma lacuna existente na literatura pertinente à modelagem de dados assimétricos e censurados. O objetivo principal é oferecer uma contribuição via o desenvolvimento de dois modelos, os quais serão apresentados em dois artigos. No primeiro artigo é proposto o modelo tobit-Birnbaum-Saunders, ou seja, uma variação do modelo tobit clássico, com estimação baseada no método de máxima verossimilhança, resíduos, técnicas de diagnóstico e uma aplicação a dados reais. No segundo artigo é abordada a utilização de um modelo de mistura entre as distribuições Birnbaum-Saunders e Bernoulli, de modo a generalizar o modelo tobit-Birnbaum-Saunders e considerar a possibilidade de observações parciais abaixo do ponto de corte. Para o modelo de mistura são realizadas simulações de Monte Carlo e uma aplicação a dados reais. Os resultados mostram que, em ambos os casos, a distribuição Birnbaum-Saunders oferece os melhores resultados.
Correia, Leandro Tavares. "Modelos de regressão estáticos e dinâmicos para taxas ou proporções: uma abordagem bayesiana." Universidade de São Paulo, 2015. http://www.teses.usp.br/teses/disponiveis/45/45133/tde-27082015-224138/.
Full textThis paper presents a study focused on observations in a limited interval , more specifically in [0,1] , such as rate and proportion data. In many practical cases this data structure has a considerable amount of extreme values (0 and 1) and usual classical models are not suitable for this type of data set. We propose two class of regression models to deal with this context: beta inflated of zeros and ones (BIZU) models and Tobit doubly censored models adapted in this interval. Fit quality and diagnostic techniques are also discussed. Time series of proportions are also developed through Bayesian dynamic models. Forecasting and behavioral analysis were explored using sequential Monte Carlo techniques, known as particle filters. Particularities and competitiveness between the two classes of models were also discussed as well.
Xu, Xingbai Xu. "Asymptotic Analysis for Nonlinear Spatial and Network Econometric Models." The Ohio State University, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=osu1461249529.
Full textMater, Gautier. "Caractérisation des mesures d’exposition à des produits chimiques dans les bases de données françaises COLCHIC et SCOLA pour la prévention des maladies professionnelles." Thesis, Université de Lorraine, 2016. http://www.theses.fr/2016LORR0210/document.
Full textTwo occupational exposure databases of occupational exposures to chemicals, COLCHIC and SCOLA, coexist in France with different objectives (prevention and compliance). Little is known about their representativeness of exposures in the general population. We explored to what extent COLCHIC and SCOLA adequately reflect occupational exposures in France. After performing a descriptive and comparative analysis, associations between exposure levels and ancillary information were explored for each agent, separately for COLCHIC and SCOLA and in a common dataset, using statistical modelling. Modelling results were synthesized across agents using Meta analysis. COLCHIC and SCOLA contain, respectively, 929 700 (670 chemicals) and 429 104 records (105). Three predictors "Sample Time", "Personal protective equipment" and "Year" are strongly associated with exposure levels across a large majority of chemicals in both databases, and 3 others are specific to each one. Exposure levels are in average twice higher in COLCHIC compared to SCOLA in 2007, but become comparable from 2012-2015. COLCHIC and SCOLA are an important source of information. Inclusion of descriptors associated with exposure levels in our study and the use of predictive methods should help to improve their interpretation
Park, In Kwon. "Essays on a City’s Assets: Agglomeration Economies and Legacy Capital." The Ohio State University, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=osu1269458854.
Full textBooks on the topic "Tobit models"
Powell, James. Symmetrically trimmed least squares estimation for Tobit models. Cambridge, Mass: Dept. of Economics, Massachusetts Institute of Technology, 1985.
Find full textCrawford, Allan. Downward nominal-wage rigidity: Micro evidence from Tobit models. Ottawa: Bank of Canada, 2001.
Find full textCrawford, Allan. Downward nominal-wage rigidity: Micro evidence from Tobit models. Ottawa, Ont: Bank of Canada, 2001.
