Extending the inference function for augmented margins method to implement trivariate Clayton copula-based SUR Tobit models |
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Authors: | Paulo H Ferreira Francisco Louzada |
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Institution: | 1. Department of Statistics, Federal University of Bahia, Salvador, Bahia, Brazil;2. paulohenri@ufba.br;4. Department of Applied Mathematics and Statistics, University of S?o Paulo, S?o Carlos, S?o Paulo, Brazil |
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Abstract: | AbstractIn this paper, we perform the analysis of the SUR Tobit model for three left-censored dependent variables by modeling its nonlinear dependence structure through the one-parameter Clayton copula. For unbiased parameter estimation, we propose an extension of the Inference Function for Augmented Margins (IFAM) method to the trivariate case. The interval estimation for the model parameters using resampling procedures is also discussed. We perform simulation and empirical studies, whose satisfactory results indicate the good performance of the proposed model and methods. Our procedure is illustrated using real data on consumption of food items (salad dressings, lettuce, tomato) by Americans. |
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Keywords: | Bootstrap confidence intervals consumption data data augmentation trivariate one-parameter Clayton copula two-stage maximum likelihood estimation |
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