Find full textRohweder, Herold C. Wechselkursvariabilität und internationaler Handel: Eine empirische Analyse der räumlichen Handelsverflechtung im Rahmen eines TOBIT-Regressionsansatzes. München: V. Florentz, 1989.
Find full textGomulka, J. Gamma-tobit: A tobit type model with Y-distributed error term. London: Taxation, Incentives and theDistribution of Income Programme, 1986.
Find full textBlundell, Richard. Estimation in the simultaneous equation Tobit model. London: University College, 1985.
Find full textBhattacharya, Joydeep. The Tobin effect and the Friedman rule. [New York, N.Y.]: Federal Reserve Bank of New York, 2005.
Find full textPohlmeier, Winfried. Simultane Probit- und Tobitmodelle: Theorie und Anwendungen auf Fragen der Innovationsökonomik. Berlin: Springer-Verlag, 1989.
Find full textSmith, Richard J. An exogeneity test for a simultaneous equation Tobit model with an application to labour supply. London: University College, 1985.
Find full textHuang, Hui. Baumol-Tobin and the welfare costs of national security border delays. Cambridge, Mass: National Bureau of Economic Research, 2006.
Find full textBook chapters on the topic "Tobit models"
Cunillera, Oriol. "Tobit Models." In Encyclopedia of Quality of Life and Well-Being Research, 6671–76. Dordrecht: Springer Netherlands, 2014. http://dx.doi.org/10.1007/978-94-007-0753-5_3025.
Full textKrause, A., and W. Polasek. "Approaches to Tobit Models via Gibbs Sampling." In Computational Statistics, 559–64. Heidelberg: Physica-Verlag HD, 1992. http://dx.doi.org/10.1007/978-3-662-26811-7_77.
Full textJintranun, Jintanee, Peter Calkins, and Songsak Sriboonchitta. "Charitable Giving Behavior in Northeast Thailand and Mukdaharn Province: Multivariate Tobit Models." In Uncertainty Analysis in Econometrics with Applications, 269–81. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-35443-4_19.
Full textRobin, Jean-Marc. "Tobit Model." In The New Palgrave Dictionary of Economics, 1–5. London: Palgrave Macmillan UK, 2008. http://dx.doi.org/10.1057/978-1-349-95121-5_2349-1.
Full textRobin, Jean-Marc. "Tobit Model." In The New Palgrave Dictionary of Economics, 13707–11. London: Palgrave Macmillan UK, 2018. http://dx.doi.org/10.1057/978-1-349-95189-5_2349.
Full textRobin, Jean-Marc. "Tobit model." In Microeconometrics, 323–28. London: Palgrave Macmillan UK, 2010. http://dx.doi.org/10.1057/9780230280816_35.
Full textDimand, Robert W. "Transforming the IS-LM Model Sector By Sector." In James Tobin, 24–43. London: Palgrave Macmillan UK, 2014. http://dx.doi.org/10.1057/9781137431950_3.
Full textPapalia, Rosa Bernardini, and Francesca Di Iorio. "Alternative Error Term Specifications in the Log-Tobit Model1." In Advances in Classification and Data Analysis, 185–92. Berlin, Heidelberg: Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/978-3-642-59471-7_23.
Full textWindzio, Michael. "Abgeschnittene, zensierte und selektive Daten: Tobit-Regression und Heckman-Modell." In Regressionsmodelle für Zustände und Ereignisse, 255–83. Wiesbaden: Springer Fachmedien Wiesbaden, 2013. http://dx.doi.org/10.1007/978-3-531-18852-2_10.
Full textAsada, Toichiro, Peter Flaschel, Tarik Mouakil, and Christian Proaño. "Analysis and Policy Implications of the KMG-Tobin Model." In Asset Markets, Portfolio Choice and Macroeconomic Activity, 62–92. London: Palgrave Macmillan UK, 2011. http://dx.doi.org/10.1057/9780230307773_4.
Full textConference papers on the topic "Tobit models"
Çağlayan Akay, Ebru, and Zamira Oskonbaeva. "An Empirical Analysis of the Linder Theory for Organisation for Economic Co-Operation and Development Member Countries." In International Conference on Eurasian Economies. Eurasian Economists Association, 2017. http://dx.doi.org/10.36880/c08.01854.
Full textODAH, Meshal Harbi, Bahr KADHIM MOHAMMED, and Ali SADIG MOHOMMED BAGER. "Tobit Regression Model to Determine the Dividend Yield in Iraq." In 3rd Central & Eastern European LUMEN International Conference – New Approaches in Social and Humanistic Sciences | NASHS 2017| Chisinau, Republic of Moldova | June 8-10, 2017. LUMEN Publishing House, 2018. http://dx.doi.org/10.18662/lumproc.nashs2017.30.
Full textMurakami, Yukasa, Masateru Tsunoda, and Koji Toda. "An Empirical Evaluation of the Tobit Model on Software Defect Prediction." In 2016 4th Intl Conf on Applied Computing and Information Technology/3rd Intl Conf on Computational Science/Intelligence and Applied Informatics/1st Intl Conf on Big Data, Cloud Computing, Data Science & Engineering (ACIT-CSII-BCD). IEEE, 2016. http://dx.doi.org/10.1109/acit-csii-bcd.2016.046.
Full textLee, Seung-gil, and Sun Young Chang. "Demand Model for Adult Continuing Education using the Tobit model and the Heckman Selection Model." In Education 2015. Science & Engineering Research Support soCiety, 2015. http://dx.doi.org/10.14257/astl.2015.103.27.
Full textZhao, Yuanping, Qiang Yan, and Huaying Shu. "A Tobit Model on Message Transfer and Control in Instant Message Systems." In 2009 5th International Conference on Wireless Communications, Networking and Mobile Computing (WiCOM). IEEE, 2009. http://dx.doi.org/10.1109/wicom.2009.5305431.
Full textChen, Junmin, Nataliya Stoyanets, and Zetao Hu. "RESEARCH ON INFLUENCING FACTORS OF RURAL ENDOGENOUS DEVELOPMENT ABILITY BASED ON TOBIT MODEL." In 6th International Scientific Conference ERAZ - Knowledge Based Sustainable Development. Association of Economists and Managers of the Balkans, Belgrade, Serbia, 2020. http://dx.doi.org/10.31410/eraz.2020.231.
Full textMirzaMoghadam, A. V., A. Riahi, and M. Morris. "High Pressure Turbine Low Radius Radial TOBI Discharge Coefficient Validation Process." In ASME 2011 Turbo Expo: Turbine Technical Conference and Exposition. ASMEDC, 2011. http://dx.doi.org/10.1115/gt2011-45113.
Full textAndaiyani, Sri, Saadah Yuliana, and Fida Muthia. "Testing Baumol-Tobin Model Toward Millennials in Palembang City." In 5th Sriwijaya Economics, Accounting, and Business Conference (SEABC 2019). Paris, France: Atlantis Press, 2020. http://dx.doi.org/10.2991/aebmr.k.200520.005.
Full textWu, Wen-qing, Fei Xie, and Li-ming Zhao. "A study on the operation of Chinese university science park based on DEA-Tobit model." In EM2010). IEEE, 2010. http://dx.doi.org/10.1109/icieem.2010.5646090.
Full textShan, Hongmei, Xueyuan Xiao, and Jing Shi. "Efficiency and Its Influencing Factors Analysis of E-commerce based on DEA and Tobit Model." In the 2019 3rd International Conference. New York, New York, USA: ACM Press, 2019. http://dx.doi.org/10.1145/3312662.3312700.
Full textReports on the topic "Tobit models"
Liu, Laura, Hyungsik Roger Moon, and Frank Schorfheide. Forecasting with a Panel Tobit Model. Cambridge, MA: National Bureau of Economic Research, December 2019. http://dx.doi.org/10.3386/w26569.
Full textDay, Christopher M., Hiromal Premachandra, and Darcy M. Bullock. Characterizing the Impacts of Phasing, Environment, and Temporal Factors on Pedestrian Demand at Traffic Signals. Purdue University, 2011. http://dx.doi.org/10.5703/1288284317352.
Full textIV methods for Tobit models. Cemmap, June 2021. http://dx.doi.org/10.47004/wp.cem.2021.2621.
Full text